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Introductory Statistics Using R
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Introductory Statistics Using R
An Easy Approach



April 2025 | SAGE Publications, Inc
Finally, a textbook that makes it simple to teach and learn introductory statistics using the R software! Herschel Knapp′s Introductory Statistics Using R: An Easy Approach is a jargon-free guide to real-world statistics designed to concisely answer three important questions: Which statistic should I use? How do I run the analysis? How do I document the results? Practical examples presented throughout the text with exercises at the end of each chapter build proficiency through hands-on learning. The student website includes datasets, prepared R code for each statistic in the R Syntax Guide, and tutorial videos. As well as learning statistics, with this text students learn how to convert numeric results into clear, publishable documentation.
 
Preface
 
Acknowledgements
 
About the Author
 
Part I: Statistical Foundation
 
Chapter 1: Research Principles
Overview – Research Principles

 
Rationale for Statistics

 
Levels of Measure and Types of Variables

 
Control and Treatment Groups

 
Random Assignment

 
Research Question and Hypothesis Formulation

 
Asking and Answering Research Questions

 
Good Common Sense

 
Key Concepts

 
Practice Exercises

 
 
Chapter 2: Sampling
Overview – Sampling

 
Sampling Rationale

 
Sampling Terminology

 
Representative Sample

 
Probability Sampling

 
Nonprobability Sampling

 
Sampling Bias

 
Optimal Sample Size

 
Good Common Sense

 
Key Concepts

 
Practice Exercises

 
 
Chapter 3: Getting Started In R
Overview – R And Rstudio

 
Setting Up Your RStudio Cloud Account

 
R Syntax Guide

 
Loading Packages

 
Dataset Structure

 
Codebook

 
Uploading a Dataset to R

 
Data File Types

 
First Statistical Run

 
Variable References

 
Exporting Results

 
Copying Graphs

 
Shortcuts

 
Clear the Console Window

 
Doing Math in R

 
Data Order Doesn’t Matter

 
Processing Your Own Data

 
Logging Off

 
Good Common Sense

 
Key Concepts

 
Practice Exercises

 
 
Part II: Statistical Tests
 
Chapter 4: Descriptive Statistics
Overview – Descriptive Statistics

 
Descriptive Statistics in Context

 
Descriptive Statistics for Continuous and Categorical Variables

 
Descriptive Statistics: Continuous Variables (Score)

 
Descriptive Statistics: Categorical Variables (Hand)

 
Managing Data

 
Managing Plots

 
Moving Forward

 
Good Common Sense

 
Key Concepts

 
Practice Exercises

 
 
Chapter 5: t Test and Welch Two Sample t Test
Overview – t Test

 
t Tests and Welch Two Sample t Tests in Context

 
Example

 
Type I and Type II Errors

 
Good Common Sense

 
Key Concepts

 
Practice Exercises

 
 
Chapter 6: ANOVA – Tukey Test and Wilcoxon Multiple Pairwise Comparisons Test
Overview – ANOVA Test

 
ANOVA Tests in Context

 
Layered Learning

 
Example

 
Good Common Sense

 
Key Concepts

 
Practice Exercises

 
 
Chapter 7: Paired t Test and Paired Wilcoxon Test
Overview – Paired t Test

 
Paired t Tests and Paired Wilcoxon Tests in Context

 
Layered Learning

 
Example

 
Good Common Sense

 
Key Concepts

 
Practice Exercises

 
 
Chapter 8: Correlation – Pearson Test and Spearman Test
Overview – Pearson Test

 
Correlation in Context

 
More About Correlation

 
Example

 
Correlation Versus Causation

 
Good Common Sense

 
Key Concepts

 
Practice Exercises

 
 
Chapter 9: Chi-Square
Overview – Chi-Square Test

 
Chi-Square Tests in Context

 
Example

 
Good Common Sense

 
Key Concepts

 
Practice Exercises

 
 
Glossary
 
Index

Finally! A truly straightforward introduction to statistics and R. Writing is approachable, clear, and concise. Students and those interested in getting started with R will find this textbook extremely useful and approachable.

Kate Pok-Carabalona
CUNY-Lehman College

This is an essential guide for new R instructors and students aiming to proficiently grasp statistical analysis. With its clear, step-by-step approach and practical emphasis on real-world applications, this textbook empowers learners with the necessary skills to navigate statistical analysis in R with confidence. I highly recommend it!

Selye Lee
University of Arkansas at Little Rock

This book offers a step-by-step guide appropriate for college students new to both statistics and the statistical software R. The author magically guides us through the journey using approachable language, complemented by the activities and exercises that build on each other throughout the textbook. I know this book is the best available introductory research textbook appropriate for my students in Family and Consumer Sciences.

Yoko Mimura
California State University, Northridge

I highly appreciate this amazing book. It provides a crucial understanding for students of the importance and application of statistical tools in practice. Part 1: Statistical Foundation sets the book apart, as it uniquely emphasizes the foundational reasons behind using statistical methods, something not commonly found in other texts.

Qiwei Li
The University of Texas at Dallas

An essential guide for learning statistics with R, this book offers clear explanations, practical exercises, and valuable multimedia resources, making complex concepts accessible and engaging for students of all levels.

Nicole Farris
Texas A&M University-Commerce

This text serves not only as a process guide for utilizing R for statistical analyses, but it also contains a very clear presentation of research methods, and the foundational knowledge needed to understand the analyses.

Coleen Cicale
Southeastern Louisiana University

This text is a helpful tool for teaching and learning statistics with R.

Michael Welker
Franciscan University of Steubenville

This is an effective, easy to use textbook that guides students not only through the fundamentals of statistics, but also how to run the analysis and interpret the outputs.

Karen L. Robinson
Westcliff University

It is rare that a textbook presents both parametric and non-parametric approaches to basic statistics. The information presented in this textbook is accessible and adds the skill of using R to students resumes.

Brandt A. Smith
Columbus State University