Description
Course info
Rating
(24)
Level
Intermediate
Updated
Jul 22, 2016
Duration
2h 11m
Description

R is a popular open-source programming language for data analysis. Its interactive programming environment and data visualization capabilities make R an ideal tool for creating a wide variety of data visualizations. In this course, Multivariate Data Visualization with R, you will learn how to answer questions about your data by creating multivariate data visualizations with R. First, you'll learn the basics about creating multivariate data visualizations with R, in order to have a strong foundation to build on. Next, you'll learn how to create and interpret data visualizations that involve various combinations of three categorical or numerical variables. Finally, you'll learn how to create and interpret data visualizations that involve an arbitrary number of variables at the same time. By the end of this course you'll have the skill required to create and interpret a variety of multivariate data visualizations using R.

About the author
About the author

Matthew is a data science consultant, author, and international public speaker. He has over 17 years of professional experience working with tech startups to Fortune 500 companies. He is a Microsoft MVP, ASPInsider, and open-source software contributor.

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Section Introduction Transcripts
Section Introduction Transcripts

Course Overview
Hi, I'm Matthew Renze with Pluralsight and welcome to Multivariate Data Visualization with R. R is a very popular programming language for data analysis and data visualization. It's interactive programming capabilities, powerful data analysis tools, and data visualization capabilities make it many experts first choice for creating professional data visualizations. In this course we'll learn how to create and interpret multivariate data visualizations, that is data visualizations involving three or more variables. We'll do this using the three main plotting systems in R, that is the base graphic system, lattice, and ggplot2. As an overview of this course, first we'll learn the basics of creating multivariate data visualizations in R. Next we'll learn how to create and interpret data visualizations that involve various combinations of three categorical or numeric variables. Finally, we'll learn how to create and interpret data visualizations that involve an arbitrary number of variables at the same time. By the end of this course you'll have the skills necessary to create and interpret a variety of multivariate data visualizations using R. Before beginning this course it's recommended that you have sufficient experience creating basic data visualizations with R. If you do not meet these prerequisites, please watch my previous course in Pluralsight titled Beginning Data Visualization with R. It contains all the necessary prerequisites for this course. So please join us today at Pluralsight and learn how to transform your data into actual insight with multivariate data visualization with R.

Visualizing Three Categorical Variables
Hello again and welcome to our next module on data visualization with R. I'm Matthew Renze with Pluralsight and in this module we'll learn how to create and interpret data visualizations for three categorical variables using R. As an overview of this module, first we'll learn about data visualizations that involve three categorical variables. Next we'll learn how to create these data visualizations using the base graphic system. Then we'll learn how to create these same data visualizations using Lattice. Finally, we'll create these data visualizations using ggplot2. To help orient ourselves in relation to the rest of the course, this module will cover qualitative trivariate analysis, that is the analysis of three categorical variables. In addition we'll be building up what we learned in the first course, that is univariate and bivariate analysis and building the foundation for the remainder of trivariate analysis and multivariate analysis.

Visualizing Two Categorical and One Numeric Variables
Hello and welcome back to multivariate data visualization with R. I'm Matthew Renze with Pluralsight and in this module we'll learn now to create and interpret data visualizations for two categorical variables and one numeric variable using R. As an overview of this module, first we'll learn how to create and interpret data visualizations that involve two categorical and one numeric variables. Next we'll learn how to create these data visualizations using the base graphic system. Then we'll learn how to create the same data visualizations using Lattice. Finally we'll create these data visualizations using ggplot2. To help orient ourselves in relation to the rest of the course, this module will cover trivariate data analysis for two qualitative and one quantitative variable, that is the analysis of two categorical and one numeric variables. In addition, we'll be building upon qualitative trivariate analysis and preparing for the remainder of trivariate and multivariate data analysis.

Visualizing One Categorical and Two Numeric Variables
Welcome back to Data Visualization with R. I'm Matthew Renze with Pluralsight and in this module we'll learn how to create and interpret data visualizations for one categorical and two numeric variables using R. As an overview of this module, first we'll learn how to create and interpret data visualizations that involve one categorical variable and two numeric variables. Next we'll learn how to create these data visualizations using the base graphic system. Then we'll learn how to create the same data visualizations using Lattice. Finally, we'll create these data visualizations using ggplot2. To help orient ourselves in relation to the rest of this course, this module will cover trivariate analysis for one qualitative and two quantitative variables, that is the analysis of one categorical and two numeric variables. In addition we'll be building upon the two types of trivariate analysis that we've already seen and preparing to finish up trivariate analysis and move on to multivariate analysis.

Visualizing Three Numeric Variables
Hello again and welcome to our next module on data visualization with R. I'm Matthew Renze with Pluralsight and in this module we'll learn how to create and interpret data visualizations for three numeric variables using R. An as overview of this module, first we'll learn how to create and interpret data visualizations that involve three numeric variables. Next we'll learn how to create these data visualizations using the base graphic system. Then we'll learn how to create these same data visualizations using Lattice. Finally, we'll create these data visualizations using ggplot2. To help orient ourselves in relation to the rest of the course, this module will cover quantitative trivariate analysis, that is the analysis of three numeric variables. In addition we'll be building upon our previous modules on trivariate analysis and preparing for multivariate analysis as well.

Visualizing Many Variables
Hello again and welcome to our final module on multivariate data visualization with R. I'm Matthew Renze with Pluralsight and in this module we'll learn how to create and interpret data visualizations that involve many variables at the same time using R. As an overview of this module, first we'll learn how to create and interpret data visualizations that involve many variables, that is an arbitrary number of variables at the same time. Next we'll learn how to create these data visualizations using the base graphic system. Then we'll learn how to create these same data visualizations using Lattice. Next we'll create these data visualizations using ggplot2. Finally we'll wrap things up for this module and for the course as a whole. To help orient ourselves in relation to the rest of the course, this module will cover multivariate data analysis. That is, the analysis of many variables at the same time. In addition, we'll be building upon trivariate analysis and completing our study of the analysis of categorical and numeric variables in preparation for learning about analyzing other types of data in the next and final course in this three part data visualization series.