Statistics for people who (think they) hate statistics / Neil J. Salkind.

Format:

Book

Author/Creator:

Salkind, Neil J.

Contributor:

Class of 1953 Fund.

Language:

English

Subjects (All):

Statistics.

Microsoft Excel (Computer file).

Physical Description:

xviii, 403 pages : illustrations ; 26 cm

Edition:

Excel edition.

Place of Publication:

Thousand Oaks : SAGE Publications, [2007]

Summary:

Based on the bestselling text Statistics for People Who (Think They) Hate Statistics, The Excel Edition offers the same personable and clear style that made the original text so successful. In this new edition, author Neil J. Salkind gives students the critical tools that they need to use Excel, while learning the basics of statistics in their first or second course. While this text is not solely a guide to using Excel, it does offer greater utility to students embarking on professional careers in which they are likely to use this program as a statistical tool.

Key Features: Applies Excel to statistical techniques: Introductory chapters present Excel as an accessible tool for statistical analyses. Students learn how to install the free Excel Analysis ToolPak to gain access to a host of new and very useful analytical techniques, such as ANOVA, correlation, covariance, moving averages, regression, and more. In addition, other Excel formulae illustrate reliability, goodness-of-fit, and Chi-square. Presents concepts and techniques in an unhurried pace: Using a nonintimidating, user-friendly style, this book walks students through various statistical procedures, beginning with correlations and graphical representation of data and ending with inferential techniques and analysis of variance. Real-world examples from a variety of settings illustrate the utility of statistics and reinforce concepts introduced. Provides valuable teaching tools: Pedagogical features help present an often intimidating and difficult subject in a way that is informative, engaging, and clear. These tools include icons, tip boxes, further readings, a glossary, the famous "Difficulty Rating Scale" and "Top Ten" lists, and much more. In addition, an extensive Excel functionality is located at the back of the book.

Contents:

A Note to the Student Why I Wrote this Book xvi

Part 1 Yippee! I'm in Statistics 1

1 Statistics or Sadistics? It's Up to You 5

Why Statistics? 5

And Why Excel? 6

A Five-Minute History of Statistics 6

Statistics: What It Is (and Isn't) 8

What Are Descriptive Statistics? 9

What Are Inferential Statistics? 9

In Other Words... 10

Tooling Around With the Analysis ToolPak 11

What Am I Doing in a Statistics Class? 11

Ten Ways to Use This Book (and Learn Statistics at the Same Time!) 13

About Those Icons 15

Key to Difficulty Icons 16

Key to "How Much Excel" Icons 17

Time to Practice 17

1a All You Need to Know About Formulas and Functions 19

What's a Formula? 19

Creating a Formula 20

Operator, Operator-Get Me a Formula! 22

Beware the Parentheses 22

What's a Function? 23

Using a Function 24

Using Functions in Formulas 29

We're Taking Names: Naming Ranges 30

Using Ranges 31

Time to Practice 32

1b All You Need to Know About Using the Amazing Data Analysis ToolPak 35

A Look at a Data Analysis Tool 36

Don't Have It? 37

Part II [Sigma]igma Freud and Descriptive Statistics 39

2 Computing and Understanding Averages: Means to an End 41

Computing the Mean 42

And Now...Using Excel's AVERAGE Function 43

Things to Remember 45

Computing a Weighted Mean 46

Computing the Median 48

And Now...Using Excel's MEDIAN Function 50

Things to Remember 53

Computing the Mode 53

And Now...Using Excel's MODE Function 54

Apple Pie a la Bimodal 56

Using the Amazing Analysis ToolPak to Compute Descriptive Statistics 56

Make the Analysis ToolPak Output Pretty 60

When to Use What 61

Time to Practice 62

3 Vive la Difference: Understanding Variability 66

Why Understanding Variability Is Important 66

Computing the Range 67

Computing the Standard Deviation 68

And Now...Using Excel's STDEV Function 70

Why n - 1? What's Wrong With Just n? 73

What's the Big Deal? 74

Things to Remember 75

Computing the Variance 75

And Now...Using Excel's VAR Function 76

The Standard Deviation Versus the Variance 77

Using the Amazing Analysis ToolPak (AGAIN!) 78

Time to Practice 78

4 A Picture Really Is Worth a Thousand Words 82

Why Illustrate Data? 82

Ten Ways to a Great Figure (Eat Less and Exercise More?) 83

First Things First: Creating a Frequency Distribution 84

The Classiest of Intervals 85

The Plot Thickens: Creating a Histogram 86

The Tally-Ho Method 88

Using the Amazing Analysis ToolPak to Create a Histogram 89

The Next Step: A Frequency Polygon 93

Cumulating Frequencies 94

Fat and Skinny Frequency Distributions 96

Average Value 96

Variability 96

Skewness 97

Kurtosis 98

Excellent Charts 100

Your First Excel Chart: A Moment to Remember 101

Excellent Charts Part Deux: Making Charts Pretty 104

Other Cool Charts 105

Bar Charts 106

Line Charts 106

Pie Charts 107

Time to Practice 108

5 Ice Cream and Crime: Computing Correlation Coefficients 110

What Are Correlations All About? 110

Types of Correlation Coefficients: Flavor 1 and Flavor 2 111

Things to Remember 112

Computing a Simple Correlation Coefficient 114

And Now...Using Excel's CORREL Function 116

A Visual Picture of a Correlation: The Scatterplot 117

Using Excel to Create a Scatterplot 121

Bunches of Correlations: The Correlation Matrix 122

More Excel-Bunches of Correlations a la Excel 123

Using the Amazing Analysis ToolPak to Compute Correlations 124

Understanding What the Correlation Coefficient Means 126

Using-Your-Thumb Rule 126

A Determined Effort: Squaring the Correlation Coefficient 127

As More Ice Cream Is Eaten...the Crime Rate Goes Up (or Association Versus Causality) 129

Other Cool Correlations 130

Time to Practice 132

Part III Taking Chances for Fun and Profit 135

6 Hypotheticals and You: Testing Your Questions 137

So You Want to Be a Scientist... 137

Samples and Populations 138

The Null Hypothesis 139

The Purposes of the Null Hypothesis 140

The Research Hypothesis 141

The Nondirectional Research Hypothesis 142

The Directional Research Hypothesis 143

Some Differences Between the Null Hypothesis and the Research Hypothesis 145

What Makes a Good Hypothesis? 146

Time to Practice 149

7 Are Your Curves Normal? Probability and Why It Counts 151

Why Probability? 151

The Normal Curve (a.k.a. the Bell-Shaped Curve) 152

Hey, That's Not Normal! 153

More Normal Curve 101 155

Our Favorite Standard Score: The z Score 159

Using Excel to Compute z Scores 161

What z Scores Represent 164

What z Scores Really Represent 168

Hypothesis Testing and z Scores: The First Step 169

Time to Practice 170

Part IV Significantly Different: Using Inferential Statistics 173

8 Significantly Significant: What It Means for You and Me 175

The Concept of Significance 175

If Only We Were Perfect 176

The World's Most Important Table (for This Semester Only) 178

More About Table 8.1 179

Back to Type I Errors 180

Significance Versus Meaningfulness 182

An Introduction to Inferential Statistics 184

How Inference Works 184

How to Select What Test to Use 185

Here's How to Use the Chart 187

An Introduction to Tests of Significance 187

How a Test of Significance Works: The Plan 188

Here's the Picture That's Worth a Thousand Words 189

Time to Practice 191

9 t(ea) for Two: Tests Between the Means of Different Groups 192

Introduction to the t Test for Independent Samples 192

The Path to Wisdom and Knowledge 193

Computing the Test Statistic 195

So How Do I Interpret t[subscript (58)] = -.14, p > .05? 199

And Now...Using Excel's TTEST Function 200

Using the Amazing Data Analysis ToolPak to Compute the t Value 202

Special Effects: Are Those Differences for Real? 205

Computing and Understanding the Effect Size 206

A Very Cool Effect Size Calculator 208

Time to Practice 209

10 t(ea) for Two (Again): Tests Between the Means of Related Groups 211

Introduction to the t Test for Dependent Samples 211

The Path to Wisdom and Knowledge 212

Computing the Test Statistic 214

So How Do I Interpret t[subscript (24)] = 2.45, p < .05? 217

And Now...Using Excel's TTEST Function 218

Using the Amazing Data Analysis ToolPak to Compute the t Value 220

Time to Practice 223

11 Two Groups Too Many? Try Analysis of Variance 225

Introduction to Analysis of Variance 225

The Path to Wisdom and Knowledge 226

Different Flavors of ANOVA 226

Computing the F Test Statistic 229

So How Do I Interpret F[subscript (2, 27)] = 8.80, p < .05? 236

And Now...Using Excel's FDIST and FTEST Functions 237

Using the Amazing Data Analysis ToolPak to Compute the F Value 237

Time to Practice 240

12 Two Too Many Factors: Factorial Analysis of Variance: A Brief Introduction 244

Introduction to Factorial Analysis of Variance 244

Two Flavors of Factorial ANOVA 245

The Path to Wisdom and Knowledge 246

A New Flavor of ANOVA 247

The Main Event: Main Effects in Factorial ANOVA 249

Even More Interesting: Interaction Effects 251

Computing the ANOVA F Statistic Using the Amazing Data Analysis ToolPak 253

Time to Practice 257

13 Cousins or Just Good Friends? Testing Relationships Using the Correlation Coefficient 259

Introduction to Testing the Correlation Coefficient 259

The Path to Wisdom and Knowledge 260

Computing the Test Statistic 260

So How Do I Interpret r[subscript (27)] = .393, p < .05? 265

Causes and Associations (Again!) 266

Significance Versus Meaningfulness (Again, Again!) 267

Time to Practice 267

14 Predicting Who'll Win the Super Bowl: Using Linear Regression 270

What Is Prediction All About? 270

The Logic of Prediction 271

Drawing the World's Best Line (for Your Data) 275

And Now...Using Excel's SLOPE Function 278

And Now...Using Excel's INTERCEPT Function 280

How Good Is

Our Prediction? 283

The More Predictors the Better? Maybe 284

The Big Rule When It Comes to Using Multiple Predictor Variables 285

Time to Practice 286

15 What to Do When You're Not Normal: Chi-Square and Some Other Nonparametric Tests 289

Introduction to Nonparametric Statistics 289

Introduction to One-Sample Chi-Square 290

Computing the Chi-Square Test Statistic 291

So How Do I Interpret [Characters not reproducible] = 20.6, p < .05? 295

And Now...Using Excel's CHIDIST Function 295

Other Nonparametric Tests You Should Know About 296

Time to Practice 298

16 Just the Truth: An Introduction to Understanding Reliability and Validity 300

An Introduction to Reliability and Validity 300

What's Up With This Measurement Stuff? 301

All About Measurement Scales 302

A Rose by Any Other Name: The Nominal Level of Measurement 303

Any Order Is Fine With Me: The Ordinal Level of Measurement 303

1 + 1 = 2: The Interval Level of Measurement 303

Can Anyone Have Nothing of Anything? The Ratio Level of Measurement 304

In Sum... 304

Reliability-Doing It Again Until You Get It Right 305

Test Scores-Truth or Dare 305

Observed Score = True Score + Error Score 306

Different Types of Reliability 307

How Big Is Big? Interpreting Reliability Coefficients 313

Just One More Thing 314

Validity-Whoa! What Is the Truth? 314

Different Types of Validity 315

A Last, Friendly Word 318

Validity and Reliability: Really Close Cousins 319

Time to Practice 320

17 Some Other (Important) Statistical Procedures You Should Know About 321

Multivariate Analysis of Variance 321

Repeated Measures Analysis of Variance 322

Analysis of Covariance 323

Multiple Regression 323

Factor Analysis 324

Path Analysis 325

Structural Equation Modeling 325

18 A Statistical Software Sampler 327

Selecting the Perfect Statistics Software 328

What's Out There 329

The Free Stuff 330

Time to Pay 332

Part V Ten Things You'll Want to Know and Remember 337

19 The Ten (or More) Best Internet Sites for Statistics Stuff 339

Tons and Tons of Resources 339

Calculators Galore! 340

Who's Who and What's Happened 341

It's All Here 341

HyperStat 341

Data? You Want Data? 342

More and More and More and More Resources 343

Plain, But Fun 343

How About Studying Statistics in Stockholm? 343

Online Statistical Teaching Materials 344

More and More and More Stuff 344

20 The Ten Commandments of Data Collection 345

Appendix A Excel-erate Your Learning: All You Need to Know About Excel 350

Appendix C The Data Sets 371.

Notes:

This edition shows the students how to install the Excel Analysis ToolPak option (free) to earn access to a host of new and very useful analytical techniques.

Includes bibliographical references and index.

Local Notes:

Acquired for the Penn Libraries with assistance from the Class of 1953 Fund.

ISBN:

1412924812

9781412924818

1412924820

9781412924825

OCLC:

63808129

Online:

Publisher description