1
Overview
2
Setting Up
2.1
R and R Studio
2.2
R Scripts
2.3
R Console
2.4
Working Directories
2.5
A brief note on functions in R
2.6
Installing packages
2.7
Documentation
2.8
Activity
3
Data
3.1
Data formats
3.1.1
Tibbles
3.1.2
Data frames
3.2
Opening non-csv data in R
3.3
Activity
4
Variables
4.1
Variable types
4.2
Variable recoding
4.2.1
A brief pause to talk about “piping”
4.2.2
Variable recoding in the tidyverse approach: mutate
4.2.3
Old school variable recoding in base R
4.3
Variable renaming
4.3.1
Renaming multiple variables at once
5
Data Manipulation
5.1
Subsetting
5.2
Merging
5.2.1
left_join()
5.2.2
Other join commands
5.2.3
merge
5.3
Hierarchical data structures
5.3.1
Going from wide to long
5.3.2
Going from long to wide
6
Summary Statistics
6.1
The tidyverse approach: summarize
7
Grouping
8
the “by” command does something to a variable, in groups based on another variable
9
Basic Statistical Analyses
9.1
T-tests
9.2
OLS Regression
9.3
Logistic Regression
10
Data Visualization
10.1
Basic Plotting
10.2
ggplot2
R Training for SSDS
8
the “by” command does something to a variable, in groups based on another variable
by(iris$Sepal.Length, iris$Species, mean) #calculate mean Sepal.Length by species