Even You Can Learn Statistics

David M. Levine, a much-honored innovator in statistics education, is Professor Emeritus of Statistics and Computer Information Systems at Baruch College (CUNY). His bestselling books include Statistics for Managers Using Microsoft Excel, Basic Business Statistics, Business Statistics: A First Course, Statistics for Six Sigma Green Belts with Minitab and JMP, Six Sigma for Green Belts and Champions, and Design for Six Sigma for Green Belts and Champions.     David F. Stephan is an independent instructional technologist. As a computer information systems instructor at Baruch College (CUNY), he pioneered the use of computers in classrooms, devised interdisciplinary multimedia tools, and created techniques for teaching computer applications in a business context. The developer of PHStat2, the Pearson Education statistics add-in system for Microsoft Excel, he has coauthored several books with David M. Levine.

Acknowledgments. . . . . viii

About the Authors . . . . . ix

Introduction The Even You Can Learn Statistics Owners Manual. . . . xi

Chapter 1 Fundamentals of Statistics . . . . . 1

1.1 The First Three Words of Statistics. . . . . . . 2

1.2 The Fourth and Fifth Words . . . . 4

1.3 The Branches of Statistics . . . . . 5

1.4 Sources of Data . . . . . 6

1.5 Sampling Concepts . . . . 7

1.6 Sample Selection Methods. . . . . 9

Chapter 2 Presenting Data in Charts and Tables. . . . . 19

2.1 Presenting Categorical Variables. . . . . . 19

2.2 Presenting Numerical Variables. . . . .. 26

2.3 Misusing Charts. . . . . 32

Chapter 3 Descriptive Statistics . . . . 43

3.1 Measures of Central Tendency . . . . 43

3.2 Measures of Position. . . . . 47

3.3 Measures of Variation. . . . . . 51

3.4 Shape of Distributions . . . . . 57

Chapter 4 Probability . . . . . . 71

4.1 Events. . . . . . 71

4.2 More Definitions . . . . . . 72

4.3 Some Rules of Probability . . . . . 74

4.4 Assigning Probabilities . . . . 77

Chapter 5 Probability Distributions . . . . 83

5.1 Probability Distributions for Discrete Variables . . .. . 83

5.2 The Binomial and Poisson Probability Distributions. . . . 89

5.3 Continuous Probability Distributions and the Normal Distribution . . . 97

5.4 The Normal Probability Plot. . . . . 105

Chapter 6 Sampling Distributions and Confidence Intervals . . . . 119

6.1 Sampling Distributions. . . . . . . 119

6.2 Sampling Error and Confidence Intervals. . . . . . 123

6.3 Confidence Interval Estimate for the Mean Using the t Distribution (ó Unknown) . . . . . 127

6.4 Confidence Interval Estimation for Categorical Variables. .. . . 131

Chapter 7 Fundamentals of Hypothesis Testing . . . 141

7.1 The Null and Alternative Hypotheses. . . . . . 141

7.2 Hypothesis Testing Issues . . . . . 143

7.3 Decision-Making Risks . . . . . . . 145

7.4 Performing Hypothesis Testing . . . . . 147

7.5 Types of Hypothesis Tests . . . . 148

Chapter 8 Hypothesis Testing: Z and t Tests . . . . 153

8.1 Testing for the Difference Between Two Proportions. . . . . . 153

8.2 Testing for the Difference Between the Means of Two Independent Groups .. . . . . . 160

8.3 The Paired t Test . . . . . 166

Chapter 9 Hypothesis Testing: Chi-Square Tests and the One-Way Analysis of Variance (ANOVA). . . . . .179

9.1 Chi-Square Test for Two-Way Cross-Classification Tables . . . . . 179

9.2 One-Way Analysis of Variance (ANOVA): Testing for the Differences Among the Means of More Than Two Groups . . . . 186

Chapter 10 Simple Linear Regression . . . . . ..207

10.1 Basics of Regression Analysis . . . . . . . 208

10.2 Determining the Simple Linear Regression Equation . . . . . . 209

10.3 Measures of Variation . . . . . . 217

10.4 Regression Assumptions. . . . . . . . . 222

10.5 Residual Analysis. . . . . . .223

10.6 Inferences About the Slope. . . . . 225

10.7 Common Mistakes Using Regression Analysis . . . . . 228

Chapter 11 Multiple Regression . . . . . ..245

11.1 The Multiple Regression Model . . . . . 245

11.2 Coefficient of Multiple Determination. . . . . . 248

11.3 The Overall F test. . . . . . . 249

11.4 Residual Analysis for the Multiple Regression Model . . . . . . 250

11.5 Inferences Concerning the Population Regression Coefficients . . . . 251

Chapter 12 Quality and Six Sigma Applications of Statistics . . . . 265

12.1 Total Quality Management . . . . . 265

12.2 Six Sigma. . . . . . . 267

12.3 Control Charts . . . . . 268

12.4 The p Chart. . . . . . .271

12.5 The Parable of the Red Bead Experiment: Understanding Process Variability . . . . . . . . 276

12.6 Variables Control Charts for the Mean and Range . . . . . 278

Appendix A Calculator and Spreadsheet Operation and Configuration . . . . ..295

A.C1 Calculator Operation Conventions ...... 295

A.C2 Calculator Technical Configuration ...... 297

A.C3 Using the A2MULREG Program ...... 298

A.C4 Using TI Connect ...... 298

A.S1 Spreadsheet Operation Conventions ..... 299

A.S2 Spreadsheet Technical Configurations..... 299

Appendix B Review of Arithmetic and Algebra . . . . .301

Assessment Quiz . . . . . . 301

Symbols. . . . . 304

Answers to Quiz. . . . . . . 310

Appendix C Statistical Tables . . . 311

Appendix D Spreadsheet Tips. . . . . . ..339

CT: Chart Tips . . . . . 339

FT: Function Tips . . . . .341

ATT: Analysis ToolPak Tips (Microsoft Excel only). . . . .343

Appendix E Advanced Techniques. . . . . . 347

E.1 Using PivotTables to Create Two-Way Cross-Classification Tables . . . . 347

E.2 Using the FREQUENCY Function to Create Frequency Distributions. . . . . . . 349

E.3 Calculating Quartiles . . . . . . 350

E.4 Using the LINEST Function to Calculate Regression Results. . . . . 351

Appendix F Documentation for Downloadable Files . . . . 353

F.1 Downloadable Data Files . . . . . . 353

F.2 Downloadable Spreadsheet Solution Files. . . . . . 357

Glossary . . . . ..359

Index . . . . .367