This course focuses on teaching data management, analysis, and visualization using R. The learning outcomes include skills such as reading, filtering, cleaning, and manipulating data, as well as conducting various statistical analyses like t-tests, ANOVA, regression, and survival analysis. The course also covers creating visualizations, web apps, and text analysis in R. The teaching method includes hands-on tutorials and written instructions. This course is intended for individuals interested in learning R for data analysis and visualization purposes.
Overview
Syllabus
Downloading & Installing R & RStudio.
Orientation to RStudio.
Creating & Saving an R Script.
Setting a Working Directory in R.
Creating a Project in RStudio.
Gentle Introduction to R.
Orientation to Written Tutorials.
Reading Data into R.
Removing & Adding Variable Names in R.
Arranging (Sorting) Data in R.
Joining (Merging) Data in R.
Writing Data from R.
Filtering Data in R.
Cleaning Data in R.
Removing Objects from R Global Environment.
Creating Tables in R.
Manipulating & Restructuring Data in R.
Descriptive Statistics in R.
Internal Consistency Reliability in R.
Creating Scale Scores in R.
Aggregating & Segmenting Data in R.
Creating PivotTables in R.
Scatterplots in R.
Correlation in R.
Correlation Matrix in R.
Independent-Samples t-test in R.
Paired-Samples t-test in R.
One-Way ANOVA in R.
Evaluating 2x2 Mixed-Factorial Design Using Independent-Samples t-test in R.
Centering & Standardizing Variables in R.
Chi-Square Test of Independence in R.
Estimating a Market Pay Line in R.
Aging Market Survey Data in R.
Applying Market Survey Weights in R.
Hierarchical Linear Regression in R.
Compa-Ratios & Pay Compression in R.
Moderated Multiple Linear Regression in R.
Path Analysis in R.
Mediation Analysis in R.
k-Fold Cross-Validation in R.
Simple Linear Regression in R.
Multiple Linear Regression in R.
Logistic Regression in R.
Survival Analysis in R.
LASSO Regression in R (Part One).
LASSO Regression in R (Part Two).
Daily Diary Data Cleaning & Merging.
Shiny Web Apps in R.
Introduction to Text Analysis in R.
Evaluating Disparate Adverse Impact Using 4/5ths Rule, Chi-Square Test, & Fisher Exact Test in R.
Evaluating Disparate (Adverse) Impact Using Z-Difference-Test & Z-Impact-Ratio-Test in R.
Visualizing Disparate (Adverse) Impact Using Bar Charts in R.
Taught by
David Caughlin
