Chapter 1 About

Welcome to this BookDown website Data Analysis and Visualization 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 five 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.

5 Data visualization with ggplot2

Introduction to data visualization principles.
Creating basic plots: Scatter plots, bar plots, line plots, and histograms.
Customizing plots using ggplot2: Adding labels, titles, themes, and annotations.
Multi-panel plots: Faceting data for better insights.
Advanced visualizations: Box plots, density plots, and violin plots.