Comprehensive Graphics Visualizations with R
4.4 (43 ratings)
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Comprehensive Graphics Visualizations with R

Learn the important features of the base, ggplot and lattice ("trellis") graphical capabilities in R
4.4 (43 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
1,376 students enrolled
Last updated 2/2016
English
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Includes:
  • 8.5 hours on-demand video
  • 10 Supplemental Resources
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I Learn?
  • Learn how to create a wide range of elegant and stunning graphical visualizations using the base, lattice and ggplot graphics systems in R.
  • Learn to use the R Commander interface to create a variety of 2D and 3D graphics using different data sets.
  • Learn to apply all of these graphical capabilities to your own data by practicing with all of the supplied course videos R scripts and by completiing each of the five sets of exercises - one for each section of the course.
View Curriculum
Requirements
  • Students will need to install the R console software, RStudio and the R Commander R packages. They are each free and instructions are provided with the course materials.
Description

Comprehensive Graphics with R is a thorough, comprehensive overview of each of three major graphics approaches in R: base, lattice, and ggplot. The course also demonstrates the use of the R Commander interface to create a variety of 2D and 3D graphics. Most of the course is engaged in live, "hands-on" demonstrations of creating a wide range of 2D and 3D plots and graphs using extensive scripts and data sets, all provided with the course materials. Adequate documentation including slides, exercises and exercise solutions are also provided. The course demonstrates (and uses) two of the most popular ‘front-ends’ to the R Console: R Commander and RStudio. We begin by exploring the range of graphics output available using both the R Commander and RStudio GUI interfaces to the R Console. The course then follows with a more in-depth examination of the graphics capabilities for each of the three main graphics systems, base, lattice, and ggplot.

This course is a ‘must see’ for anyone who will use R and wishes to get the most out of the stunning variety of graphical charts, plots, and even animations that are available. The R software was designed from the outset to be particularly strong in visualization and graphical capabilities. However, if you are unaware of the full range of these capabilities you are missing opportunities to apply this wide variety of rich, powerful graphics to your own work and research projects. Accordingly, this course is specifically designed to comprehensively demonstrate and explain the broad range of graphical outputs that are available with R.

Who is the target audience?
  • Anyone who uses R software for any reason will benefit from this course, including beginning, intermediate and advanced R users.
  • Anyone who wants to learn R will benefit from this course.
  • The course is especially appropriate for graduate students and faculty who wish to learn a graphics software alternative to SPSS or SAS, as well as working data analytics professionals and other quantitative professionals.
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Curriculum For This Course
69 Lectures
08:31:40
+
Orientation to Course and to R Graphics ("Pre-Session")
13 Lectures 01:40:02





Plotting with R Commander (part 2)
10:18

Plotting with R Commander (part 3)
10:39

Scatterplot HH
06:52

Scatterplot Matrix HH
08:21

Plot of Means
06:07

Strip Chart
08:40

More Strip Chart
07:43

3D Plots
05:15
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DAY 1 Base Graphics Features compared to GGPlot
6 Lectures 45:46

Begin ggplot Graphics as Compared to Base
11:01


Still More Graphics Features
07:16

More on Plotting Characters
07:05

More on Plotting and Features and an Exercise
06:46
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DAY 2 Continue with Base Graphics versus Ggplot
19 Lectures 02:23:04
Exercise Solution and More on Base Graphics
09:43

More Base Features Compared to ggplot
08:17


Adding Text to Plots (part 2)
09:31

Adding Shapes to Plots Interactively (part 1)
07:22

Adding Shapes to Plots Interactively (part 2)
07:39

Adding Shapes to Plots Interactively (part 3)
08:05

Adding Nonlinear Fits to Plots (part 1)
07:52

Adding Nonlinear Fits to Plots (part 2)
06:10

Adding Nonlinear Fits to Plots (part 3)
05:50

Adding Nonlinear Fits to Plots (part 4)
05:26

Adding Nonlinear Fits to Plots (part 5)
07:21

Boxplots (part 1)
05:55

Boxplots (part 2)
07:25

Boxplots (part 3)
07:23

Boxplots (part 4)
10:21

Histograms
06:54

Time Series and Piechart
06:07

Stripchart and Pairs Plot
06:58
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DAY 3 Begin Lattice ("Trellis") Graphics
18 Lectures 02:03:58
Day 3 Introduction, Exercise Solution, and Shingles
07:02


Interaction and XYplots
06:25

Box and Whiskers Plot and Design Plot
08:14

Effects Sizes
05:34

Bubble and Sunflower Plots
07:53

Begin Trellis Graphics with Histogram
06:46

Density Plot
06:31

Begin Technical Overview of Lattice
08:03

Update Oats Plot
06:32

Continue Dotplots
06:29

More Densityplots
07:26

QQMath Plots
05:47

More Bwplots
06:40

Violin Plots
07:37

Multiway Tables, More Barcharts and Dotplots
07:10

Postdoc Barcharts
04:57

More Dotplots
08:17
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DAY 4 More Trellis Graphics and More GGplot Graphics
13 Lectures 01:38:50
Day 4 Introduction and Titanic Data (part 1)
07:36

More Titanic Data and Charts
09:02

More Elaborate XYPlots
06:31

Continue Elaborate XYPlots Earthquake Data
06:20

Continue Elaborate XYPlots Earthquake Data
07:55

Elaborate XYPlot with Shingles
07:42

Continue Elaborate XYPlots
09:54

Revisit ggplot2 (part 1)
08:02

GGplot with Smooth Plots
06:27

More GGplot Smooths
07:54

More GGplot
05:12

Different GGplots
07:22

Still More GGplot Graphs and Charts
08:53
About the Instructor
Geoffrey Hubona, Ph.D.
4.0 Average rating
1,481 Reviews
12,628 Students
28 Courses
Associate 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. Currently, he is a visiting associate professor of MIS at Texas A&M International University. 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; an MA in Economics, also from USF; an MBA in Finance from George Mason University in Fairfax, VA; and a BA in Psychology from the University of Virginia in Charlottesville, VA. 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.