Beginning R 4: From Beginner to Pro

Table of Contents
About the Authors
About the Technical Reviewer
Acknowledgments
Foreword
Chapter 1: Installing R
	1.1 Your Tech Stack
	1.2 Updating Your Operating System
		Windows
		MacOS
	1.3 Downloading and Installing R from CRAN
		Windows
		MacOS
	1.4 Downloading and Installing RStudio
		Windows
		MacOS
	1.5 Using RStudio
		New Projects
	1.6 My First R Script
	1.7 Summary
	1.8 Practice for Mastery
		Comprehension Checks
		Exercises
Chapter 2: Installing Packages and Using Libraries
	2.1 Installing Packages
		haven
		readxl
		writexl
		data.table
		extraoperators
		JWileymisc
		ggplot2
		visreg
		emmeans
		ez
		palmerpenguins
	2.2 Using Packages
	2.3 Summary
	2.4 Practice for Mastery
		Comprehension Checks
		Exercises
Chapter 3: Data Input and Output
	3.1 Setup
	3.2 Input
		Manual Entry
		CSV: .csv
		Excel: .xlsx or .xls
		RDS: .rds
		Other Proprietary Formats
			SPSS: .sav
			Stata: .dta
			SAS: .sas7bdat
	3.3 Output
		CSV
		Excel
		RDS
	3.4 Summary
	3.5 Practice for Mastery
		Comprehension Checks
		Exercises
Chapter 4: Working with Data
	4.1 Setup
	4.2 What Do Our Data Look Like?
	4.3 How Does data.table Work?
		How Do Row Operations Work?
			order()
			Subsetting
		How Do Column Operations Work?
			Choosing Columns
			Creating Columns
		How Do by Operations Work?
	4.4 Examples
		Example 1: Metropolitan Area Counts
		Example 2: Metropolitan Statistical Areas (MSAs)
		Example 3
	4.5 Summary
	4.6 Practice for Mastery
		Comprehension Checks
		Exercises
Chapter 5: Data and Samples
	5.1 R Setup
	5.2 Populations and Samples
	5.3 Variables and Data
		Example
			Note
		Example
		Example
		Thoughts on Variables and Data
	5.4 Thinking Statistically
	5.5 Evaluating Studies
	5.6 Evaluating Samples
		Convenience Samples
			Example
			Example
		Kth Samples
			Example
			Example
		Cluster Samples
			Example
			Example
		Stratified Samples
			Example
			Example
		Random Samples
			Example
			Example
		Sample Recap
	5.7 Frequency Tables
		Example
			Example
			Example
	5.8 Summary
	5.9 Practice for Mastery
		Comprehension Checks
		Exercises
Chapter 6: Descriptive Statistics
	6.1 R Setup
	6.2 Visualization
		Histograms
			Example
			Example
		Dot Plots/Charts
			Example
		ggplot2
			Example
			Example
	6.3 Central Tendency
		Arithmetic Mean
			Example
			Example
		Median
			Example
			Example
	6.4 Position
		Example
		Example
		Example
	6.5 Turbulence
		Example
		Example
	6.6 Summary
	6.7 Practice for Mastery
		Comprehension Checks
		Exercises
Chapter 7: Understanding Probability and Distributions
	7.1 R Setup
	7.2 Probability
		Example: Independent
		Example: Complement
		Probability Final Thoughts
	7.3 Normal Distribution
		Example
		Example
		Example
		Example
	7.4 Distribution Probability
		Example
		Example
	7.5 Central Limit Theorem
		Example
		Example
		Example
	7.6 Summary
	7.7 Practice for Mastery
		Comprehension Checks
		Exercises
Chapter 8: Correlation and Regression
	8.1 R Setup
	8.2 Correlations
		Parametric
			Example
			Example
			Example
		Non-parametric: Spearman
			Example
			Example
		Non-parametric: Kendall
			Example
			Example
		Correlation Choices
	8.3 Simple Linear Regression
		Introduction
		Assumptions
			Linearity
			Normality
			Homoscedasticity
			Independence
			Linear Regression Assumption Summary
		R2: Variance Explained
		Linear Regression in R
			Example
			Example
	8.4 Summary
	8.5 Practice for Mastery
		Comprehension Checks
		Exercises
Chapter 9: Confidence Intervals
	9.1 R Setup
	9.2 Visualizing Confidence Intervals
		Example: Sigma Known
		Example: Sigma Unknown
		Example
		Example
	9.3 Understanding Similar vs. Dissimilar Data
		Example
		Example
	9.4 Summary
	9.5 Practice for Mastery
		Comprehension Checks
		Exercises
Chapter 10: Hypothesis Testing
	10.1 R Setup
	10.2 H0 vs. H1
		Example
		Example
	10.3 Type I/II Errors
		Example
		Example
		Example
	10.4 Alpha and Beta
	10.5 Assumptions
	10.6 Null Hypothesis Significance Testing (NHST)
		Example
		Example
		Example
	10.7 Summary
	10.8 Practice for Mastery
		Comprehension Checks
		Exercises
Chapter 11: Multiple Regression
	11.1 R Setup
	11.2 Linear Regression Redux
		Example
	11.3 Multiple Regression
		Implications of Multiple Predictors
		Multiple Regression in R
			Example
		Effect Sizes and Formatting
			Example
			Example
		Assumption and Cleaning
			Example
			Example
	11.4 Categorical Predictors
		Example
		Example
	11.5 Summary
	11.6 Practice for Mastery
		Comprehension Checks
		Exercises
Chapter 12: Moderated Regression
	12.1 R Setup
	12.2 Moderation Theory
		Moderation in R
	12.3 Continuous x Categorical Moderation in R
		Example
	12.4 Continuous x Continuous Moderation in R
	12.5 Summary
	12.6 Practice for Mastery
		Comprehension Checks
		Exercises
Chapter 13: Analysis of Variance
	13.1 R Setup
	13.2 ANOVA Background
		Formal Mathematics
	13.3 One-Way ANOVA
		Example
		Example
	13.4 Factorial ANOVA
		Example
		Example
	13.5 Summary
	13.6 Practice for Mastery
		Comprehension Checks
		Exercises
Bibliography
Index