Coupon & course info
Course Name: Applied Multivariate Analysis with R
Subtitle: Learn to use R software to conduct PCAs, MDSs, cluster analyses, EFAs and to estimate SEM models.
Instructor: Taught by Geoffrey Hubona, Professor of Information Systems
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: 1259 students enrolled
Ratings: 6 reviews
Rank: ranked #252 in Udemy Business Courses
Brief course description
Applied Multivariate Analysis (MVA) with R is a practical, conceptual and applied “hands-on” course that teaches students how to perform various specific MVA tasks using real data sets and R software. It is an excellent and practical background course for anyone engaged with educational or professional tasks and responsibilities in the fields of data mining or predictive analytics, statistical or quantitative modeling (including linear, GLM and/or non-linear modeling, covariance-based Structural Equation Modeling (SEM) specification and estimation, and/or variance-based PLS Path Model specification and estimation. Students learn all about the nature of multivariate data and multivariate analysis. Students specifically learn how to create and estimate: covariance and correlation matrices; Principal Components Analyses (PCA); Multidimensional Scaling (MDS); Cluster Analysis; Exploratory Factor Analyses (EFA); and SEM model estimation. The course also teaches how to create dozens of different dazzling 2D and 3D multivariate data visualizations using R software. All software, R scripts, datasets and slides used in all lectures are provided in the course materials. The course is structured as a series of seven sections, each addressing a specific MVA topic and each section culminating with one or more “hands-on” exercises for the students to complete before proceeding to reinforce learning the presented MVA concepts and skills. The course is an excellent vehicle to acquire “real-world” predictive analytics skills that are in high demand today in the workplace. The course is also a fertile source of relevant skills and knowledge for graduate students and faculty who are required to analyze and interpret research data.
(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
Skill level: All Levels
Lectures: 75 lessons
Duration: 12 Hours of video
What you get: Conceptualize and apply multivariate skills and “hands-on” techniques using R software in analyzing real data.
Target audience: Anyone interested in using multivariate analysis technques as a basis for data mining, statistical modeling, and structural equation modeling (SEM) estimation.
Requirements: No specific knowledge or skills are required.
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