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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.

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(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