Introductory Statistics Using R

Herschel Knapp - Yeshiva University, USA

February 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.

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ISBN: 9781071929001 Paperback Suggested Retail Price: $142.00 Bookstore Price: $113.60

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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

Key features

This friendly and practical introduction to statistics shows students how to properly select, process, and interpret statistics using the R software without heavy emphasis on theory, formula derivations, or software coding.
Online tutorial videos help students learn and use the R software, along with the R Syntax Guide, which includes prepared R code for each statistic.
Practical examples presented throughout the text with exercises at the end of each chapter builds proficiency through hands-on learning.
Datasets are available for all the examples and exercises.

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Introductory Statistics Using R
An Easy Approach

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