Data Analysis in R
Compiled: 2025-06-16
Chapter 1 About
Welcome to this BookDown website Data Analysis in R designed to help you develop your knowledge of how to conduct statistical analysis, create figures, and troubleshoot in R. The book is broken into four chapters:
1. About
- A brief introduction to the resource.
2. Foundations of data analysis with R
- Setting up your environment
- Vectors, factors, matrices, and data frames
- Data manipulation with tidyverse
3. Importing, saving, and exploring data
- Importing: Getting your data into R
- Note on data from Qualtrics
- Good practices: Making sure your data is correct
- Distributions and summary statistics: Understanding basic properties of data
4. Inferential statistics
- Pearson correlation: Assessing relationships between variables
- Linear regression: Predicting outcomes based on a single predictor
- T-test: Comparing means between two groups
- ANOVA: Analyzing variance between multiple groups