# Statistics for People Who (Think They) Hate Statistics Using R - International Student Edition

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## Description

Neil J. Salkind's best-selling Statistics for People Who (Think They) Hate Statistics has been helping ease student anxiety around an often intimidating subject since it first published in 2000. Now the bestselling SPSS and Excel versions are joined by a first edition of the text for use with the R software. New co-author Leslie A. Shaw carries forward Neil's signature humorous, personable, and informative approach. The text guides students through various statistical procedures, beginning with descriptive statistics, correlation, and graphical representation of data, and ending with inferential techniques and analysis of variance.

Features and benefits:

Lots of support for getting started with R: Included are two introductory chapters on R and on R Studio, plus an appendix on other R packages and resource sites.

Step-by-step demonstrations of each statistical procedure in R: The authors show how to import the dataset, enter the syntax to run the test, and understand the output.

Additional resources make it easy to transition to this text, and to R: Code and datasets are available on an accompanying website, which also includes screencast R tutorial videos for students, and PowerPoint slides and additional test questions for instructors.

show more

Features and benefits:

Lots of support for getting started with R: Included are two introductory chapters on R and on R Studio, plus an appendix on other R packages and resource sites.

Step-by-step demonstrations of each statistical procedure in R: The authors show how to import the dataset, enter the syntax to run the test, and understand the output.

Additional resources make it easy to transition to this text, and to R: Code and datasets are available on an accompanying website, which also includes screencast R tutorial videos for students, and PowerPoint slides and additional test questions for instructors.

show more

## Product details

- Paperback
- 177 x 254mm | 990g
- 12 Sep 2019
- SAGE Publications Inc
- Thousand Oaks, United States
- English
- International Student Edition
- 1544387881
- 9781544387888
- 556,594

## Table of contents

Preface

Acknowledgements

About the Authors

Part I Yippee! I'm in Statistics

Chapter 1. Statistics or Sadistics? It's Up to You

What You Will Learn in This Chapter

Why Statistics?

A 5-Minute History of Statistics

Statistics: What it is and Isn't

What am I doing in a Statistics Class?

Ten Ways to Use this Book (and Learn Statistics at the Same Time)

Key to Difficulty Icons

Glossary

Real-World Stats

Summary

Time to Practice

Part II Welcome to the Interesting, Flexible, Useful, Fun and (Very) Deep Worlds of R and RStudio

Chapter 2. Here's Why We Love R and How to Get Started

What You Will Learn in This Chapter

A Very Short History of R

The Plusses of Using R

Where to Find and Download R

The Opening R Screen

A Note About Formatting

Bunches of Data - Free!

Getting R Help

Some Important Lingo

RStudio

Where to Find RStudio and How to Install It

Ordering from RStudio

Summary

Time to Practice

Chapter 3. Using RStudio: Much Easier Than You Think

What You Will Learn in This Chapter

Why RStudio (and Why Not Just R?)

The Grand Tour and All About Those Four Panes

RStudio Pane Goodies

Showing Your Stuff - Working With Menus and Tabs and A Sample Data Analysis Using RStudio

Working with Data

Next Step: Using and Importing Datasets

Reading in Established Datasets

Computing Some Statistics

Summary

Time to Practice

Part III Sigma Freud and Descriptive Statistics

Chapter 4. Means to an End: Computing and Understanding Averages

What You Will Learn in This Chapter

What You Will Learn in This Chapter Computing the Mean

Computing the Median

Computing the Mode

When to Use What Measure of Central Tendency (and All You Need to Know About Scales of Measurement for Now)

Using the Computer to Compute Descriptive Statistics

Real World Stats

Summary

Time to Practice

Chapter 5. Understanding Variability: Vive la Difference

What You Will Learn in This Chapter

Why Understanding Variability is Important

Computing the Range

Computing the Standard Deviation

Computing the Variance

Using R to Compute Measures of Variability

Real World Stats

Summary

Time to Practice

Chapter 6. Creating Graphs: A Picture Really Is Worth a Thousand Words

What You Will Learn in This Chapter

Why Illustrate Data?

Ten Ways to a Great Graphic

First Things First: Creating a Frequency Distribution

The Plot Thickens: Creating a Histogram

The Next Step: A Frequency Polygon

Other Cool Ways to Chart Data

Using the Computer (R, That Is) to Illustrate Data

Real World Stats

Summary

Time to Practice

Chapter 7. Computing Correlation Coefficients: Ice Cream and Crime

What You Will Learn in This Chapter

What are Correlations All About?

Computing a Simple Correlation Coefficient

Understanding What the Correlation Coefficient Means

A Determined Effort: Squaring the Correlation Coefficient

Other Cool Correlations

Parting Ways: A Bit About Partial Correlations

Summary

Time to Practice

Chapter 8: Understanding Reliability and Validity: Just the Truth

What You Will Learn in This Chapter

An Introduction to Reliability and Validity

Reliability: Doing it Again Until You Get it Right

Different Types of Reliability

How Big is Big? Finally: Interpreting Reliability Coefficients

Validity: Whoa! What is the Truth?

A Last Friendly Word

Validity and Reliability: Really Close Cousins

Real World Stats

Summary

Time to Practice

Part IV Taking Chances for Fun and Profit

Chapter 9. Hypotheticals and You: Testing Your Questions

What You Will Learn in This Chapter

So You Want to Be a Scientist

Samples and Populations

The Null Hypothesis

The Research Hypothesis

What Makes a Good Hypothesis?

Real-World Stats

Summary

Time to Practice

Chapter 10. Probability and Why It Counts: Fun with a Bell-Shaped Curve

What You'll Learn About in this Chapter

Why Probability?

The Normal Curve (A.K.A The Bell-Shaped Curve)

Our Favorite Standard Score

Fat and Skinny Frequency Distributions

Real World Stats

Summary

Time to Practice

Part IV Significantly Different: Using Inferential Statistics

Chapter 11. Significantly Significant: What It Means for You and Me

What You'll Learn About in this Chapter

The Concept of Significance

Significance Versus Meaningfulness

An Introduction to Inferential Statistics

An Introduction to Tests of Significance

Be Even More Confident

Real World Stats

Summary

Time to Practice

12. The One-Sample Z-Test: Only the Lonely

What You'll Learn About in this Chapter

Introduction to the One-Sample Z-Test

The Path to Wisdom and Knowledge

Computing the Z-Test Statistic

Using R to Perform a Z-Test

Special Effects: Are Those Differences for Real?

Real World Stats

Summary

Time to Practice

Chapter 13. t(ea) for Two: Tests Between the Means of Different Groups

What You'll Learn About in This Chapter

Introduction to the t-test for Independent Samples

The Path to Wisdom and Knowledge

Computing the t-Test Statistic

Using R to Perform a t-Test

Real-World Stats

Summary

Time to Practice

14. t(ea) for Two (Again): Tests Between the Means of Related Groups

What You'll Learn About in This Chapter

Introduction of the t-Test for Dependent Samples

The Path to Wisdom and Knowledge

Computing the t-Test Statistic

Using R to Perform a t-Test

The Effect Size for t(ea) for Two (Again)

Real World Stats

Summary

Time to Practice

Chapter 15. Two Groups Too Many? Try Analysis of Variance

Introduction to Analysis of Variance

The Path to Wisdom and Knowledge

Different Flavors of ANOVA

Computing the F-test Statistic

Using R to Compute the F Ratio

The Effect Size for One-Way ANOVA

But Where is the Difference?

Real World Stats

Summary

Time to Practice

Chapter 16. Two Too Many Factors: Factorial Analysis of Variance-A Brief Introduction

What You'll Learn About in This Chapter

Introduction to Factorial Analysis of Variance

The Path to Wisdom and Knowledge

A New Flavor of ANOVA

All of These Effects

Even More Interesting Interaction Effects

Using R to Compute the F Ratio

Computing the Effect Size for Factorial ANOVA

Real World Stats

Summary

Time to Practice

Chapter 17. Testing Relationships Using the Correlation Coefficient: Cousins or Just Good Friends?

What You'll Learn About in This Chapter

Introduction to Testing the Correlation Coefficient

The Path to Wisdom and Knowledge

Computing the Test Statistic

Using R to Compute a Correlation Coefficient (Again)

Real World Stats

Summary

Time to Practice

18. Using Linear Regression: Predicting the Future

What You'll Learn About in this Chapter

Introduction to Linear Regression

What is Prediction All About?

The Logic of Prediction

Drawing the World's Best Line (for Your Data)

How Good is Your Prediction?

Using R to Compute the Regression Line

The More Predictors the Better? Maybe

Real World Stats

Summary

Time to Practice

Part VI More Statistics! More Tools! More Fun!

Chapter 19. Chi-Square and Some Other Nonparametric Tests: What to Do When You're Not Normal

What You'll Learn About in this Chapter

Introduction toe Nonparametric Statistics

Introduction to the Goodness of Fit (One-Sample) Chi-Square

Computing the Goodness of Fit Chi-Square Test Statistic

Introduction to the Test of Independence Chi-Square

Computing the Test of Independence Chi-Square Test Statistic

Using R to Perform Chi-Square Tests

Summary

Time to Practice

20. Some Other (Important) Statistical Procedures You Should Know About: A Statistical Software Sampler

What You'll Learn About in this Chapter

Multivariate Analysis of Variance

Repeated Measures Analysis of Variance

Analysis of Covariance

Multiple Regression

Multilevel Models

Meta-Analysis

Logistic Regression

Factor Analysis

Path Analysis

Structural Equation Modeling

Summary

Appendix A: More Fun Stuff with R and RStudio

Appendix B: Tables

Appendix C: Data Sets

Appendix D: Answers to Practice Questions

Appendix E: Math: Just the Basics

Appendix F: The Ten (or More) Best (and Most Fun) Internet Sites for Statistics Stuff

Appendix G: The Ten Commandments of Data Collection

Appendix H: Glossary

Appendix I: The Reward

Index

show more

Acknowledgements

About the Authors

Part I Yippee! I'm in Statistics

Chapter 1. Statistics or Sadistics? It's Up to You

What You Will Learn in This Chapter

Why Statistics?

A 5-Minute History of Statistics

Statistics: What it is and Isn't

What am I doing in a Statistics Class?

Ten Ways to Use this Book (and Learn Statistics at the Same Time)

Key to Difficulty Icons

Glossary

Real-World Stats

Summary

Time to Practice

Part II Welcome to the Interesting, Flexible, Useful, Fun and (Very) Deep Worlds of R and RStudio

Chapter 2. Here's Why We Love R and How to Get Started

What You Will Learn in This Chapter

A Very Short History of R

The Plusses of Using R

Where to Find and Download R

The Opening R Screen

A Note About Formatting

Bunches of Data - Free!

Getting R Help

Some Important Lingo

RStudio

Where to Find RStudio and How to Install It

Ordering from RStudio

Summary

Time to Practice

Chapter 3. Using RStudio: Much Easier Than You Think

What You Will Learn in This Chapter

Why RStudio (and Why Not Just R?)

The Grand Tour and All About Those Four Panes

RStudio Pane Goodies

Showing Your Stuff - Working With Menus and Tabs and A Sample Data Analysis Using RStudio

Working with Data

Next Step: Using and Importing Datasets

Reading in Established Datasets

Computing Some Statistics

Summary

Time to Practice

Part III Sigma Freud and Descriptive Statistics

Chapter 4. Means to an End: Computing and Understanding Averages

What You Will Learn in This Chapter

What You Will Learn in This Chapter Computing the Mean

Computing the Median

Computing the Mode

When to Use What Measure of Central Tendency (and All You Need to Know About Scales of Measurement for Now)

Using the Computer to Compute Descriptive Statistics

Real World Stats

Summary

Time to Practice

Chapter 5. Understanding Variability: Vive la Difference

What You Will Learn in This Chapter

Why Understanding Variability is Important

Computing the Range

Computing the Standard Deviation

Computing the Variance

Using R to Compute Measures of Variability

Real World Stats

Summary

Time to Practice

Chapter 6. Creating Graphs: A Picture Really Is Worth a Thousand Words

What You Will Learn in This Chapter

Why Illustrate Data?

Ten Ways to a Great Graphic

First Things First: Creating a Frequency Distribution

The Plot Thickens: Creating a Histogram

The Next Step: A Frequency Polygon

Other Cool Ways to Chart Data

Using the Computer (R, That Is) to Illustrate Data

Real World Stats

Summary

Time to Practice

Chapter 7. Computing Correlation Coefficients: Ice Cream and Crime

What You Will Learn in This Chapter

What are Correlations All About?

Computing a Simple Correlation Coefficient

Understanding What the Correlation Coefficient Means

A Determined Effort: Squaring the Correlation Coefficient

Other Cool Correlations

Parting Ways: A Bit About Partial Correlations

Summary

Time to Practice

Chapter 8: Understanding Reliability and Validity: Just the Truth

What You Will Learn in This Chapter

An Introduction to Reliability and Validity

Reliability: Doing it Again Until You Get it Right

Different Types of Reliability

How Big is Big? Finally: Interpreting Reliability Coefficients

Validity: Whoa! What is the Truth?

A Last Friendly Word

Validity and Reliability: Really Close Cousins

Real World Stats

Summary

Time to Practice

Part IV Taking Chances for Fun and Profit

Chapter 9. Hypotheticals and You: Testing Your Questions

What You Will Learn in This Chapter

So You Want to Be a Scientist

Samples and Populations

The Null Hypothesis

The Research Hypothesis

What Makes a Good Hypothesis?

Real-World Stats

Summary

Time to Practice

Chapter 10. Probability and Why It Counts: Fun with a Bell-Shaped Curve

What You'll Learn About in this Chapter

Why Probability?

The Normal Curve (A.K.A The Bell-Shaped Curve)

Our Favorite Standard Score

Fat and Skinny Frequency Distributions

Real World Stats

Summary

Time to Practice

Part IV Significantly Different: Using Inferential Statistics

Chapter 11. Significantly Significant: What It Means for You and Me

What You'll Learn About in this Chapter

The Concept of Significance

Significance Versus Meaningfulness

An Introduction to Inferential Statistics

An Introduction to Tests of Significance

Be Even More Confident

Real World Stats

Summary

Time to Practice

12. The One-Sample Z-Test: Only the Lonely

What You'll Learn About in this Chapter

Introduction to the One-Sample Z-Test

The Path to Wisdom and Knowledge

Computing the Z-Test Statistic

Using R to Perform a Z-Test

Special Effects: Are Those Differences for Real?

Real World Stats

Summary

Time to Practice

Chapter 13. t(ea) for Two: Tests Between the Means of Different Groups

What You'll Learn About in This Chapter

Introduction to the t-test for Independent Samples

The Path to Wisdom and Knowledge

Computing the t-Test Statistic

Using R to Perform a t-Test

Real-World Stats

Summary

Time to Practice

14. t(ea) for Two (Again): Tests Between the Means of Related Groups

What You'll Learn About in This Chapter

Introduction of the t-Test for Dependent Samples

The Path to Wisdom and Knowledge

Computing the t-Test Statistic

Using R to Perform a t-Test

The Effect Size for t(ea) for Two (Again)

Real World Stats

Summary

Time to Practice

Chapter 15. Two Groups Too Many? Try Analysis of Variance

Introduction to Analysis of Variance

The Path to Wisdom and Knowledge

Different Flavors of ANOVA

Computing the F-test Statistic

Using R to Compute the F Ratio

The Effect Size for One-Way ANOVA

But Where is the Difference?

Real World Stats

Summary

Time to Practice

Chapter 16. Two Too Many Factors: Factorial Analysis of Variance-A Brief Introduction

What You'll Learn About in This Chapter

Introduction to Factorial Analysis of Variance

The Path to Wisdom and Knowledge

A New Flavor of ANOVA

All of These Effects

Even More Interesting Interaction Effects

Using R to Compute the F Ratio

Computing the Effect Size for Factorial ANOVA

Real World Stats

Summary

Time to Practice

Chapter 17. Testing Relationships Using the Correlation Coefficient: Cousins or Just Good Friends?

What You'll Learn About in This Chapter

Introduction to Testing the Correlation Coefficient

The Path to Wisdom and Knowledge

Computing the Test Statistic

Using R to Compute a Correlation Coefficient (Again)

Real World Stats

Summary

Time to Practice

18. Using Linear Regression: Predicting the Future

What You'll Learn About in this Chapter

Introduction to Linear Regression

What is Prediction All About?

The Logic of Prediction

Drawing the World's Best Line (for Your Data)

How Good is Your Prediction?

Using R to Compute the Regression Line

The More Predictors the Better? Maybe

Real World Stats

Summary

Time to Practice

Part VI More Statistics! More Tools! More Fun!

Chapter 19. Chi-Square and Some Other Nonparametric Tests: What to Do When You're Not Normal

What You'll Learn About in this Chapter

Introduction toe Nonparametric Statistics

Introduction to the Goodness of Fit (One-Sample) Chi-Square

Computing the Goodness of Fit Chi-Square Test Statistic

Introduction to the Test of Independence Chi-Square

Computing the Test of Independence Chi-Square Test Statistic

Using R to Perform Chi-Square Tests

Summary

Time to Practice

20. Some Other (Important) Statistical Procedures You Should Know About: A Statistical Software Sampler

What You'll Learn About in this Chapter

Multivariate Analysis of Variance

Repeated Measures Analysis of Variance

Analysis of Covariance

Multiple Regression

Multilevel Models

Meta-Analysis

Logistic Regression

Factor Analysis

Path Analysis

Structural Equation Modeling

Summary

Appendix A: More Fun Stuff with R and RStudio

Appendix B: Tables

Appendix C: Data Sets

Appendix D: Answers to Practice Questions

Appendix E: Math: Just the Basics

Appendix F: The Ten (or More) Best (and Most Fun) Internet Sites for Statistics Stuff

Appendix G: The Ten Commandments of Data Collection

Appendix H: Glossary

Appendix I: The Reward

Index

show more

## About Neil J. Salkind

Neil J. Salkind received his PhD in human development from the University of Maryland, and after teaching for 35 years at the University of Kansas, he was Professor Emeritus in the Department of Psychology and Research in Education, where he collaborated with colleagues and work with students. His early interests were in the area of children's cognitive development, and after research in the areas of cognitive style and (what was then known as) hyperactivity, he was a postdoctoral fellow at the University of North Carolina's Bush Center for Child and Family Policy. His work then changed direction to focus on child and family policy, specifically the impact of alternative forms of public support on various child and family outcomes. He delivered more than 150 professional papers and presentations; written more than 100 trade and textbooks; and is the author of Statistics for People Who (Think They) Hate Statistics (SAGE), Theories of Human Development (SAGE), and Exploring Research (Prentice Hall). He has edited several encyclopedias, including the Encyclopedia of Human Development, the Encyclopedia of Measurement and Statistics, and the Encyclopedia of Research Design. He was editor of Child Development Abstracts and Bibliography for 13 years. He lived in Lawrence, Kansas, where he liked to read, swim with the River City Sharks, work as the proprietor and sole employee of big boy press, bake brownies (see www.statisticsforpeople.com for the recipe), and poke around old Volvos and old houses.

Leslie A. Shaw received her PhD in psychology from the University of Kansas, specifically in quantitative psychology. During graduate school, she worked on a variety of projects from university class enrollment, alumni donations, community policing, and self-determination. She also taught statistical computing labs and introductory statistics in a team-teaching format. The self-determination research led to more opportunities at the Beach Center on Disabilities and Kansas University Center on Developmental Disabilities to contribute to research on the Supports Intensity Scale, both adult and child versions, and the Self-Determination Inventory: Self Report. After graduation, she held a postdoctoral position at the Kansas University Center on Developmental Disabilities, where she also taught a class each semester in the quantitative psychology program. She is now a research associate at the Yang-Tan Institute on Employment and Disability in the ILR School at Cornell University. She has coauthored more than 20 articles to date, and she serves as a statistical consultant for the journal Intellectual and Developmental Disabilities.

show more

Leslie A. Shaw received her PhD in psychology from the University of Kansas, specifically in quantitative psychology. During graduate school, she worked on a variety of projects from university class enrollment, alumni donations, community policing, and self-determination. She also taught statistical computing labs and introductory statistics in a team-teaching format. The self-determination research led to more opportunities at the Beach Center on Disabilities and Kansas University Center on Developmental Disabilities to contribute to research on the Supports Intensity Scale, both adult and child versions, and the Self-Determination Inventory: Self Report. After graduation, she held a postdoctoral position at the Kansas University Center on Developmental Disabilities, where she also taught a class each semester in the quantitative psychology program. She is now a research associate at the Yang-Tan Institute on Employment and Disability in the ILR School at Cornell University. She has coauthored more than 20 articles to date, and she serves as a statistical consultant for the journal Intellectual and Developmental Disabilities.

show more