Data Analysis in R

4.0 credits

This course emphasizes data visualization and exploratory data analysis (EDA) in the R environment. Topics include the tidyverse and the "tidy" approach to data analysis, statistical and graphical tools for bivariate and multivariate EDA, methods for summarizing and visualizing missing data in analysis, statistical communication principles, formatting tables of statistical results for presentation, effect size statistics and their importance for communicating research results, and advanced data visualization with ggplot. Students will become proficient with R packages and functions for EDA and visualization as well as with advanced RMarkdown techniques.