Geoffrey Hubona

95% off Comprehensive Linear Modeling with R (Coupon)

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Comprehensive Linear Modeling with R - Udemy Coupon

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Coupon & course info

Course Name: Comprehensive Linear Modeling with R

Subtitle: Learn to model with R: ANOVA, regression, GLMs, survival analysis, GAMs, mixed-effects, split-plot and nested designs

Instructor: Taught by Geoffrey Hubona, Professor of Information Systems

Category: Business

Subcategory: Data & Analytics

Provided by: Udemy

Price: $99 (before discount)

Free coupon code: See above (no charge for coupon)

Review info & popularity

As of March 9, 2016…

Students: 39390 students enrolled

Ratings: 2 reviews

Rank: ranked #439 in Udemy Business Courses

Brief course description

Comprehensive Linear Modeling with R provides a wide overview of numerous contemporary linear and non-linear modeling approaches for the analysis of research data. These include basic, conditional and simultaneous inference techniques; analysis of variance (ANOVA); linear regression; survival analysis; generalized linear models (GLMs); parametric and non-parametric smoothers and generalized additive models (GAMs); longitudinal and mixed-effects, split-plot and other nested model designs. The course showcases the use of R Commander in performing these tasks. R Commander is a popular GUI-based “front-end” to the broad range of embedded statistical functionality in R software. R Commander is an ‘SPSS-like’ GUI that enables the implementation of a large variety of statistical and graphical techniques using both menus and scripts. Please note that the R Commander GUI is written in the RGtk2 R-specific visual language (based on GTK+) which is known to have problems running on a Mac computer.

The course progresses through dozens of statistical techniques by first explaining the concepts and then demonstrating the use of each with concrete examples based on actual studies and research data. Beginning with a quick overview of different graphical plotting techniques, the course then reviews basic approaches to establish inference and conditional inference, followed by a review of analysis of variance (ANOVA). The course then progresses through linear regression and a section on validating linear models. Then generalized linear modeling (GLM) is explained and demonstrated with numerous examples. Also included are sections explaining and demonstrating linear and non-linear models for survival analysis, smoothers and generalized additive models (GAMs), longitudinal models with and without generalized estimating equations (GEE), mixed-effects, split-plot, and nested designs. Also included are detailed examples and explanations of validating linear models using various graphical displays, as well as comparing alternative models to choose the ‘best’ model. The course concludes with a section on the special considerations and techniques for establishing simultaneous inference in the linear modeling domain.

The rather long course aims for complete coverage of linear (and some non-linear) modeling approaches using R and is suitable for beginning, intermediate and advanced R users who seek to refine these skills. These candidates would include graduate students and/or quantitative and/or data-analytic professionals who perform linear (and non-linear) modeling as part of their professional duties.

(Read more about this course on the official course page.)

Geoffrey Hubona bio

Dr. Geoffrey Hubona has been a full-time faculty member at 3 major state universities in the Eastern United States for 20 years, teaching dozens of different statistics, business information systems, and computer science courses to undergraduate, master’s and PhD students. He earned a PhD in Information Systems and Computer Science (1993) from the University of South Florida in Tampa, FL (1993); an MA in Economics (1990) from USF; an MBA in Finance (1979) from George Mason University in Fairfax, VA; and a BA in Psychology (1972) from the University of Virginia in Charlottesville, VA. He held full-time faculty positions at the University of Maryland Baltimore County (1993-1996), Virginia Commonwealth University (1996-2001), and Georgia State University (2001-2010). He is the founder of the Georgia R School (2010), a non-profit online educational institution that teaches research methods and quantitative analysis techniques such as linear and non-linear modeling, multivariate methods, data mining, programming and simulation, and structural equation modeling and partial least squares (PLS) path modeling. Dr. Hubona is recognized as an expert of the analytical, open-source R software suite and of various path modeling software packages, including SmartPLS. He has published dozens of research articles that explain and use these techniques for the analysis of data, and, with software co-development partner Dean Lim, has created a popular cloud-based PLS software application, PLS-GUI.

(Learn more about this instructor on the official course page.)

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Final details for this Udemy course

Languages: English

Skill level: All Levels

Lectures: 104 lessons

Duration: 14.5 Hours of video

What you get: Understand, use and apply, estimate, interpret and validate: ANOVA; regression; survival analysis; GLMs; smoothers and GAMs; longitudinal, mixed-effects, split-plot and nested model designs using their own data and R software.

Target audience: This course is aimed at graduate students and working quantitative and data-analytic professionals who seek to acquire a wide range of linear (and non-linear) modeling skills using R.

Requirements: Students will need to install R and R Commander using the ample video and written instructions that are provided for doing so.

Access: Lifetime access

Peace of mind: 30 day money back guarantee

Availability: available online, as well as on iOS and Android

Download options: check course to see if you can download lessons

95% off Multivariate Data Visualization with R (Coupon)

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Multivariate Data Visualization with R - Udemy Coupon

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Bonus: download a free guide that reveals 11 tricks for getting the biggest discounts on Udemy courses, including this course.

Coupon & course info

Course Name: Multivariate Data Visualization with R

Subtitle: Course describes and demonstrates a creative approach for constructing and drawing grid-based multivariate graphs in R

Instructor: Taught by Geoffrey Hubona, Professor of Information Systems

Category: Business

Subcategory: Data & Analytics

Provided by: Udemy

Price: $49 (before discount)

Free coupon code: See above (no charge for coupon)

Review info & popularity

As of March 9, 2016…

Students: 1515011 students enrolled

Ratings: 4 reviews

Rank: ranked #522 in Udemy Business Courses

Brief course description

It is often both useful and revealing to create visualizations, plots and graphs of the multivariate data that is the subject of one’s research project. Often, both pre-analysis and post-analysis visualizations can help one understand “what is going on in the data” in a way that looking at numerical summaries of fitted model estimates cannot. The lattice package in R is uniquely designed to graphically depict relationships in multivariate data sets.

This course describes and demonstrates this creative approach for constructing and drawing grid-based multivariate graphic plots and figures using R. Lattice graphics are characterized as multi-variable (3, 4, 5 or more variables) plots that use conditioning and paneling. Consequently, it is a popular approach for, and a good fit to visually present the results of multi-variable statistical model fitting. The appearance of most of the plots, graphs and figures are determined by panel functions, rather than by the high-level graphics function calls themselves. Further, the user of lattice graphics has extensive and comprehensive control over many more of the details and features of the visual plots, far greater control that is afforded by the base graphics approach in R. The method is based on trellis graphics which were popularized in the S language developed by Bell Labs.

…

(Read more about this course on the official course page.)

Geoffrey Hubona bio

Dr. Geoffrey Hubona has been a full-time faculty member at 3 major state universities in the Eastern United States for 20 years, teaching dozens of different statistics, business information systems, and computer science courses to undergraduate, master’s and PhD students. He earned a PhD in Information Systems and Computer Science (1993) from the University of South Florida in Tampa, FL (1993); an MA in Economics (1990) from USF; an MBA in Finance (1979) from George Mason University in Fairfax, VA; and a BA in Psychology (1972) from the University of Virginia in Charlottesville, VA. He held full-time faculty positions at the University of Maryland Baltimore County (1993-1996), Virginia Commonwealth University (1996-2001), and Georgia State University (2001-2010). He is the founder of the Georgia R School (2010), a non-profit online educational institution that teaches research methods and quantitative analysis techniques such as linear and non-linear modeling, multivariate methods, data mining, programming and simulation, and structural equation modeling and partial least squares (PLS) path modeling. Dr. Hubona is recognized as an expert of the analytical, open-source R software suite and of various path modeling software packages, including SmartPLS. He has published dozens of research articles that explain and use these techniques for the analysis of data, and, with software co-development partner Dean Lim, has created a popular cloud-based PLS software application, PLS-GUI.

(Learn more about this instructor on the official course page.)

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Final details for this Udemy course

Languages: English

Skill level: All Levels

Lectures: 32 lessons

Duration: 7 Hours of video

What you get: Graphically depict visual 2D, 3D, 4D (and so on) relationships that exist in multivariate data sets.

Target audience: Anyone who uses R, or who wants to use R, for any sort of multivariate data analysis would benefit from taking this course.

Requirements: Students will need to install R and RStudio (instructions are provided in the course materials).

Access: Lifetime access

Peace of mind: 30 day money back guarantee

Availability: available online, as well as on iOS and Android

Download options: check course to see if you can download lessons

95% off R Programming for Simulation and Monte Carlo Methods (Coupon)

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R Programming for Simulation and Monte Carlo Methods - Udemy Coupon

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Bonus: download a free guide that reveals 11 tricks for getting the biggest discounts on Udemy courses, including this course.

Coupon & course info

Course Name: R Programming for Simulation and Monte Carlo Methods

Subtitle: Learn to program statistical applications and Monte Carlo simulations with numerous “real-life” cases and R software.

Instructor: Taught by Geoffrey Hubona, Professor of Information Systems

Category: Business

Subcategory: Data & Analytics

Provided by: Udemy

Price: $49 (before discount)

Free coupon code: See above (no charge for coupon)

Review info & popularity

As of March 9, 2016…

Students: 741 students enrolled

Ratings: 3 reviews

Rank: ranked #592 in Udemy Business Courses

Brief course description

R Programming for Simulation and Monte Carlo Methods focuses on using R software to program probabilistic simulations, often called Monte Carlo Simulations. Typical simplified “real-world” examples include simulating the probabilities of a baseball player having a ‘streak’ of twenty sequential season games with ‘hits-at-bat’ or estimating the likely total number of taxicabs in a strange city when one observes a certain sequence of numbered cabs pass a particular street corner over a 60 minute period. In addition to detailing half a dozen (sometimes amusing) ‘real-world’ extended example applications, the course also explains in detail how to use existing R functions, and how to write your own R functions, to perform simulated inference estimates, including likelihoods and confidence intervals, and other cases of stochastic simulation. Techniques to use R to generate different characteristics of various families of random variables are explained in detail. The course teaches skills to implement various approaches to simulate continuous and discrete random variable probability distribution functions, parameter estimation, Monte-Carlo Integration, and variance reduction techniques. The course partially utilizes the Comprehensive R Archive Network (CRAN) spuRs package to demonstrate how to structure and write programs to accomplish mathematical and probabilistic simulations using R statistical software.

…

…

(Read more about this course on the official course page.)

Geoffrey Hubona bio

Dr. Geoffrey Hubona has been a full-time faculty member at 3 major state universities in the Eastern United States for 20 years, teaching dozens of different statistics, business information systems, and computer science courses to undergraduate, master’s and PhD students. He earned a PhD in Information Systems and Computer Science (1993) from the University of South Florida in Tampa, FL (1993); an MA in Economics (1990) from USF; an MBA in Finance (1979) from George Mason University in Fairfax, VA; and a BA in Psychology (1972) from the University of Virginia in Charlottesville, VA. He held full-time faculty positions at the University of Maryland Baltimore County (1993-1996), Virginia Commonwealth University (1996-2001), and Georgia State University (2001-2010). He is the founder of the Georgia R School (2010), a non-profit online educational institution that teaches research methods and quantitative analysis techniques such as linear and non-linear modeling, multivariate methods, data mining, programming and simulation, and structural equation modeling and partial least squares (PLS) path modeling. Dr. Hubona is recognized as an expert of the analytical, open-source R software suite and of various path modeling software packages, including SmartPLS. He has published dozens of research articles that explain and use these techniques for the analysis of data, and, with software co-development partner Dean Lim, has created a popular cloud-based PLS software application, PLS-GUI.

(Learn more about this instructor on the official course page.)

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Final details for this Udemy course

Languages: English

Skill level: All Levels

Lectures: 107 lessons

Duration: 11.5 Hours of video

What you get: Use R software to program probabilistic simulations, often called Monte Carlo simulations.

Target audience: You do NOT need to be experienced with R software and you do NOT need to be an experienced programmer.

Requirements: Students will need to install the popular no-cost R Console and RStudio software (instructions provided).

Access: Lifetime access

Peace of mind: 30 day money back guarantee

Availability: available online, as well as on iOS and Android

Download options: check course to see if you can download lessons

95% off Linear Mixed-Effects Models with R (Coupon & Review)

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Attention: This post may contain affiliate links, meaning when you click the links and make a purchase, we receive a commission at no extra cost to you. Thanks!

Linear Mixed-Effects Models with R - Udemy Coupon

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This is the best Udemy Linear Mixed-Effects Models with R coupon code discount for 2025.

So if you’re interested in Geoffrey Hubona, Ph.D.’s “Linear Mixed-Effects Models with R” course, which will help you increase your Teaching & Academics skills, get your discount on this Udemy online course up above while it’s still available. (The coupon code will be instantly applied.)

Linear Mixed-Effects Models with R review for 2025

In our review of this course, we try to help you answer all of your most important questions about Linear Mixed-Effects Models with R as quickly and efficiently as possible, so that you can determine whether this online education training is worth your time and money.

Feel free to jump to whatever question you want answered the most.

Here’s what you’ll learn:

Why use LMMWR as an abbreviation of the course name?

During our Linear Mixed-Effects Models with R course review, you might sometimes see us refer to it as LMMWR for the following 2 reasons:

  1. We created the acronym by taking the first letter of every word (which was very ingenious and innovative, we know)
  2. We’re lazy and LMMWR is simpler and easier for reviewing purposes

The full course name is 34 characters long, including blanks, while LMMWR is 5 characters long.

You do the math.

Okay, we’ll do the math. We’re saving 29 characters every time we use LMMWR.

So, just a heads up that we’ll be using this abbreviation sometimes, so you’re not left scratching your head and wondering what the heck we’re talking about whenever we refer to LMMWR throughout the remainder of this review.

Is the Linear Mixed-Effects Models with R course for you?

To determine whether Geoffrey Hubona, Ph.D.’s Udemy course is a good fit for you or not, ask yourself the following questions down below.

The more you answer “yes” to each question, the more likely it is that you’ll like this course.

Can you understand what Geoffrey Hubona, Ph.D.’s course is about in 30 seconds or less?

Hopefully, you can easily grasp in 10 seconds or less what this online course is about simply by taking a look at the title that Geoffrey Hubona, Ph.D. chose for the course, “Linear Mixed-Effects Models with R”, as well as its subtitle: “Learn how to specify, fit, interpret, evaluate and compare estimated parameters with linear mixed-effects models in R.”.

This combo of title and subtitle should be enough to communicate the purpose of the training if Geoffrey Hubona, Ph.D. is a good, clear communicator (which, of course, you want in a teacher).

In our opinion, if you still don’t know what LMMWR is about after looking at these two things, then this is a red flag, and you might be better off not taking this class.

Among other things, it means Geoffrey Hubona, Ph.D. hasn’t clearly and accurately conveyed what the course is about and might not be the best teacher for you.

For similar reasons, it’s important that you’re able to clearly understand what Linear Mixed-Effects Models with R is all about from the first few lines of the course description.

So take just a few seconds to read the opening lines down below and see what you think of them. 

Opening lines of Geoffrey Hubona, Ph.D.’s official description of LMMWR

Linear Mixed-Effects Models with R is a 7-session course that teaches the requisite knowledge and skills necessary to fit, interpret and evaluate the estimated parameters of linear mixed-effects models using R software. Alternatively referred to as nested, hierarchical, longitudinal, repeated measures, or temporal and spatial pseudo-replications, linear mixed-effects models are a form of least-squares model-fitting procedures. They are typically characterized by two (or more) sources of variance, and thus have multiple correlational structures among the predictor independent variables, which affect their estimated effects, or relationships, with the predicted dependent variables. These multiple sources of variance and correlational structures must be taken into account in estimating the “fit” and parameters for linear mixed-effects models.

The structure of mixed-effects models may be additive, or non-linear, or exponential or binomial, or assume various other ‘families’ of modeling relationships with the predicted variables. However, in this “hands-on” course, coverage is restricted to linear mixed-effects models, and especially, how to: (1) choose an appropriate linear model; (2) represent that model in R; (3) estimate the model; (4) compare (if needed), interpret and report the results; and (5) validate the model and the model assumptions. Additionally, the course explains the fitting of different correlational structures to both temporal, and spatial, pseudo-replicated models to appropriately adjust for the lack of independence among the error terms. The course does address the relevant statistical concepts, but mainly focuses on implementing mixed-effects models in R with ample R scripts, ‘real’ data sets, and live demonstrations. No prior experience with R is necessary to successfully complete the course as the first entire course section consists of a “hands-on” primer for executing statistical commands and scripts using R.

…

(Read more about this course on the official course page.)

Does LMMWR pass the 30 Seconds Test?

You can read a lot more about Linear Mixed-Effects Models with R on the official course page on Udemy, but the point is this: are the title, subtitle, and just the first few lines of the description enough to help you understand what the course is about?

If so, Geoffrey Hubona, Ph.D. has done a good job and can be considered more trustworthy and a good communicator, which are important qualities for any teacher.

And, if not, maybe you’re better off looking at other Teaching & Academics classes that are more clearly defined and more tailored to your specific interests.

Did Linear Mixed-Effects Models with R appeal to you in 30 seconds or less?

Now that you’ve done the 30 Second Test with LMMWR above, what is your gut reaction to this Teaching & Academics course with only the basic information of its title, subtitle, and the first few opening lines of its official course summary?

Did Geoffrey Hubona, Ph.D. do a good job conveying its subject matter, and did it immediately get your attention and appeal to you?

If so, Geoffrey Hubona, Ph.D.’s online course is certainly worth considering some more.

But if not, perhaps it’s in your best interest to consider some other Teaching & Academics courses instead, because clear communication and being able to hook and maintain your interest are two very important qualities for your online learning success.

Does Geoffrey Hubona, Ph.D. sound like a course instructor you’d like to learn from?

You’ve already learned how to use The 30 Second Test to make a quick evaluation of whether the LMMWR course is worth taking.

We have a similar 15 Second Bio Test where you read only the first few lines of an instructor’s background — in this case, Geoffrey Hubona, Ph.D.’s background — and then you make a quick, snap judgment as to whether you think the instructor would be ideal for you.

There is no right or wrong answer. It’s just about going with your gut instinct. What might appeal to one potential student might alienate another, and vice versa.

(FYI, all Udemy instructors, including Geoffrey Hubona, Ph.D., have a Udemy profile on their course page, so you can easily check for a bio and background on the Udemy website that way. We’re only including the first few lines of the bio down below for The 15 Second Bio Test).

Opening lines from Geoffrey Hubona, Ph.D.’s Udemy bio

Dr. Geoffrey Hubona held full-time tenure-track, and tenured, assistant and associate professor faculty positions at 3 major state universities in the Eastern United States from 1993-2010. In these positions, he taught dozens of various statistics, business information systems, and computer science courses to undergraduate, master’s and Ph.D. students. He earned a Ph.D. in Business Administration (Information Systems and Computer Science) from the University of South Florida (USF) in Tampa, FL (1993); an MA in Economics (1990), also from USF; an MBA in Finance (1979) from George Mason University in Fairfax, VA; and a BA in Psychology (1972) from the University of Virginia in Charlottesville, VA. He was a full-time assistant professor at the University of Maryland Baltimore County (1993-1996) in Catonsville, MD; a tenured associate professor in the department of Information Systems in the Business College at Virginia Commonwealth University (1996-2001) in Richmond, VA; and an associate professor in the CIS department of the Robinson College of Business at Georgia State University (2001-2010). He is the founder of the Georgia R School (2010-2014) and of R-Courseware (2014-Present), online educational organizations that teach research methods and quantitative analysis techniques. These research methods techniques include linear and non-linear modeling, multivariate methods, data mining, programming and simulation, and structural equation modeling and partial least squares (PLS) path modeling. Dr. Hubona is an expert of the analytical, open-source R software suite and of various PLS path modeling software packages, including SmartPLS. He has published dozens of research articles that explain and use these techniques for the analysis of data, and, with software co-development partner Dean Lim, has created a popular cloud-based PLS software application, PLS-GUI.

(Learn more about this instructor on the official course page.)

What did you think about Geoffrey Hubona, Ph.D. after reading just the first few lines of the bio above?

After reading just the first few lines about Geoffrey Hubona, Ph.D., did it make you more or less interested in taking the LMMWR course?

And did it make you feel like Geoffrey Hubona, Ph.D. was more or less credible and qualified to teach Linear Mixed-Effects Models with R?

Finally, overall, did you feel like you’d receive the proper training from the instructor of this Teaching & Academics course?

As always, we encourage you to listen to your gut instinct, which is different for every student.

Are the LMMWR lessons clear, specific, and organized well?

Part of the (good) problem with Udemy’s online courses, such as the Linear Mixed-Effects Models with R course, is that the instructors are constantly updating them, including adding and renaming lessons.

So it makes no sense whatsoever for us to list out all the modules and lessons in the LMMWR course here, because you can just as easily go to the Udemy course page and get all the up to date course structure as of right now.

We do, however, have some tips about reviewing Geoffrey Hubona, Ph.D.’s course structure, so that you can get a better sense of whether this program is worth your time or not.

In a nutshell, you want to scan the the titles of the different sections and lessons of the course, and verify that they are clearly relevant to the course’s name, Linear Mixed-Effects Models with R, as well as the course’s subtitle, Learn how to specify, fit, interpret, evaluate and compare estimated parameters with linear mixed-effects models in R..

If the section names and lessons are clear, specific, and relevant, then it’s a good sign that LMMWR is potentially a good, useful course for you, and you can have more confidence in Geoffrey Hubona, Ph.D.’s teaching abilities and lesson planning.

On the other hand, if the module names are confusing, vague, or irrelevant, then this is a red flag, which might indicate that the program is worth skipping.

Have you taken some free lessons from Geoffrey Hubona, Ph.D. that you enjoyed?

Have you already learned something from Geoffrey Hubona, Ph.D. that you valued or enjoyed?

For example, does the Linear Mixed-Effects Models with R training have some free lessons that you can try? (Almost all Udemy instructors will give you at least one or two lessons for free to help you make a better, more informed decision before enrolling in their course.)

But if you weren’t able to get any LMMWR lessons for free, have you perhaps watched a YouTube video by Geoffrey Hubona, Ph.D., or perhaps come across this instructor’s thoughts on Quora, Facebook, LinkedIn, Github, Reddit, or some other platform?

Or have you perhaps even taken one of Geoffrey Hubona, Ph.D.’s free courses or free webinars? (Many online teachers offer these freebies, which is a great way to get to know them and evaluate their teaching methods before buying one of their courses.)

In any case, the more familiar you are with Geoffrey Hubona, Ph.D.’s teaching methods, and the more you enjoy them, the more likely it is that Linear Mixed-Effects Models with R will be a good fit for you.

(P.S.: We strongly encourage you to seek out some free instruction from Geoffrey Hubona, Ph.D. before purchasing this course, since it’s one of the best ways to determine whether LMMWR will be helpful for you.)

Are “Linear Mixed-Effects Models with R” reviews generally positive?

On the bottom of the LMMWR page, you can read student reviews of the class.

Prior to September 09, 2025, there were 490 students enrolled, 176 reviews / ratings, and it was overall rated 3.5 out of 5.

Obviously, the more highly other students rate LMMWR the better, but no matter what, keep an open mind when reading the reviews, since you might still like a course a great deal that other students dislike.

After all, everyone’s got their own opinion.

We recommend that you spend only a couple minutes scanning the LMMWR reviews to get an overall sense of them. You don’t have to read each one!

Is Geoffrey Hubona, Ph.D. responsive to student questions in the LMMWR training?

You can see what other students have to say about this in their LMMWR reviews.

But, our simple all time favorite way of gauging an instructor’s responsiveness is to simply email the instructor and see if or how they respond.

In this case, Udemy has a messaging system for students / anyone who has an account, and you can send Geoffrey Hubona, Ph.D. a message through this system quite easily, even if you haven’t bought LMMWR yet.

For example, you could say, “Hi, and I came across LMMWR while looking at Teaching & Academics courses on Udemy. If I enroll in your training, would you mind if I asked you any questions along the way?”

If you use this approach, the response (or lack of response) from the professor will tell you everything.

Obviously, the quicker the response the better!

Are you comfortable going through the lessons in Linear Mixed-Effects Models with R on your own, online?

This is a big one, because Linear Mixed-Effects Models with R is an online course as opposed to a course that you physically take in a classroom.

Of course, you will need a good internet connection to have access to the course material and lessons, but beyond that, you also have to be comfortable being self motivated to some degree, being on your own, and not having any physical interaction with any of the other students taking Linear Mixed-Effects Models with R.

Yes, you will be able to interact with the students and the teacher, Geoffrey Hubona, Ph.D., online, but it’s a different kind of experience than what you’d get if you were interacting with them in person.

This is not a big deal to most people, but it might be something for you to consider if you feel like you do better taking classes in person rather than learning online.

Do the pros / benefits of LMMWR make it worth your time?

Ideally, if you’ve gone through the evaluation steps above, you have a list of positive things about the Linear Mixed-Effects Models with R training that looks something like this:

  • The purpose of LMMWR can be clearly grasped and understood, and its lesson structure is clear, specific, and well organized
  • Geoffrey Hubona, Ph.D. is well qualified to teach this subject matter, has good teaching abilities, and is responsive to student questions
  • Other LMMWR students have great things to say about the program

Other benefits include:

  • You get to go through LMMWR at your own pace
  • You join a community of 490 other students taking the course
  • You get lifetime access to the training
  • All updates to the training are free
  • You have a 30 day money back guarantee

Even if there are some things that you don’t like about the program, so what?

The question is simply this: do you think that LMMWR would be worth your time, even if there are some things that could be better about it?

Can you comfortably afford LMMWR?

Can you comfortably afford the cost of Linear Mixed-Effects Models with R?

This is an important question to answer, because even if you think LMMWR sounds like the greatest online class in the world, it’s still not worth taking if you can’t comfortably afford it!

Before September 09, 2025, the price was $12.99 before any Udemy discount, and you were able to pay with a credit card.

Keep in mind that this is a Udemy online course, and there’s a great chance that you can get a solid discount on LMMWR with Udemy coupons / promo codes, especially with the strategies we provide for helping you find the best, most popular coupons available.

We’ll cover that in greater detail in the next section, because at the end of the day, its important that you can learn whatever you want to learn without getting into a lot of credit card debt.

How can you maximize your discount on Linear Mixed-Effects Models with R?

By far, the easiest way to get the best and biggest discount on this course is to use the Linear Mixed-Effects Models with R discount code link at the top of this page.

It will instantly give you the best coupon code we could find for Geoffrey Hubona, Ph.D.’s online training.

We don’t believe there’s a bigger discount than the one we provided, but if for some reason you’d like to try find one, you can use the methods below to hunt for the best LMMWR course coupons and promo codes you can find.

FYI, the methods below will help you not just with getting LMMWR for a better price, but also with any other Geoffrey Hubona, Ph.D. Udemy course that you’d like to get for cheaper.

How can Google help you get a LMMWR discount?

To use this method, do a Google search for the LMMWR training, but in your search query, be sure to add words like coupon code, promo code, deal, sale, discount, and Udemy.

For example, you might do a search for “Udemy Linear Mixed-Effects Models with R promo code” or “Linear Mixed-Effects Models with R udemy coupon codes” and see what turns up.

Similarly, you can use the same combination of search terms with Geoffrey Hubona, Ph.D.’s name and see what happens.

For example, you might do a Google search for “Geoffrey Hubona, Ph.D. Udemy coupons” or “Geoffrey Hubona, Ph.D. course coupon codes” and see if that helps you.

However, in general, it’s far more powerful to do a search for deals and coupon codes with the actual training’s name, than with the instructor’s name.

So in this case, for example, prioritize searches for “Linear Mixed-Effects Models with R coupons” rather than “Geoffrey Hubona, Ph.D. coupons”.

How can a Udemy sale get you LMMWR for cheaper?

Every once in while, Udemy will do a sitewide sale where they offer all (or almost all) their courses at a discounted price. For example, one of the best sales is where every course is only $10 or $9.99.

So, if you’re interested in saving as much money as possible, you could wait and see if you can get LMMWR for this cheaper Udemy sale price one day.

The problem is that these sales only occur sporadically, so you might be waiting for a while. Also, if Geoffrey Hubona, Ph.D. decides not to participate in the site wide sale, then you won’t get a discount on LMMWR, even though you could get a great discount on almost any other class at Udemy!

To understand this, think of there as being two different coupon categories for the LMMWR course. Category one is an official Udemy coupon (which instructors can opt out of), while category two is a coupon offered directly by the instructor.

At the end of the day, it doesn’t matter what kind of a coupon tag you’re dealing with (for example, “officially from Udemy” or “officially from the instructor”), as long as long as as you’re dealing with active coupons that get you a better price.

How can you get a LMMWR discount from Geoffrey Hubona, Ph.D.?

If you’re really serious about getting “Linear Mixed-Effects Models with R” for the cheapest price possible, then perhaps one of the most powerful things you can do is get a coupon code straight from Geoffrey Hubona, Ph.D., instead of waiting for a Udemy sale.

To do this, you can use either the direct approach or an indirect approach to try to get your discount.

With the direct approach, the big idea is to simply get Geoffrey Hubona, Ph.D.’s contact info in some way or another (whether it’s email, or Twitter, or whatever else).

Then you send a message saying something like “I’m interested in enrolling in Linear Mixed-Effects Models with R. Do you happen to currently have an active coupon code for it that I could use?” (And then, hopefully, you’ll get a reply with your discount code.)

On the other hand, with the indirect approach, you join Geoffrey Hubona, Ph.D.’s mailing list, if you can find it, and then you hope that at some time LMMWR will be promoted to you at a discount.

By far, the more powerful approach is the direct approach, because it tends to get results faster. But you can experiment with the indirect approach and see if it works for you.

Can you get LMMWR for free?

Of course, the best possible price for the LMMWR training is free! As in, you pay no money whatsoever.

And guess what? Sometimes Udemy instructors provide coupon codes that enable students to take their courses for free. So, perhaps it’s possible that Geoffrey Hubona, Ph.D. has done this.

Basically, if you’re trying to get this program for free, you will want to search for the course’s name along with other words like free coupon, or 100 off coupon.

For example, you might do a google search for “Linear Mixed-Effects Models with R free coupon” or “Linear Mixed-Effects Models with R 100 off coupon” and see what happens.

But keep this in mind: often, Udemy teachers will offer a free coupon for their course when it first opens to get some publicity and reviews. And then, after a few days, they’ll make the coupon expired.

So even Geoffrey Hubona, Ph.D. has offered free coupons for LMMWR in the past, the odds are likely they will all be currently expired. This is a common pattern that we have found.

What about a LMMWR free download?

It’s important to understand that there’s a difference between getting full access to the LMMWR training for free legally with a free coupon code vs. finding a way to download LMMWR illegally.

If you really want to go the download route, you can do a google search for something like “Linear Mixed-Effects Models with R download”.

And if that doesn’t get you the results you want, you can add the word “free” to your search.

For example, perhaps you could do a google search for “Linear Mixed-Effects Models with R free download”.

However, even if you get some results from these searches, we do not recommend that you take this course of action.

First of all, there are some shady sites out there that could be trying to infect your computer.

Second, Geoffrey Hubona, Ph.D. created this course and deserves monetary compensation for it.

And third, if you go the free download route, you’ll be missing out on a lot of value, because you won’t be able to ask the instructor questions or interact with the other 490 students enrolled in the program.

Can you get a refund on Linear Mixed-Effects Models with R if you don’t like it?

Let’s say that you used our tips above, and you were able to buy the LMMWR training at a fantastic discounted price. So at this point, you’re super excited.

Then, you actually dive into Geoffrey Hubona, Ph.D.’s course, and you discover that it just isn’t for you for whatever reason.

And now you’re super bummed, because you feel like it wasn’t money well spent.

Well, guess what?

Udemy offers a rock solid 30 day money back guarantee on all their courses, so you can get a refund on LMMWR no matter what. And this means there is absolutely no risk.

Indeed, even if you left a super negative, critical review on the LMMWR training, and then asked for your money back, you’d get a refund. For better or worse, there’s nothing Geoffrey Hubona, Ph.D. could do about it, since it is simply Udemy policy.

To sum it up: yes, you can get a full refund, so at the end of the day, don’t worry about the possibility of purchasing LMMWR and not liking it, since you can always get your money back.

What is OCP’s overall rating of Linear Mixed-Effects Models with R?

During this LMMWR review, you’ve learned about some of the unusual ways we like to evaluate courses, such as with The 30 Second Test and The 15 Second Bio Test.

So our overall review process is perhaps a little unusual and different from other reviews out there. Keep this in mind when you consider the overall rating / score that we have given this course.

Anyway, after taking a look at the LMMWR training, the instructor, Geoffrey Hubona, Ph.D., and reading what other students have said about this program, we give it an overall rating of 4 out of 5.

Ultimately, though, what matters most is what you would rate it based on the same criteria.

What are some potential alternatives to Linear Mixed-Effects Models with R?

If you like this course, you might also be interested in:

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TLDR: Just the quick facts about LMMWR

Okay, if all of this was Too Long Didn’t Read for you, here is the Cliff’s Notes version of what LMMWR’s online training is all about:

LMMWR coupon & course info

Course Name: Linear Mixed-Effects Models with R

Subtitle: Learn how to specify, fit, interpret, evaluate and compare estimated parameters with linear mixed-effects models in R.

Instructor: Taught by Geoffrey Hubona, Ph.D.

Category: Teaching & Academics

Subcategory: Math & Science

Provided by: Udemy

Price: $12.99 (before discount)

Free coupon code: Get Udemy coupon code discount at top of page (no charge for coupon, especially since we are compensated for referrals via affiliate marketing)

LMMWR review info & popularity

Prior to September 09, 2025…

Students: 490 students enrolled

Ratings: 176 reviews

Rank: ranked #85 in Udemy Academics Courses in Udemy Teaching & Academics Courses

Rankings tip: rankings change all the time, so even if Linear Mixed-Effects Models with R is a bestseller or one of the top Udemy courses one year, it doesn’t mean it will be a top Udemy course the next year

LMMWR final details

Languages: English

Skill level: All Levels

Lectures: 77 lectures lectures lessons

Duration: 10.5 total hours hours of video

What you get: Specify an appropriate linear mixed-effects model structure with their own data.

Target audience: Students do NOT need to be knowledgeable and/or experienced with R software to successfully complete this course.

Requirements: Students will need to install the no-cost R console and the no-cost RStudio application (instructions and provided).

Access: Lifetime access

Peace of mind: 30 day money back guarantee

Availability: available online, as well as on iOS and Android

Download options: check course to see if you can download lessons

95% off The Comprehensive Statistics and Data Science with R Course (Coupon)

Online Courses Pro
Attention: This post may contain affiliate links, meaning when you click the links and make a purchase, we receive a commission at no extra cost to you. Thanks!

The Comprehensive Statistics and Data Science with R Course - Udemy Coupon

Get Discount

Bonus: download a free guide that reveals 11 tricks for getting the biggest discounts on Udemy courses, including this course.

Coupon & course info

Course Name: The Comprehensive Statistics and Data Science with R Course

Subtitle: Learn how to use R for data science tasks, all about R data structures, functions and visualizations, and statistics.

Instructor: Taught by Geoffrey Hubona, Ph.D., Professor of Information Systems

Category: Business

Subcategory: Data & Analytics

Provided by: Udemy

Price: $50 (before discount)

Free coupon code: See above (no charge for coupon)

Review info & popularity

As of September 8, 2016…

Students: 518 students enrolled

Ratings: 19 reviews

Rank: ranked #157d in Udemy Business Courses

Brief course description

This course, The Comprehensive Statistics and Data Science with R Course, is mostly based on the authoritative documentation in the online “An Introduction to R” manual produced with each new R release by the Comprehensive R Archive Network (CRAN) development core team. These are the people who actually write, test, produce and release the R code to the general public by way of the CRAN mirrors. It is a rich and detailed 10-session course which covers much of the content in the contemporary 105-page CRAN manual. The ten sessions follow the outline in the An Introduction to R online manual and specifically instruct with respect to the following user topics:

1. Introduction to R; Inputting data into R

2. Simple manipulation of numbers and vectors

(Read more about this course on the official course page.)

Geoffrey Hubona, Ph.D. bio

Dr. Geoffrey Hubona held full-time tenure-track, and tenured, assistant and associate professor faculty positions at 3 major state universities in the Eastern United States from 1993-2010. In these positions, he taught dozens of various statistics, business information systems, and computer science courses to undergraduate, master’s and Ph.D. students. He earned a Ph.D. in Business Administration (Information Systems and Computer Science) from the University of South Florida (USF) in Tampa, FL (1993); an MA in Economics (1990), also from USF; an MBA in Finance (1979) from George Mason University in Fairfax, VA; and a BA in Psychology (1972) from the University of Virginia in Charlottesville, VA. He was a full-time assistant professor at the University of Maryland Baltimore County (1993-1996) in Catonsville, MD; a tenured associate professor in the department of Information Systems in the Business College at Virginia Commonwealth University (1996-2001) in Richmond, VA; and an associate professor in the CIS department of the Robinson College of Business at Georgia State University (2001-2010). He is the founder of the Georgia R School (2010-2014) and of R-Courseware (2014-Present), online educational organizations that teach research methods and quantitative analysis techniques. These research methods techniques include linear and non-linear modeling, multivariate methods, data mining, programming and simulation, and structural equation modeling and partial least squares (PLS) path modeling. Dr. Hubona is an expert of the analytical, open-source R software suite and of various PLS path modeling software packages, including SmartPLS. He has published dozens of research articles that explain and use these techniques for the analysis of data, and, with software co-development partner Dean Lim, has created a popular cloud-based PLS software application, PLS-GUI.

(Learn more about this instructor on the official course page.)

Recommended courses

If you like this course, you might also be interested in:

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Final details for this Udemy course

Languages: English

Skill level: All Levels

Lectures: 219 lessons

Duration: 19.5 hours of video

What you get: Students will understand what R is, and how to input and output data files into their R sessions.

Target audience: This course will benefit anyone wishing to learn R and especially those who seek an in-depth “hands-on” tutorial on performing statistical analyses with R.

Requirements: Students must install R and RStudio (free software) but ample instructions are provided.

Access: Lifetime access

Peace of mind: 30 day money back guarantee

Availability: available online, as well as on iOS and Android

Download options: check course to see if you can download lessons

95% off PLS Path Modeling with the semPLS and PLSPM Packages in R (Coupon)

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Attention: This post may contain affiliate links, meaning when you click the links and make a purchase, we receive a commission at no extra cost to you. Thanks!

PLS Path Modeling with the semPLS and PLSPM Packages in R - Udemy Coupon

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Bonus: download a free guide that reveals 11 tricks for getting the biggest discounts on Udemy courses, including this course.

Coupon & course info

Course Name: PLS Path Modeling with the semPLS and PLSPM Packages in R

Subtitle: How to make use of the unique semPLS and PLSPM packages features and capabilities to estimate path models.

Instructor: Taught by Geoffrey Hubona, Ph.D., Professor of Information Systems

Category: Academics

Subcategory: Math & Science

Provided by: Udemy

Price: $40 (before discount)

Free coupon code: See above (no charge for coupon)

Review info & popularity

As of September 8, 2016…

Students: 255 students enrolled

Ratings: 6 reviews

Rank: ranked #22d in Udemy Academics Courses

Brief course description

The course PLS Path Modeling with the semPLS and PLSPM packages in R demonstrates the major capabilities and functions of the R semPLS package; and the major capabilities and functions of the R PLSPM package. Although the semPLS and plspm R packages use the same PLS algorithm as does SmartPLS, and consequently produce identical PLS model estimates (in almost all cases with a few exceptions), each of the two R packages also contains additional, useful, complementary functions and capabilities. Specifically, semPLS has some interesting plots and graphs of PLS path model estimates and also converts your model to run in covariance-based R functions (which is quite handy!). On the other hand, the PLSPM package has very complete and well-formatted PLS output that is consistent with the tables and reports required for publication, and also has very useful and unique multigroup-moderation analysis capabilities, and a unique REBUS-PLS function for discovering heterogeneity (more multi-group differences). If you are interested in knowing a lot about PLS path modeling, it is certainly a good use of your time to become familiar with both the semPLS and PLSPM packages in R.

…

…

(Read more about this course on the official course page.)

Geoffrey Hubona, Ph.D. bio

Dr. Geoffrey Hubona held full-time tenure-track, and tenured, assistant and associate professor faculty positions at 3 major state universities in the Eastern United States from 1993-2010. In these positions, he taught dozens of various statistics, business information systems, and computer science courses to undergraduate, master’s and Ph.D. students. He earned a Ph.D. in Business Administration (Information Systems and Computer Science) from the University of South Florida (USF) in Tampa, FL (1993); an MA in Economics (1990), also from USF; an MBA in Finance (1979) from George Mason University in Fairfax, VA; and a BA in Psychology (1972) from the University of Virginia in Charlottesville, VA. He was a full-time assistant professor at the University of Maryland Baltimore County (1993-1996) in Catonsville, MD; a tenured associate professor in the department of Information Systems in the Business College at Virginia Commonwealth University (1996-2001) in Richmond, VA; and an associate professor in the CIS department of the Robinson College of Business at Georgia State University (2001-2010). He is the founder of the Georgia R School (2010-2014) and of R-Courseware (2014-Present), online educational organizations that teach research methods and quantitative analysis techniques. These research methods techniques include linear and non-linear modeling, multivariate methods, data mining, programming and simulation, and structural equation modeling and partial least squares (PLS) path modeling. Dr. Hubona is an expert of the analytical, open-source R software suite and of various PLS path modeling software packages, including SmartPLS. He has published dozens of research articles that explain and use these techniques for the analysis of data, and, with software co-development partner Dean Lim, has created a popular cloud-based PLS software application, PLS-GUI.

(Learn more about this instructor on the official course page.)

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Final details for this Udemy course

Languages: English

Skill level: All Levels

Lectures: 97 lessons

Duration: 9 hours of video

What you get: …

Target audience: …

Requirements: …

Access: Lifetime access

Peace of mind: 30 day money back guarantee

Availability: available online, as well as on iOS and Android

Download options: check course to see if you can download lessons

95% off Structural equation modeling (SEM) with lavaan (Coupon & Review)

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Attention: This post may contain affiliate links, meaning when you click the links and make a purchase, we receive a commission at no extra cost to you. Thanks!

Structural equation modeling (SEM) with lavaan - Udemy Coupon

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This is the best Udemy Structural equation modeling (SEM) with lavaan coupon code discount for 2025.

So if you’re interested in Geoffrey Hubona, Ph.D.’s “Structural equation modeling (SEM) with lavaan” course, which will help you increase your Teaching & Academics skills, get your discount on this Udemy online course up above while it’s still available. (The coupon code will be instantly applied.)

Structural equation modeling (SEM) with lavaan review for 2025

In our review of this course, we try to help you answer all of your most important questions about Structural equation modeling (SEM) with lavaan as quickly and efficiently as possible, so that you can determine whether this online education training is worth your time and money.

Feel free to jump to whatever question you want answered the most.

Here’s what you’ll learn:

Why use SEM(WL as an abbreviation of the course name?

During our Structural equation modeling (SEM) with lavaan course review, you might sometimes see us refer to it as SEM(WL for the following 2 reasons:

  1. We created the acronym by taking the first letter of every word (which was very ingenious and innovative, we know)
  2. We’re lazy and SEM(WL is simpler and easier for reviewing purposes

The full course name is 46 characters long, including blanks, while SEM(WL is 6 characters long.

You do the math.

Okay, we’ll do the math. We’re saving 40 characters every time we use SEM(WL.

So, just a heads up that we’ll be using this abbreviation sometimes, so you’re not left scratching your head and wondering what the heck we’re talking about whenever we refer to SEM(WL throughout the remainder of this review.

Is the Structural equation modeling (SEM) with lavaan course for you?

To determine whether Geoffrey Hubona, Ph.D.’s Udemy course is a good fit for you or not, ask yourself the following questions down below.

The more you answer “yes” to each question, the more likely it is that you’ll like this course.

Can you understand what Geoffrey Hubona, Ph.D.’s course is about in 30 seconds or less?

Hopefully, you can easily grasp in 10 seconds or less what this online course is about simply by taking a look at the title that Geoffrey Hubona, Ph.D. chose for the course, “Structural equation modeling (SEM) with lavaan”, as well as its subtitle: “Learn how to specify, estimate and interpret SEM models with no-cost professional R software used by experts worldwide.”.

This combo of title and subtitle should be enough to communicate the purpose of the training if Geoffrey Hubona, Ph.D. is a good, clear communicator (which, of course, you want in a teacher).

In our opinion, if you still don’t know what SEM(WL is about after looking at these two things, then this is a red flag, and you might be better off not taking this class.

Among other things, it means Geoffrey Hubona, Ph.D. hasn’t clearly and accurately conveyed what the course is about and might not be the best teacher for you.

For similar reasons, it’s important that you’re able to clearly understand what Structural equation modeling (SEM) with lavaan is all about from the first few lines of the course description.

So take just a few seconds to read the opening lines down below and see what you think of them. 

Opening lines of Geoffrey Hubona, Ph.D.’s official description of SEM(WL

This “hands-on” course teaches one how to use the R software lavaan package to specify, estimate the parameters of, and interpret covariance-based structural equation (SEM) models that use latent variables. “lavaan” (note the purposeful use of lowercase “L” in ‘lavaan’) is an acronym for latent variable analysis, and the name suggests the long-term goal of the developer, Yves Rosseel: “to provide a collection of tools that can be used to explore, estimate, and understand a wide family of latent variable models, including factor analysis, structural equation, longitudinal, multilevel, latent class, item response, and missing data models.” The course uses and executes many “live” examples (with included R scripts and datasets) using no-cost R and RStudio software to demonstrate and teach how to: (1) specify a SEM model in lavaan syntax; (2) fit and then evaluate your model; (3) perform a CFA; (4) impute and replace missing data; (5) estimate mediating and other indirect effects; (6) estimate and evaluate multigroup models, simultaneously establishing measurement invariance; and (7) specifying and estimating latent (growth) curve models, including the use of random (and latent) intercepts and slopes. The R lavaan package is world-class ‘professional-grade’ SEM software, used by thousands of SEM experts, graduate students, and college and university faculty around the world.

…

…

(Read more about this course on the official course page.)

Does SEM(WL pass the 30 Seconds Test?

You can read a lot more about Structural equation modeling (SEM) with lavaan on the official course page on Udemy, but the point is this: are the title, subtitle, and just the first few lines of the description enough to help you understand what the course is about?

If so, Geoffrey Hubona, Ph.D. has done a good job and can be considered more trustworthy and a good communicator, which are important qualities for any teacher.

And, if not, maybe you’re better off looking at other Teaching & Academics classes that are more clearly defined and more tailored to your specific interests.

Did Structural equation modeling (SEM) with lavaan appeal to you in 30 seconds or less?

Now that you’ve done the 30 Second Test with SEM(WL above, what is your gut reaction to this Teaching & Academics course with only the basic information of its title, subtitle, and the first few opening lines of its official course summary?

Did Geoffrey Hubona, Ph.D. do a good job conveying its subject matter, and did it immediately get your attention and appeal to you?

If so, Geoffrey Hubona, Ph.D.’s online course is certainly worth considering some more.

But if not, perhaps it’s in your best interest to consider some other Teaching & Academics courses instead, because clear communication and being able to hook and maintain your interest are two very important qualities for your online learning success.

Does Geoffrey Hubona, Ph.D. sound like a course instructor you’d like to learn from?

You’ve already learned how to use The 30 Second Test to make a quick evaluation of whether the SEM(WL course is worth taking.

We have a similar 15 Second Bio Test where you read only the first few lines of an instructor’s background — in this case, Geoffrey Hubona, Ph.D.’s background — and then you make a quick, snap judgment as to whether you think the instructor would be ideal for you.

There is no right or wrong answer. It’s just about going with your gut instinct. What might appeal to one potential student might alienate another, and vice versa.

(FYI, all Udemy instructors, including Geoffrey Hubona, Ph.D., have a Udemy profile on their course page, so you can easily check for a bio and background on the Udemy website that way. We’re only including the first few lines of the bio down below for The 15 Second Bio Test).

Opening lines from Geoffrey Hubona, Ph.D.’s Udemy bio

Dr. Geoffrey Hubona held full-time tenure-track, and tenured, assistant and associate professor faculty positions at 3 major state universities in the Eastern United States from 1993-2010. In these positions, he taught dozens of various statistics, business information systems, and computer science courses to undergraduate, master’s and Ph.D. students. He earned a Ph.D. in Business Administration (Information Systems and Computer Science) from the University of South Florida (USF) in Tampa, FL (1993); an MA in Economics (1990), also from USF; an MBA in Finance (1979) from George Mason University in Fairfax, VA; and a BA in Psychology (1972) from the University of Virginia in Charlottesville, VA. He was a full-time assistant professor at the University of Maryland Baltimore County (1993-1996) in Catonsville, MD; a tenured associate professor in the department of Information Systems in the Business College at Virginia Commonwealth University (1996-2001) in Richmond, VA; and an associate professor in the CIS department of the Robinson College of Business at Georgia State University (2001-2010). He is the founder of the Georgia R School (2010-2014) and of R-Courseware (2014-Present), online educational organizations that teach research methods and quantitative analysis techniques. These research methods techniques include linear and non-linear modeling, multivariate methods, data mining, programming and simulation, and structural equation modeling and partial least squares (PLS) path modeling. Dr. Hubona is an expert of the analytical, open-source R software suite and of various PLS path modeling software packages, including SmartPLS. He has published dozens of research articles that explain and use these techniques for the analysis of data, and, with software co-development partner Dean Lim, has created a popular cloud-based PLS software application, PLS-GUI.

(Learn more about this instructor on the official course page.)

What did you think about Geoffrey Hubona, Ph.D. after reading just the first few lines of the bio above?

After reading just the first few lines about Geoffrey Hubona, Ph.D., did it make you more or less interested in taking the SEM(WL course?

And did it make you feel like Geoffrey Hubona, Ph.D. was more or less credible and qualified to teach Structural equation modeling (SEM) with lavaan?

Finally, overall, did you feel like you’d receive the proper training from the instructor of this Teaching & Academics course?

As always, we encourage you to listen to your gut instinct, which is different for every student.

Are the SEM(WL lessons clear, specific, and organized well?

Part of the (good) problem with Udemy’s online courses, such as the Structural equation modeling (SEM) with lavaan course, is that the instructors are constantly updating them, including adding and renaming lessons.

So it makes no sense whatsoever for us to list out all the modules and lessons in the SEM(WL course here, because you can just as easily go to the Udemy course page and get all the up to date course structure as of right now.

We do, however, have some tips about reviewing Geoffrey Hubona, Ph.D.’s course structure, so that you can get a better sense of whether this program is worth your time or not.

In a nutshell, you want to scan the the titles of the different sections and lessons of the course, and verify that they are clearly relevant to the course’s name, Structural equation modeling (SEM) with lavaan, as well as the course’s subtitle, Learn how to specify, estimate and interpret SEM models with no-cost professional R software used by experts worldwide..

If the section names and lessons are clear, specific, and relevant, then it’s a good sign that SEM(WL is potentially a good, useful course for you, and you can have more confidence in Geoffrey Hubona, Ph.D.’s teaching abilities and lesson planning.

On the other hand, if the module names are confusing, vague, or irrelevant, then this is a red flag, which might indicate that the program is worth skipping.

Have you taken some free lessons from Geoffrey Hubona, Ph.D. that you enjoyed?

Have you already learned something from Geoffrey Hubona, Ph.D. that you valued or enjoyed?

For example, does the Structural equation modeling (SEM) with lavaan training have some free lessons that you can try? (Almost all Udemy instructors will give you at least one or two lessons for free to help you make a better, more informed decision before enrolling in their course.)

But if you weren’t able to get any SEM(WL lessons for free, have you perhaps watched a YouTube video by Geoffrey Hubona, Ph.D., or perhaps come across this instructor’s thoughts on Quora, Facebook, LinkedIn, Github, Reddit, or some other platform?

Or have you perhaps even taken one of Geoffrey Hubona, Ph.D.’s free courses or free webinars? (Many online teachers offer these freebies, which is a great way to get to know them and evaluate their teaching methods before buying one of their courses.)

In any case, the more familiar you are with Geoffrey Hubona, Ph.D.’s teaching methods, and the more you enjoy them, the more likely it is that Structural equation modeling (SEM) with lavaan will be a good fit for you.

(P.S.: We strongly encourage you to seek out some free instruction from Geoffrey Hubona, Ph.D. before purchasing this course, since it’s one of the best ways to determine whether SEM(WL will be helpful for you.)

Are “Structural equation modeling (SEM) with lavaan” reviews generally positive?

On the bottom of the SEM(WL page, you can read student reviews of the class.

Prior to September 09, 2025, there were 504 students enrolled, 223 reviews / ratings, and it was overall rated 3.5 out of 5.

Obviously, the more highly other students rate SEM(WL the better, but no matter what, keep an open mind when reading the reviews, since you might still like a course a great deal that other students dislike.

After all, everyone’s got their own opinion.

We recommend that you spend only a couple minutes scanning the SEM(WL reviews to get an overall sense of them. You don’t have to read each one!

Is Geoffrey Hubona, Ph.D. responsive to student questions in the SEM(WL training?

You can see what other students have to say about this in their SEM(WL reviews.

But, our simple all time favorite way of gauging an instructor’s responsiveness is to simply email the instructor and see if or how they respond.

In this case, Udemy has a messaging system for students / anyone who has an account, and you can send Geoffrey Hubona, Ph.D. a message through this system quite easily, even if you haven’t bought SEM(WL yet.

For example, you could say, “Hi, and I came across SEM(WL while looking at Teaching & Academics courses on Udemy. If I enroll in your training, would you mind if I asked you any questions along the way?”

If you use this approach, the response (or lack of response) from the professor will tell you everything.

Obviously, the quicker the response the better!

Are you comfortable going through the lessons in Structural equation modeling (SEM) with lavaan on your own, online?

This is a big one, because Structural equation modeling (SEM) with lavaan is an online course as opposed to a course that you physically take in a classroom.

Of course, you will need a good internet connection to have access to the course material and lessons, but beyond that, you also have to be comfortable being self motivated to some degree, being on your own, and not having any physical interaction with any of the other students taking Structural equation modeling (SEM) with lavaan.

Yes, you will be able to interact with the students and the teacher, Geoffrey Hubona, Ph.D., online, but it’s a different kind of experience than what you’d get if you were interacting with them in person.

This is not a big deal to most people, but it might be something for you to consider if you feel like you do better taking classes in person rather than learning online.

Do the pros / benefits of SEM(WL make it worth your time?

Ideally, if you’ve gone through the evaluation steps above, you have a list of positive things about the Structural equation modeling (SEM) with lavaan training that looks something like this:

  • The purpose of SEM(WL can be clearly grasped and understood, and its lesson structure is clear, specific, and well organized
  • Geoffrey Hubona, Ph.D. is well qualified to teach this subject matter, has good teaching abilities, and is responsive to student questions
  • Other SEM(WL students have great things to say about the program

Other benefits include:

  • You get to go through SEM(WL at your own pace
  • You join a community of 504 other students taking the course
  • You get lifetime access to the training
  • All updates to the training are free
  • You have a 30 day money back guarantee

Even if there are some things that you don’t like about the program, so what?

The question is simply this: do you think that SEM(WL would be worth your time, even if there are some things that could be better about it?

Can you comfortably afford SEM(WL?

Can you comfortably afford the cost of Structural equation modeling (SEM) with lavaan?

This is an important question to answer, because even if you think SEM(WL sounds like the greatest online class in the world, it’s still not worth taking if you can’t comfortably afford it!

Before September 09, 2025, the price was $13.99 before any Udemy discount, and you were able to pay with a credit card.

Keep in mind that this is a Udemy online course, and there’s a great chance that you can get a solid discount on SEM(WL with Udemy coupons / promo codes, especially with the strategies we provide for helping you find the best, most popular coupons available.

We’ll cover that in greater detail in the next section, because at the end of the day, its important that you can learn whatever you want to learn without getting into a lot of credit card debt.

How can you maximize your discount on Structural equation modeling (SEM) with lavaan?

By far, the easiest way to get the best and biggest discount on this course is to use the Structural equation modeling (SEM) with lavaan discount code link at the top of this page.

It will instantly give you the best coupon code we could find for Geoffrey Hubona, Ph.D.’s online training.

We don’t believe there’s a bigger discount than the one we provided, but if for some reason you’d like to try find one, you can use the methods below to hunt for the best SEM(WL course coupons and promo codes you can find.

FYI, the methods below will help you not just with getting SEM(WL for a better price, but also with any other Geoffrey Hubona, Ph.D. Udemy course that you’d like to get for cheaper.

How can Google help you get a SEM(WL discount?

To use this method, do a Google search for the SEM(WL training, but in your search query, be sure to add words like coupon code, promo code, deal, sale, discount, and Udemy.

For example, you might do a search for “Udemy Structural equation modeling (SEM) with lavaan promo code” or “Structural equation modeling (SEM) with lavaan udemy coupon codes” and see what turns up.

Similarly, you can use the same combination of search terms with Geoffrey Hubona, Ph.D.’s name and see what happens.

For example, you might do a Google search for “Geoffrey Hubona, Ph.D. Udemy coupons” or “Geoffrey Hubona, Ph.D. course coupon codes” and see if that helps you.

However, in general, it’s far more powerful to do a search for deals and coupon codes with the actual training’s name, than with the instructor’s name.

So in this case, for example, prioritize searches for “Structural equation modeling (SEM) with lavaan coupons” rather than “Geoffrey Hubona, Ph.D. coupons”.

How can a Udemy sale get you SEM(WL for cheaper?

Every once in while, Udemy will do a sitewide sale where they offer all (or almost all) their courses at a discounted price. For example, one of the best sales is where every course is only $10 or $9.99.

So, if you’re interested in saving as much money as possible, you could wait and see if you can get SEM(WL for this cheaper Udemy sale price one day.

The problem is that these sales only occur sporadically, so you might be waiting for a while. Also, if Geoffrey Hubona, Ph.D. decides not to participate in the site wide sale, then you won’t get a discount on SEM(WL, even though you could get a great discount on almost any other class at Udemy!

To understand this, think of there as being two different coupon categories for the SEM(WL course. Category one is an official Udemy coupon (which instructors can opt out of), while category two is a coupon offered directly by the instructor.

At the end of the day, it doesn’t matter what kind of a coupon tag you’re dealing with (for example, “officially from Udemy” or “officially from the instructor”), as long as long as as you’re dealing with active coupons that get you a better price.

How can you get a SEM(WL discount from Geoffrey Hubona, Ph.D.?

If you’re really serious about getting “Structural equation modeling (SEM) with lavaan” for the cheapest price possible, then perhaps one of the most powerful things you can do is get a coupon code straight from Geoffrey Hubona, Ph.D., instead of waiting for a Udemy sale.

To do this, you can use either the direct approach or an indirect approach to try to get your discount.

With the direct approach, the big idea is to simply get Geoffrey Hubona, Ph.D.’s contact info in some way or another (whether it’s email, or Twitter, or whatever else).

Then you send a message saying something like “I’m interested in enrolling in Structural equation modeling (SEM) with lavaan. Do you happen to currently have an active coupon code for it that I could use?” (And then, hopefully, you’ll get a reply with your discount code.)

On the other hand, with the indirect approach, you join Geoffrey Hubona, Ph.D.’s mailing list, if you can find it, and then you hope that at some time SEM(WL will be promoted to you at a discount.

By far, the more powerful approach is the direct approach, because it tends to get results faster. But you can experiment with the indirect approach and see if it works for you.

Can you get SEM(WL for free?

Of course, the best possible price for the SEM(WL training is free! As in, you pay no money whatsoever.

And guess what? Sometimes Udemy instructors provide coupon codes that enable students to take their courses for free. So, perhaps it’s possible that Geoffrey Hubona, Ph.D. has done this.

Basically, if you’re trying to get this program for free, you will want to search for the course’s name along with other words like free coupon, or 100 off coupon.

For example, you might do a google search for “Structural equation modeling (SEM) with lavaan free coupon” or “Structural equation modeling (SEM) with lavaan 100 off coupon” and see what happens.

But keep this in mind: often, Udemy teachers will offer a free coupon for their course when it first opens to get some publicity and reviews. And then, after a few days, they’ll make the coupon expired.

So even Geoffrey Hubona, Ph.D. has offered free coupons for SEM(WL in the past, the odds are likely they will all be currently expired. This is a common pattern that we have found.

What about a SEM(WL free download?

It’s important to understand that there’s a difference between getting full access to the SEM(WL training for free legally with a free coupon code vs. finding a way to download SEM(WL illegally.

If you really want to go the download route, you can do a google search for something like “Structural equation modeling (SEM) with lavaan download”.

And if that doesn’t get you the results you want, you can add the word “free” to your search.

For example, perhaps you could do a google search for “Structural equation modeling (SEM) with lavaan free download”.

However, even if you get some results from these searches, we do not recommend that you take this course of action.

First of all, there are some shady sites out there that could be trying to infect your computer.

Second, Geoffrey Hubona, Ph.D. created this course and deserves monetary compensation for it.

And third, if you go the free download route, you’ll be missing out on a lot of value, because you won’t be able to ask the instructor questions or interact with the other 504 students enrolled in the program.

Can you get a refund on Structural equation modeling (SEM) with lavaan if you don’t like it?

Let’s say that you used our tips above, and you were able to buy the SEM(WL training at a fantastic discounted price. So at this point, you’re super excited.

Then, you actually dive into Geoffrey Hubona, Ph.D.’s course, and you discover that it just isn’t for you for whatever reason.

And now you’re super bummed, because you feel like it wasn’t money well spent.

Well, guess what?

Udemy offers a rock solid 30 day money back guarantee on all their courses, so you can get a refund on SEM(WL no matter what. And this means there is absolutely no risk.

Indeed, even if you left a super negative, critical review on the SEM(WL training, and then asked for your money back, you’d get a refund. For better or worse, there’s nothing Geoffrey Hubona, Ph.D. could do about it, since it is simply Udemy policy.

To sum it up: yes, you can get a full refund, so at the end of the day, don’t worry about the possibility of purchasing SEM(WL and not liking it, since you can always get your money back.

What is OCP’s overall rating of Structural equation modeling (SEM) with lavaan?

During this SEM(WL review, you’ve learned about some of the unusual ways we like to evaluate courses, such as with The 30 Second Test and The 15 Second Bio Test.

So our overall review process is perhaps a little unusual and different from other reviews out there. Keep this in mind when you consider the overall rating / score that we have given this course.

Anyway, after taking a look at the SEM(WL training, the instructor, Geoffrey Hubona, Ph.D., and reading what other students have said about this program, we give it an overall rating of 3.6 out of 5.

Ultimately, though, what matters most is what you would rate it based on the same criteria.

What are some potential alternatives to Structural equation modeling (SEM) with lavaan?

If you like this course, you might also be interested in:

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TLDR: Just the quick facts about SEM(WL

Okay, if all of this was Too Long Didn’t Read for you, here is the Cliff’s Notes version of what SEM(WL’s online training is all about:

SEM(WL coupon & course info

Course Name: Structural equation modeling (SEM) with lavaan

Subtitle: Learn how to specify, estimate and interpret SEM models with no-cost professional R software used by experts worldwide.

Instructor: Taught by Geoffrey Hubona, Ph.D.

Category: Teaching & Academics

Subcategory: Math & Science

Provided by: Udemy

Price: $13.99 (before discount)

Free coupon code: Get Udemy coupon code discount at top of page (no charge for coupon, especially since we are compensated for referrals via affiliate marketing)

SEM(WL review info & popularity

Prior to September 09, 2025…

Students: 504 students enrolled

Ratings: 223 reviews

Rank: ranked #114d in Udemy Academics Courses in Udemy Teaching & Academics Courses

Rankings tip: rankings change all the time, so even if Structural equation modeling (SEM) with lavaan is a bestseller or one of the top Udemy courses one year, it doesn’t mean it will be a top Udemy course the next year

SEM(WL final details

Languages: English

Skill level: All Levels

Lectures: 73 lectures lectures lessons

Duration: 11.5 total hours hours of video

What you get: Specify and estimate parameters in a structural equation model using the R lavaan package and interpret and report on the SEM model results.

Target audience: Course participants may be “brand-new” (inexperienced) to using both R software and/or SEM model estimation, or they may be more experienced in one or both techniques.

Requirements: Students will be required to install no-cost R and RStudio software (instructions are provided).

Access: Lifetime access

Peace of mind: 30 day money back guarantee

Availability: available online, as well as on iOS and Android

Download options: check course to see if you can download lessons

95% off PLS Path Modeling with the Desktop PLS-GUI Application (Coupon)

Online Courses Pro
Attention: This post may contain affiliate links, meaning when you click the links and make a purchase, we receive a commission at no extra cost to you. Thanks!

PLS Path Modeling with the Desktop PLS-GUI Application - Udemy Coupon

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Bonus: download a free guide that reveals 11 tricks for getting the biggest discounts on Udemy courses, including this course.

Coupon & course info

Course Name: PLS Path Modeling with the Desktop PLS-GUI Application

Subtitle: How to conduct PLS path modeling using a desktop application created with R software

Instructor: Taught by Geoffrey Hubona, Ph.D., Professor of Information Systems

Category: Academics

Subcategory: Math & Science

Provided by: Udemy

Price: $30 (before discount)

Free coupon code: See above (no charge for coupon)

Review info & popularity

As of October 3, 2016…

Students: 193 students enrolled

Ratings: 2 reviews

Rank: ranked #97e in Udemy Academics Courses

Brief course description

PLS Path Modeling with the Desktop PLS-GUI Application is a course that both teaches about the practice of variance-based structural equation modeling (SEM), sometimes referred to as PLS Path Modeling, and is a course that provides a beta application, the desktop PLS-GUI, to do so. The PLS-GUI application was developed using the visual RGtk2 programming language in R software. RGtk2 is the R-based GUI language extension derived from the public GTK+ (GIMP Tool Kit) language.

The PLS-GUI desktop application was jointly developed by Dr. Geoffrey Hubona and Dean Lim, both of whom are co-instructors of this course.

Course participants are encouraged to use the included PLS-GUI desktop application with their own data and PLS model files. Please note that this was a beta version application which is no longer directly supported by our staff. So, while we are limited in our ability to provide fixes or solutions to use-related issues which may arise installing or using the application, we are happy to answer any and all questions relevant to the course content per se.

(Read more about this course on the official course page.)

Geoffrey Hubona, Ph.D. bio

Dr. Geoffrey Hubona held full-time tenure-track, and tenured, assistant and associate professor faculty positions at 3 major state universities in the Eastern United States from 1993-2010. In these positions, he taught dozens of various statistics, business information systems, and computer science courses to undergraduate, master’s and Ph.D. students. He earned a Ph.D. in Business Administration (Information Systems and Computer Science) from the University of South Florida (USF) in Tampa, FL (1993); an MA in Economics (1990), also from USF; an MBA in Finance (1979) from George Mason University in Fairfax, VA; and a BA in Psychology (1972) from the University of Virginia in Charlottesville, VA. He was a full-time assistant professor at the University of Maryland Baltimore County (1993-1996) in Catonsville, MD; a tenured associate professor in the department of Information Systems in the Business College at Virginia Commonwealth University (1996-2001) in Richmond, VA; and an associate professor in the CIS department of the Robinson College of Business at Georgia State University (2001-2010). He is the founder of the Georgia R School (2010-2014) and of R-Courseware (2014-Present), online educational organizations that teach research methods and quantitative analysis techniques. These research methods techniques include linear and non-linear modeling, multivariate methods, data mining, programming and simulation, and structural equation modeling and partial least squares (PLS) path modeling. Dr. Hubona is an expert of the analytical, open-source R software suite and of various PLS path modeling software packages, including SmartPLS. He has published dozens of research articles that explain and use these techniques for the analysis of data, and, with software co-development partner Dean Lim, has created a popular cloud-based PLS software application, PLS-GUI.; I am an avid user and statistical programmer of all things related to SEM especially the newer Partial Least Squares SEM. I believe PLS-SEM will be the future of big data as related to marketing. I am also a data analyst and CMRP marketing researcher.

(Learn more about this instructor on the official course page.)

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Final details for this Udemy course

Languages: English

Skill level: All Levels

Lectures: 63 lessons

Duration: 4.5 hours of video

What you get: This course teaches students about PLS path modeling, including multi-group analysis and prediction-oriented segmentation.

Target audience: Anyone involved with PLS path modeling will benefit from this course, whether they are a novice or more experienced PLS path modeler.

Requirements: Students will need to install R and the desktop PLS-GUI application with the provided instructions.

Access: Lifetime access

Peace of mind: 30 day money back guarantee

Availability: available online, as well as on iOS and Android

Download options: check course to see if you can download lessons

95% off Visualization and Imputation of Missing Data (Coupon)

Online Courses Pro
Attention: This post may contain affiliate links, meaning when you click the links and make a purchase, we receive a commission at no extra cost to you. Thanks!

Visualization and Imputation of Missing Data - Udemy Coupon

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Bonus: download a free guide that reveals 11 tricks for getting the biggest discounts on Udemy courses, including this course.

Coupon & course info

Course Name: Visualization and Imputation of Missing Data

Subtitle: Learn to create numerous unique visualizations to better understand patterns of missing data in your data sample.

Instructor: Taught by Geoffrey Hubona, Ph.D., Professor of Information Systems

Category: Academics

Subcategory: Social Science

Provided by: Udemy

Price: $25 (before discount)

Free coupon code: See above (no charge for coupon)

Review info & popularity

As of October 3, 2016…

Students: 562 students enrolled

Ratings: 10 reviews

Rank: ranked #138e in Udemy Academics Courses

Brief course description

There are many problems associated with analyzing data sets that contain missing data. However, there are various techniques to ‘fill in,’ or impute, missing data values with reasonable estimates based on the characteristics of the data itself and on the patterns of ‘missingness.’ Generally, techniques appropriate for imputing missing values in multivariate normal data and not as useful when applied to non-multivariate-normal data. This Visualization and Imputation of Missing Data course focuses on understanding patterns of ‘missingness’ in a data sample, especially non-multivariate-normal data sets, and teaches one to use various appropriate imputation techniques to “fill in” the missing data. Using the VIM and VIMGUI packages in R, the course also teaches how to create dozens of different and unique visualizations to better understand existing patterns of both the missing and imputed data in your samples.

The course teaches both the concepts and provides software to apply the latest non-multivariate-normal-friendly data imputation techniques, including: (1) Hot-Deck imputation: the sequential and random hot-deck algorithm; (2) the distance-based, k-nearest neighbor imputation approach; (3) individual, regression-based imputation; and (4) the iterative, model-based, stepwise regression imputation technique with both standard and robust methods (the IRMI algorithm). Furthermore, the course trains one to recognize the patterns of missingness using many vibrant and varied visualizations of the missing data patterns created by the professional VIMGUI software included in the course materials and made available to all course participants.

This course is useful to anyone who regularly analyzes large or small data sets that may contain missing data. This includes graduate students and faculty engaged in empirical research and working professionals who are engaged in quantitative research and/or data analysis. The visualizations that are taught are especially useful to understand the types of data missingness that may be present in your data and consequently, how best to deal with this missing data using imputation. The course includes the means to apply the appropriate imputation techniques, especially for non-multivariate-normal sets of data which tend to be most problematic to impute.

(Read more about this course on the official course page.)

Geoffrey Hubona, Ph.D. bio

Dr. Geoffrey Hubona held full-time tenure-track, and tenured, assistant and associate professor faculty positions at 3 major state universities in the Eastern United States from 1993-2010. In these positions, he taught dozens of various statistics, business information systems, and computer science courses to undergraduate, master’s and Ph.D. students. He earned a Ph.D. in Business Administration (Information Systems and Computer Science) from the University of South Florida (USF) in Tampa, FL (1993); an MA in Economics (1990), also from USF; an MBA in Finance (1979) from George Mason University in Fairfax, VA; and a BA in Psychology (1972) from the University of Virginia in Charlottesville, VA. He was a full-time assistant professor at the University of Maryland Baltimore County (1993-1996) in Catonsville, MD; a tenured associate professor in the department of Information Systems in the Business College at Virginia Commonwealth University (1996-2001) in Richmond, VA; and an associate professor in the CIS department of the Robinson College of Business at Georgia State University (2001-2010). He is the founder of the Georgia R School (2010-2014) and of R-Courseware (2014-Present), online educational organizations that teach research methods and quantitative analysis techniques. These research methods techniques include linear and non-linear modeling, multivariate methods, data mining, programming and simulation, and structural equation modeling and partial least squares (PLS) path modeling. Dr. Hubona is an expert of the analytical, open-source R software suite and of various PLS path modeling software packages, including SmartPLS. He has published dozens of research articles that explain and use these techniques for the analysis of data, and, with software co-development partner Dean Lim, has created a popular cloud-based PLS software application, PLS-GUI.

(Learn more about this instructor on the official course page.)

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Final details for this Udemy course

Languages: English

Skill level: All Levels

Lectures: 38 lessons

Duration: 5 hours of video

What you get: Use visualizations created by R software to identify patterns of ‘missingness’ in data sets and to impute reasonable values to replace the missing data.

Target audience: This course is useful for anyone analyzing large or small data sets that may contain missing data.

Requirements: Students will need to install R software but ample instructions for doing so are provided.

Access: Lifetime access

Peace of mind: 30 day money back guarantee

Availability: available online, as well as on iOS and Android

Download options: check course to see if you can download lessons

95% off The Comprehensive Programming in R Course (Coupon)

Online Courses Pro
Attention: This post may contain affiliate links, meaning when you click the links and make a purchase, we receive a commission at no extra cost to you. Thanks!

The Comprehensive Programming in R Course - Udemy Coupon

Get Discount

Bonus: download a free guide that reveals 11 tricks for getting the biggest discounts on Udemy courses, including this course.

Coupon & course info

Course Name: The Comprehensive Programming in R Course

Subtitle: How to design and develop efficient general-purpose R applications for diverse tasks and domains.

Instructor: Taught by Geoffrey Hubona, Professor of Information Systems

Category: Business

Subcategory: Data & Analytics

Provided by: Udemy

Price: $149 (before discount)

Free coupon code: See above (no charge for coupon)

Review info & popularity

As of March 9, 2016…

Students: 1215 students enrolled

Ratings: 110 reviews

Rank: ranked #126 in Udemy Business Courses

Brief course description

The Comprehensive Programming in R Course is actually a combination of two R programming courses that together comprise a gentle, yet thorough introduction to the practice of general-purpose application development in the R environment. The original first course (Sections 1-8) consists of approximately 12 hours of video content and provides extensive example-based instruction on details for programming R data structures. The original second course (Sections 9-14), an additional 12 hours of video content, provides a comprehensive overview on the most important conceptual topics for writing efficient programs to execute in the unique R environment. Participants in this comprehensive course may already be skilled programmers (in other languages) or they may be complete novices to R programming or to programming in general, but their common objective is to write R applications for diverse domains and purposes. No statistical knowledge is necessary. These two courses, combined into one course here on Udemy, together comprise a thorough introduction to using the R environment and language for general-purpose application development.

The Comprehensive Programming in R Course (Sections 1-8) presents an detailed, in-depth overview of the R programming environment and of the nature and programming implications of basic R objects in the form of vectors, matrices, dataframes and lists. The Comprehensive Programming in R Course (Sections 9-14) then applies this understanding of these basic R object structures to instruct with respect to programming the structures; performing mathematical modeling and simulations; the specifics of object-oriented programming in R; input and output; string manipulation; and performance enhancement for computation speed and to optimize computer memory resources.

…

(Read more about this course on the official course page.)

Geoffrey Hubona bio

Dr. Geoffrey Hubona has been a full-time faculty member at 3 major state universities in the Eastern United States for 20 years, teaching dozens of different statistics, business information systems, and computer science courses to undergraduate, master’s and PhD students. He earned a PhD in Information Systems and Computer Science (1993) from the University of South Florida in Tampa, FL (1993); an MA in Economics (1990) from USF; an MBA in Finance (1979) from George Mason University in Fairfax, VA; and a BA in Psychology (1972) from the University of Virginia in Charlottesville, VA. He held full-time faculty positions at the University of Maryland Baltimore County (1993-1996), Virginia Commonwealth University (1996-2001), and Georgia State University (2001-2010). He is the founder of the Georgia R School (2010), a non-profit online educational institution that teaches research methods and quantitative analysis techniques such as linear and non-linear modeling, multivariate methods, data mining, programming and simulation, and structural equation modeling and partial least squares (PLS) path modeling. Dr. Hubona is recognized as an expert of the analytical, open-source R software suite and of various path modeling software packages, including SmartPLS. He has published dozens of research articles that explain and use these techniques for the analysis of data, and, with software co-development partner Dean Lim, has created a popular cloud-based PLS software application, PLS-GUI.

(Learn more about this instructor on the official course page.)

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Final details for this Udemy course

Languages: English

Skill level: All Levels

Lectures: 120 lessons

Duration: 25 Hours of video

What you get: Acquire the skills needed to successfully develop general-purpose programming applications in the R environment

Target audience: Anyone interested in writing computer applications that execute in the R environment.

Requirements: Students will need to install the no-cost R console and the no-cost RStudio application (instructions are provided).

Access: Lifetime access

Peace of mind: 30 day money back guarantee

Availability: available online, as well as on iOS and Android

Download options: check course to see if you can download lessons