4.3 — Categorical Data & Interactions — R Practice

Author

Answer Key

Published

November 9, 2022

Required Packages & Data

Load all the required packages we will use (note I have installed them already into the cloud project) by running (clicking the green play button) the chunk below:

library(tidyverse) # your friend and mine
library(broom) # for tidy regression
library(modelsummary) # for nice regression tables

We are returning to the speeding tickets data that we began to explore in R Practice 4.1 on Multivariate Regression. Download and read in (read_csv) the data below.

# run or edit this chunk (if you want to rename the data)

# read in data from url 
# or you could download and upload it to this project instead
speed <- read_csv("https://metricsf22.classes.ryansafner.com/files/data/speeding_tickets.csv")
Rows: 68357 Columns: 9
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
dbl (9): Black, Hispanic, Female, Amount, MPHover, Age, OutTown, OutState, S...

ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

This data comes from a paper by Makowsky and Strattman (2009) that we will examine later. Even though state law sets a formula for tickets based on how fast a person was driving, police officers in practice often deviate from that formula. This dataset includes information on all traffic stops. An amount for the fine is given only for observations in which the police officer decided to assess a fine. There are a number of variables in this dataset, but the one’s we’ll look at are:

Variable Description
Amount Amount of fine (in dollars) assessed for speeding
Age Age of speeding driver (in years)
MPHover Miles per hour over the speed limit
Black Dummy \(=1\) if driver was black, \(=0\) if not
Hispanic Dummy \(=1\) if driver was Hispanic, \(=0\) if not
Female Dummy \(=1\) if driver was female, \(=0\) if not
OutTown Dummy \(=1\) if driver was not from local town, \(=0\) if not
OutState Dummy \(=1\) if driver was not from local state, \(=0\) if not
StatePol Dummy \(=1\) if driver was stopped by State Police, \(=0\) if stopped by other (local)

We want to explore who gets fines, and how much. We’ll come back to the other variables (which are categorical) in this dataset in later lessons.

Question 1

We will have to do a little more cleaning to get some of the data into a more usable form.

Part A

Inspect the data with str() or head() or glimpse() to see what it looks like.

# type your code below in this chunk
str(speed)
spc_tbl_ [68,357 × 9] (S3: spec_tbl_df/tbl_df/tbl/data.frame)
 $ Black   : num [1:68357] 0 0 0 0 0 0 0 0 0 0 ...
 $ Hispanic: num [1:68357] 0 0 0 0 0 0 0 0 0 0 ...
 $ Female  : num [1:68357] 1 1 1 0 0 0 1 0 1 0 ...
 $ Amount  : num [1:68357] NA NA NA NA NA NA NA NA NA NA ...
 $ MPHover : num [1:68357] 14 15 15 13 12 17 15 15 15 15 ...
 $ Age     : num [1:68357] 22 43 32 24 54 30 18 53 51 33 ...
 $ OutTown : num [1:68357] 1 1 0 1 1 1 0 0 1 1 ...
 $ OutState: num [1:68357] 0 0 0 0 0 0 0 0 0 0 ...
 $ StatePol: num [1:68357] 0 0 0 0 0 0 0 0 0 0 ...
 - attr(*, "spec")=
  .. cols(
  ..   Black = col_double(),
  ..   Hispanic = col_double(),
  ..   Female = col_double(),
  ..   Amount = col_double(),
  ..   MPHover = col_double(),
  ..   Age = col_double(),
  ..   OutTown = col_double(),
  ..   OutState = col_double(),
  ..   StatePol = col_double()
  .. )
 - attr(*, "problems")=<externalptr>

What class of variable are Black, Hispanic, Female, OutTown, and OutState?

They are all num - numeric variables.

Part B

Notice that when importing the data from the .csv file, R interpreted these variables as numeric (num) or double (dbl), but we want them to be factor (fct) variables, to ensure R recognizes that there are two groups (categories), 0 and 1.

You could convert the variables one at a time to factors using as.factor() inside a mutate() command. But there is a special mutate() command that allows you to apply a transformation (like changing a variable’s class to factor), which you can run the following chunk to execute:

# run or edit this chunk
speed <- speed %>%
  mutate_at(c("Black", "Hispanic", "Female", "OutTown", "OutState"), factor)

speed