Getting Started with R and RStudio:

Click on the links below to watch tutorials demonstrating how to download, install, and perform basic functions in R and RStudio.

Downloading and Installing R
Downloading and Installing R Studio
Basic R Functions: Typing into R
Opening and Saving Scripts and Plots

R Tutorials:

Click on the links below to watch the R tutorials accompanying the book that demonstrate data management, exploratory data analysis, and key statistical tests using real-world data.

Chapter 1:

Creating and Reading in Data for Analysis: Using a .CSV file
This video demonstrates how to use a .CSV file in R.

Chapter 2:

Making a basic table of frequencies and percentages: Data management
This video demonstrates how to manage data in R using data from the 2014 Behavioral Risk Factor Surveillance Survey.

Chapter 3:

Graphs for a single categorical variable: Building a basic bar graph
This video demonstrates how to build a basic bar graph in R using data from the 2011–2012 National Health and Nutrition Examination Survey.

Chapter 4:

Using distributions to learn about populations from samples: Visualizing the binomial distribution
This video explores the binomial distribution and basic sampling in R using 2017 Kaiser Family Foundation state opioid policy data.

Chapter 5:

Understanding the relationship between two categorical variables using bar graphs, frequencies, and percentages: Data cleaning
This video demonstrates data cleaning for categorical variables in R using 2017 Pew Research Center voting perceptions data.

Chapter 6:

Comparing a sample mean to a population mean: Computing a one sample t-test
This video demonstrates how to compute a one sample t-test in R using 2015–2016 National Health and Nutrition Examination Survey data.

Chapter 7:

Exploring data using graphics and descriptive statistics: Data management and exploratory data analysis
This video demonstrates data management and exploratory data analysis in R using 2018 General Social Survey data.

Chapter 8:

Computing and interpreting the covariance between two variables: Using drop_na()
This video demonstrates computing the covariance using the drop_na() function in R using 2015 United Nations Educational, Scientific, and Cultural Organization data on education.

Chapter 9:

Using exploratory data analysis before developing a linear regression model: Importing and merging sources, checking the descriptive statistics, and using a scatterplot and a correlation coefficient
This video demonstrates how to check descriptive statistics, use a scatterplot, and calculate a correlation coefficient in R using 2017 American Foundation for AIDS Research distance to needle exchange data.

Chapter 10:

Using exploratory data analysis before developing a logistic regression model
This video demonstrates how to perform exploratory data analysis before developing a logistic regression model in R using 2016 Pew Research Center library use data.

Chapter 11:

Exploratory data analysis for the multinomial model
This video demonstrates how to perform exploratory data analysis for the multinomial model in R using 2017 data from the National Science Foundation Scientists and Engineers Statistical Data System.