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Statistics for People Who (Think They) Hate Statistics Using R
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Statistics for People Who (Think They) Hate Statistics Using R

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544 pages | SAGE Publications, Inc

Neil J. Salkind’s bestselling 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 text for use with the R software, Statistics for People Who (Think They) Hate Statistics Using R. New co-author Leslie A. Shaw carries forward Salkind’s signature humorous, personable, and informative approach as the text guides students in a grounding of statistical basics and R computing, and the application of statistics to research studies. The book covers various basic and advanced statistical procedures, from correlation and graph creation to analysis of variance, regression, non-parametric tests, and more.  

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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 Différence
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

Supplements

Instructor Resource Site
edge.sagepub.com/salkindshaw

SAGE edge for instructors supports your teaching by making it easy to integrate quality content and create a rich learning environment for students with:
  • a password-protected site for complete and protected access to all text-specific instructor resources;  
  • R syntax and data files are available for download and use with exercises in the book;
  • test banks that provide a diverse range of ready-to-use options that save you time. You can also easily edit any question and/or insert your own personalized questions;
  • multimedia content featuring original screencast tutorial videos that demonstrate setting up the data and running selected problems in R meet the learning needs of today’s media-savvy students and bring concepts to life; and
  • editable, chapter-specific PowerPoint® slides that offer complete flexibility for creating a multimedia presentation for your course.
 
Student Study Site
SAGE edge for students enhances learning, it’s easy to use, and offers:
  • an open-access site that makes it easy for students to maximize their study time, anywhere, anytime;
  • R syntax and data files are available for download and use with exercises in the book;
  • video resources that bring concepts to life, are tied to learning objectives, and are curated and produced exclusively for this text, featuring: 
    • Screencast tutorial videos demonstrate setting up the data and running selected problems in R
  • eFlashcards that strengthen understanding of key terms and concepts; and
  • eQuizzes that allow students to practice and assess how much they’ve learned and where they need to focus their attention.
 

“Salkind is the master of presenting options for data analysis in a logical, straightforward manner so students are able to focus on the meaning rather than the math of statistics.”

Jacqueline Craven
Delta State University

“The (late) Dr. Salkind's text continues (with Dr. Shaw's R-integration) to be a readable statistical text that provides a gentle yet surprisingly comprehensive introduction to statistics. For anyone teaching a basic level, introductory level, or first class in statistics, I cannot think of a better text. This R update adds an important element to the Excel and SPSS versions of this inimitable text.”

Jeff Savage
Cornerstone University

“There are many textbooks on R, textbooks on Statistics, and textbooks on R and Statistics that are extremely technical, and difficult to read and use. This textbook is the golden mean!”

Shlomo Sawilowsky
Wayne State University

“The text makes statistics accessible for even the most ‘math-phobic’ student and ‘demystifies’ the world of R. It is the most comprehensive statistics textbook that walks students through both the mathematical and software steps of doing statistics.”

Daniel Scheller
University of Texas at El Paso

“The value of this text is that it presents complex ideas in a way that people can relate to—using examples, walking through steps, and providing all the additional tools needed to succeed in an introduction to statistics course.”

Candace Forbes Bright
East Tennessee State University

“This text is a thorough and effective packaging of statistical analysis and computational techniques in the R language, which would be highly useful to students from a variety of backgrounds.”

Matthew Phillips
University of North Carolina, Charlotte

“Salkind and Shaw do an excellent job of presenting difficult statistical concepts and tools in a highly accessible manner. One of the best introductory statistics textbooks available.”

Scott Comparato
Southern Illinois University

“Salkind's book has always been the very best text for introducing my undergraduate students to statistics. Now, it introduces R as well. I will recommend this book to everyone.”

Matthew R. Miles
Brigham Young University, Idaho

“As with previous editions of this book by Dr. Salkind, this textbook captures the essence of Dr. Salkind's style, talent, and expertise in explaining statistics. Including information and instruction on R software for analysis is a benefit since students can now access a free software program.”

Mary Beth Zeni
Ursuline College
Key features
KEY FEATURES: 
  • Two introductory chapters on R and on R Studio, plus an appendix on other R packages and resource sites ensures that students receive ample support for getting started with R.
  • Inferential statistics chapters start with an example from a journal article to show students how that chapter's example is used in real life.
  • “The Path to Wisdom and Knowledge” flowcharts help students learn how to select the appropriate statistical test in the core chapters covering inferential statistics and serve as an especially helpful resource for visual learners.
  • Step-by-step demonstrations of each statistical procedure in R include examples of how to import datasets, enter the syntax to run tests, and guidance on how to understand the output.
  • For those instructors currently using Salkind’s Excel or SPSS editions and switching to R, adoption of this R version is painless with chapters 8-20 requiring few course updates.
  • Additional resources at edge.sagepub.com/salkindshaw, such as code and datasets, which also includes screencast R tutorial videos for students, and PowerPoint slides and additional test questions for instructors, make it easy to transition to this text and to R.
 

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