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Statistics for People Who (Think They) Hate Statistics

Statistics for People Who (Think They) Hate Statistics
Using Microsoft Excel 2016

Fourth Edition
Additional resources:

February 2016 | 544 pages | SAGE Publications, Inc
Based on Neil J. Salkind’s best-selling text, Statistics for People Who (Think They) Hate Statistics, this adapted Excel 2016 version presents an often intimidating and difficult subject in a way that is clear, informative, and personable. Researchers and students will appreciate the book's unhurried pace and thorough, friendly presentation. Opening with an introduction to Excel 2016, including coverage of how to use functions and formulas, this edition also shows students how to install the Excel Data Analysis Tools option to access a host of useful analytical techniques. The book walks readers through various statistical procedures, beginning with simple descriptive statistics, correlations, and graphical representations of data, and ending with inferential techniques, analysis of variance, and a new introductory chapter on working with large datasets and data mining using Excel.

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Part I: Yippee! I’m in Statistics
Chapter 1: Statistics or Sadistics? It’s Up to You
Why Statistics?  
A Five-Minute History of Statistics  
Statistics: What It Is (and Isn’t)  
Tooling Around With the Analysis ToolPak  
What Am I Doing in a Statistics Class?  
Ten Ways to Use This Book (and Learn Statistics at the Same Time!)  
About Those Icons  
Key to Difficulty Icons  
Key to “How Much Excel” Icons  
Little Chapter 1a. All You Need to Know About Formulas and Functions  
What’s a Formula?  
What’s a Function?  
Little Chapter 1b. All You Need to Know About Using the Amazing Analysis ToolPak  
A Look at the Analysis ToolPak  
Don’t Have It?  
Little Chapter 1c. Mac Lovers Rejoice! StatPlus: The Mac Alternative to the Analysis ToolPak  
Little Chapter 1c. For Mac Lovers Who are Still using Version 2011: Rejoice!! And, for Mac Lovers Who are new to Version 2016, Rejoice More!!!  
Part II: Sigma Freud and Descriptive Statistics
Chapter 2: Computing and Understanding Averages: Means to an End
Computing the Mean  
Computing a Weighted Mean  
Computing the Median  
Computing the Mode  
Using the Amazing Analysis ToolPak to Compute Descriptive Statistics  
When to Use What  
Chapter 3: Vive la Différence: Understanding Variability
Why Understanding Variability Is Important  
Computing the Range  
Computing the Standard Deviation  
Computing the Variance  
And Now... Using Excel’s VAR.S Function  
The Standard Deviation Versus the Variance  
Using the Amazing Analysis ToolPak (Again!)  
Chapter 4: A Picture Really Is Worth a Thousand Words
Why Illustrate Data?  
Ten Ways to a Great Figure (Eat Less and Exercise More?)  
First Things First: Creating a Frequency Distribution  
The Plot Thickens: Creating a Histogram  
Fat and Skinny Frequency Distributions  
Excellent Charts  
Excellent Charts Part Deux: Making Charts Pretty  
Other Cool Charts  
Chapter 5: Ice Cream and Crime: Computing Correlation Coefficients
What Are Correlations All About?  
Computing a Simple Correlation Coefficient  
More Excel—Bunches of Correlations à la Excel  
Using the Amazing Analysis ToolPak to Compute Correlations  
Understanding What the Correlation Coefficient Means  
As More Ice Cream Is Eaten... the Crime Rate Goes Up (or Association Versus Causality)  
Other Cool Correlations  
Chapter 6: Just the Truth: An Introduction to Understanding Reliability and Validity
An Introduction to Reliability and Validity  
All About Measurement Scales  
Reliability—Doing It Again Until You Get It Right  
Validity—Whoa! What Is the Truth?  
A Last, Friendly Word  
Validity and Reliability: Really Close Cousins  
Part III: Taking Chances for Fun and Profit
Chapter 7: Hypotheticals and You: Testing Your Questions
So You Want to Be a Scientist...  
The Null Hypothesis  
The Research Hypothesis  
What Makes a Good Hypothesis?  
Chapter 8: Are Your Curves Normal? Probability and Why It Counts
Why Probability?  
The Normal Curve (aka the Bell-Shaped Curve)  
Our Favorite Standard Score: The z Score  
Part IV: Significantly Different: Using Inferential Statistics
Chapter 9: Significantly Significant: What It Means for You and Me
The Concept of Significance  
Significance Versus Meaningfulness  
An Introduction to Inferential Statistics  
An Introduction to Tests of Significance  
An Introduction to Tests of Significance  
Chapter 10: Only the Lonely: The One-Sample Z-Test
Introduction to the One-Sample Z-Test  
Computing the Test Statistic  
Using the Excel Z.TEST Function to Compute the z Value  
Chapter 11: t(ea) for Two: Tests Between the Means of Different Groups
Introduction to the t-Test for Independent Samples  
Computing the Test Statistic  
Using the Amazing Analysis ToolPak to Compute the t Value  
Special Effects: Are Those Differences for Real?  
Chapter 12: t(ea) for Two (Again): Tests Between the Means of Related Groups
Introduction to the t-Test for Dependent Samples  
Computing the Test Statistic  
Using the Amazing Analysis ToolPak to Compute the t Value  
Chapter 13: Two Groups Too Many? Try Analysis of Variance
Introduction to Analysis of Variance  
Computing the F-Test Statistic  
Using the Amazing Analysis ToolPak to Compute the F Value  
Chapter 14: Two Too Many Factors: Factorial Analysis of Variance—A Brief Introduction
Introduction to Factorial Analysis of Variance  
The Main Event: Main Effects in Factorial ANOVA  
Even More Interesting: Interaction Effects  
Computing the ANOVA F Statistic Using the Amazing Analysis ToolPak  
Chapter 15: Cousins or Just Good Friends? Testing Relationships Using the Correlation Coefficient
Introduction to Testing the Correlation Coefficient  
Computing the Test Statistic  
Chapter 16: Predicting Who’ll Win the Super Bowl: Using Linear Regression
What Is Prediction All About?  
The Logic of Prediction  
Drawing the World’s Best Line (for Your Data)  
Computing the Regression Equation Using the Amazing Analysis ToolPak  
How Good Is Our Prediction?  
The More Predictors, the Better? Maybe  
Chapter 17: What to Do When You’re Not Normal: Chi-Square and Some Other Nonparametric Tests
Introduction to Nonparametric Statistics  
Introduction to One-Sample Chi-Square  
Computing the Chi-Square Test Statistic  
Other Nonparametric Tests You Should Know About  
Chapter 18: Some Other (Important) Statistical Procedures You Should Know About
Post Hoc Comparisons  
Multivariate Analysis of Variance  
Repeated Measures Analysis of Variance  
Analysis of Covariance  
Multiple Regression  
Logistic Regression  
Factor Analysis  
Data Mining  
Path Analysis  
Structural Equation Modeling  
Chapter 19: A Statistical Software Sampler
Selecting the Perfect Statistics Software  
What’s Out There  
Chapter 20: (Mini) Data Mining: A Introduction to Getting The Most Out Of Your BIG Data
Part V: Ten Things You’ll Want to Know and Remember
Chapter 21: The Ten (or More) Best (and Most Fun) Internet Sites for Statistics Stuff
How About Studying Statistics in Stockholm?  
Calculators Galore!  
Who’s Who and What’s Happened  
It’s All Here  
Data? You Want Data?  
More and More Resources  
Plain, But Fun  
Online Statistical Teaching Materials  
And, of Course, YouTube...  
Chapter 22: The Ten Commandments of Data Collection
Appendix A: Excel-erate Your Learning: All You Need to Know About Excel
Appendix B: Tables
Appendix C: Data Sets
Appendix D: Answers to Practice Questions
Appendix E: Math – Just the Basics
Appendix F: The Reward: The Brownie Recipe


Instructor Resource Site

SAGE edge for Instructors supports teaching by making it easy to integrate quality content and create a rich learning environment for students.

  • Test banks provide a diverse range of pre-written options as well as the opportunity to edit any question and/or insert personalized questions to effectively assess students’ progress and understanding
  • Editable, chapter-specific PowerPoint® slides offer complete flexibility for creating a multimedia presentation for the course
  • Lecture notes summarize key concepts by chapter to ease preparation for lectures and class discussions
  • Sample course syllabi for semester and quarter courses provide suggested models for structuring one’s course
  • Chapter-specific discussion questions help launch classroom interaction by prompting students to engage with the material and by reinforcing important content.  
  • Lively and stimulating ideas for class activities that can be used in class to reinforce active learning. The activities apply to individual or group projects.
  • EXCLUSIVE! Access to full-text SAGE journal articles have been carefully selected to support and expand on the concepts presented in each chapter to encourage students to think critically
  • Multimedia content includes original SAGE videos that appeal to students with different learning styles
  • A Course cartridge with bonus quizzes provides easy LMS integration
Student Resource Site

SAGE edge for Students provides a personalized approach to help students accomplish their coursework goals in an easy-to-use learning environment.

  • A complete online action plan allows you to track your progress and enhance your learning experience
  • Learning objectives reinforce the most important material
  • Mobile-friendly eFlashcards strengthen understanding of key terms and concepts
  • Mobile-friendly practice quizzes allow for independent assessment by students of their mastery of course material
  • Meaningful web and video resources facilitate further exploration of topics, and responses to critical thinking questions
  • EXCLUSIVE! Access to full-text SAGE journal articles that have been carefully selected to support and expand on the concepts presented in each chapter 
  • Data files allow you to follow along with the exercises in the book

Clearly explains statistical tests in a straight forward manner, making stats more accessible to undergraduate students. I have been separately integrating Excel into the class and this accomplishes both goals with only one required text.

Professor Rebecka Bloomer
Kent School of Social Work, University Of Louisville
July 26, 2018

This book is accessible and an easy to read for students research training. Readable and easy to follow.

Dr Jay Vickers
Health, The University of Worcester
April 12, 2018

This book is amazing-I used it as a student and I'm now happy to pass the new edition on to my students.

Dr Amber L Cushing
School of Info. & Library Studies SILS, University College Dublin
October 23, 2016

This title gives hope to the students that struggle with statistics, however I could not use it for my introductory to Research Methods course. The amount of time consumed in learning to do research, lit reviews, etc, did not allow for the inclusion for this text. However, I see it as the first I would consider for my Advanced Research course.
My lack of adopting this as a text was not related to the quality of the text. I have requested that our campus library also purchase some copies of this item. I would highly recommend for a stats course or an advanced research methods course.

Dr Michael Sturgeon
Communication Arts Dept, Lee University
September 3, 2016

Well organized for statistics. Author uses command language and humor to teach

Mr Robert McDaniels
Emergency Medicine Dept, Univ Of New Mexico Sch Of Med
August 23, 2016
Key features


  • A new Chapter 20 includes an introduction to working with large datasets using Excel functions and pivot tables.
  • New chapter-ending exercises are included and contain a variety of levels of application.
  • Additional TechTalks have been added.
  • A new, chapter-ending Real World Stats feature shows readers how statistics is applied in the everyday world.
  • The answers to Time to Practice questions are now in a separate appendix (Appendix D).
  • A new Appendix E presents basic math instruction and practice exercises for those who need to brush up on their math skills.


  • Complete coverage of the Excel Data Analysis tools shows readers how they can be used for descriptive statistics, graphical representation of data, correlation, regression, and more.
  • Discussions of important topics, such as the normal curve, inference, and the central limit theorem—and their importance—help students master key concepts and skills.
  • Instructions on using Excel formulae to compute reliability estimates, Chi-square values, and other non-parametric procedures prepare students to use the software when analyzing their own work.
  • Icons, tip boxes, further readings, and the famous Difficulty Rating Scale and Top Ten lists help students put concepts into practice.
  • Answers to exercises at the back of the book (with page references) make it easy for students to check their analyses and then quickly refer to the specific information they need to review. 

Sample Materials & Chapters

Chapter 1

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