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Multivariate Data Visualization with R

By: Geoffrey Hubona

  • 06:45:16
  • 36
  • 4
  • Language: English

Course Summary

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 lo

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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.
  • The course is appropriate for students, scientists, or other quantitative-analysis professionals who want to display numerical information in plots and graphs.
  • To take advantage of the course, students will need to have a basic (introductory) level or ability to use R software. However, all of the graphic R scripts are provided with the course materials.

Pre-Requisites

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

Curriculum

  • Exercise Files
  • Introduction to Course
    01:17
  • Introduction to Lattice
    16:25
  • The Trellis Object
    13:18
  • Dimension and Physical Layout
    14:01
  • Scales and Axes
    08:43
  • Visualizing Univariate Distributions (part 1)
    17:04
  • Visualizing Univariate Distributions (part 2)
    14:56
  • Two-Sample QQ Plots
    14:14
  • Strip Plots
    08:03
  • Exercise Files
  • Multiway Tables
    12:17
  • Multipanel Dot Plots
    11:10
  • Scatter Plots and Extensions
    13:37
  • Shingles and Advanced Indexing
    06:34
  • More Scatter Plots (part 1)
    16:08
  • More Scatter Plots (part 2)
    10:22
  • Scatter Plot Matrices
    13:39
  • Parallel Coordinates Plot
    07:30
  • Exercise Files
  • Trivariate Displays
    09:01
  • 3D Scatter Plots (part 1)
    09:56
  • 3D Scatter Plots (part 2)
    08:38
  • 3D Panel Functions
    17:09
  • Visualizing 3D Surfaces
    13:53
  • More 3D Visualizations
    16:50
  • Visualizing Theoretical 3D Surfaces
    13:39
  • Exercise Files
  • Graphical Parameters and Other Settings
    15:06
  • Graphical Parameters Continued
    14:15
  • Plot Coordinates and Axis Annotation
    13:19
  • Labels and Legends
    14:50
  • Data Manipulation (part 1)
    13:56
  • Data Manipulation (part 2)
    15:27
  • Shingles and Related Utilities
    14:58
  • Ordering Categorical Variables
    14:59

About the Author

Geoffrey Hubona, Professor of Information Systems

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.

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Multivariate Data Visualization with R

  • 06:45:16
  • 36
  • 4
  • Language: English
  • 15 days Money back Gurantee
  • Unlimited Access
  • Android, iPhone and iPad Access
  • Certificate of Completion

Course Summary

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 lo

Read More

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.
  • The course is appropriate for students, scientists, or other quantitative-analysis professionals who want to display numerical information in plots and graphs.
  • To take advantage of the course, students will need to have a basic (introductory) level or ability to use R software. However, all of the graphic R scripts are provided with the course materials.

Pre-Requisites

  • Anyone who uses R, or who wants to use R, for any sort of multivariate data analysis would benefit from taking this course.
  • The course is appropriate for students, scientists, or other quantitative-analysis professionals who want to display numerical information in plots and graphs.
  • To take advantage of the course, students will need to have a basic (introductory) level or ability to use R software. However, all of the graphic R scripts are provided with the course materials.

About the Author

Geoffrey Hubona, Professor of Information Systems

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.

More From Author