Data Preprocessing and Resampling Using Tidymodels

Explore data preprocessing and resampling techniques using tidymodels packages in R with #TidyTuesday data on college tuition and diversity in US colleges. Dive into exploratory data analysis, creating recipes, filtering, and applying steps to prepare data for modeling. Learn to implement logistic regression, perform model selection, and conduct resampling by grouping models. Discover how to work with testing data and gain insights into improving resampling techniques for more accurate results.

Introduction
Data
States
State region
State table
Region table
Columns
Total Enrollment
exploratory plots
box plots
facet wrap
do schools with higher proportion of minority students
recipe
filter
steps
results
juice
logistic regression
model selection
resampling
group by model
testing data