Data Analysis 101 with R

This intermediate path develops a practical workflow for analyzing data in R. You will use dplyr and tidyr to select, filter, summarize, reshape, merge, and clean datasets while addressing missing values and other preprocessing needs. You will create clear visualizations with ggplot2 and improve data-processing workflows for complex datasets. You will also apply descriptive and inferential statistics, work with probability distributions, and formulate, conduct, and interpret hypothesis tests. This path is intended for learners with foundational R knowledge who want to strengthen their ability to prepare, analyze, visualize, and communicate data.

Syllabus

Manipulate datasets with dplyr by selecting, filtering, summarizing, and mutating data
Transform and merge complex datasets using efficient R workflows
Clean and reshape data with tidyr and handle missing values
Create clear, informative visualizations with ggplot2
Apply descriptive and inferential statistical methods in R
Formulate, conduct, and interpret hypothesis tests
Communicate findings through appropriate visual and statistical summaries