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 tutorial videos. As well as learning statistics, with this text students learn 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
