Beginning R 4: From Beginner to Pro

✍ Scribed by Matt Wiley, Joshua F. Wiley

• Publisher: Apress
• Year: 2020
• Tongue: English
• Leaves: 481
• Edition: 1
• Category: Library

✦ Synopsis

https://www.apress.com/gp/book/9781484260524

Learn how to use R 4, write and save R scripts, read in and write out data files, use built-in functions, and understand common statistical methods. This in-depth tutorial includes key R 4 features including a new color palette for charts, an enhanced reference counting system (useful for big data), and new data import settings for text (as well as the statistical methods to model text-based, categorical data). 

Each chapter starts with a list of learning outcomes and concludes with a summary of any R functions introduced in that chapter, along with exercises to test your new knowledge. The text opens with a hands-on installation of R and CRAN packages for both Windows and macOS. The bulk of the book is an introduction to statistical methods (non-proof-based, applied statistics) that relies heavily on R (and R visualizations) to understand, motivate, and conduct statistical tests and modeling.

Beginning R 4 shows the use of R in specific cases such as ANOVA analysis, multiple and moderated regression, data visualization, hypothesis testing, and more. It takes a hands-on, example-based approach incorporating best practices with clear explanations of the statistics being done.

You will:

• Acquire and install R and RStudio
• Import and export data from multiple file formats
• Analyze data and generate graphics (including confidence intervals)
• Interactively conduct hypothesis testing
• Code multiple and moderated regression solutions

 

Who This Book Is For 

Programmers and data analysts who are new to R.  Some prior experience in programming is recommended. 

✦ Table of Contents

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