Share Description
In this course, you’ll learn:
-
Installing R and RStudio
-
Navigating the RStudio environment
-
Importing data from a spreadsheet
-
Working with the tidyverse
-
Piping commands with %>%
-
Visualizing data with R base graphics and ggplot2
-
Visualizing hierarchical clusters
-
Selecting cases and subgroups
-
Recoding variables
-
Calculating frequencies
-
Calculating descriptives
-
Calculating correlations
-
Computing a linear regression
Syllabus:
- Introduction
- R for data science
- Using the exercise files
- 1. What Is R?
- R in context
2. Getting Started
- Installing R
- Environments for R
- Installing RStudio
- Navigating the RStudio environment
- Entering data
- Data types and structures
- Comments and headers
- Packages for R
- The tidyverse
- Piping commands with %>%
- Sample datasets
- Importing data from a spreadsheet
3. Data Visualization
- Using colors in R
- Creating bar charts
- Creating histograms
- Creating box plots
- Creating scatterplots
- Creating line charts
- Creating cluster charts
4. Data Wrangling
- Selecting cases and subgroups
- Recoding variables
- Computing new variables
5. Data Analysis
- Computing frequencies
- Computing descriptives
- Computing correlations
- Computing a linear regression
- Computing contingency tables
