Dive into a comprehensive series of R tutorials covering essential aspects of data management, analysis, and visualization. Learn to download and install R and RStudio, navigate the RStudio interface, create and save R scripts, and set up projects. Master data manipulation techniques including reading, cleaning, filtering, and restructuring data. Explore statistical analyses such as descriptive statistics, reliability testing, t-tests, ANOVA, and various regression methods. Develop skills in data visualization with scatterplots and bar charts. Tackle advanced topics like path analysis, mediation analysis, survival analysis, and text analysis. Gain practical experience in creating Shiny web apps and evaluating disparate impact using various statistical methods. Download accompanying data files from the provided GitHub repository to practice hands-on exercises throughout the tutorials.
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
