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

International Student Edition


August 2019 | SAGE Publications, Inc

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.
 
 
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

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