Introductory Statistics Using R

An Easy Approach
Herschel Knapp - Yeshiva University, USA
Introductory Statistics Using R
January 2025 | 256 pages | Sage US
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Description

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 step-by-step step-by-step tutorial videos. In addition to teaching statistics, this text shows students how to convert numeric results into clear, publishable documentation.

Contents

Preface

Preface

Acknowledgements

Acknowledgements

About the Author

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

Glossary

Index

Index

Additional materials

Description

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 step-by-step step-by-step tutorial videos. In addition to teaching statistics, this text shows students how to convert numeric results into clear, publishable documentation.

Contents

Preface

Preface

Acknowledgements

Acknowledgements

About the Author

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

Glossary

Index

Index

Additional materials

SAGE Publishing Logo

Introductory Statistics Using R

An Easy Approach

Herschel Knapp
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January 2025 | 256 pages | Sage US

Format Published Date ISBN Price

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 step-by-step step-by-step tutorial videos. In addition to teaching statistics, this text shows students how to convert numeric results into clear, publishable documentation.


Table Of Contents:

  • 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

Recent Product Reviews:

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

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