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Statistics for Business and Economics

by: Anderson,David R.

Statistics for Business and Economics

by: Anderson,David R.

ISBN 13:
9780324200829
ISBN 10:
032420082X
Edition: CD
Format: Hardcover
Copyright: 01/06/2004
Publisher: Cengage Learning
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Summary

This market leading book offers a proven, comprehensive, applications-oriented approach. Written by authors who are highly regarded in the field, the text provides sound methodological development. The discussion and development of each technique is presented in an application setting, with the statistical results providing insights to decisions and solutions to problems.

Preface

xxi

About the Authors

xxvii

Chapter 1 Data and Statistics

(22)

Statistics in Practice: Business Week

(1)

1.1 Applications in Business and Economics

(2)

Accounting

(1)

Finance

(1)

Marketing

(1)

Production

(1)

Economics

(1)

1.2 Data

(3)

Elements, Variables, and Observations

(1)

Scales of Measurement

(1)

Qualitative and Quantitative Data

(1)

Cross-Sectional and Time Series Data

(1)

1.3 Data Sources 8 Existing Sources

(4)

Statistical Studies

(3)

Data Acquisition Errors

(1)

1.4 Descriptive Statistics

(2)

1.5 Statistical Inference

(2)

1.6 Computers and Statistical Analysis

(1)

Summary

(1)

Glossary

(1)

Exercises

(6)

Chapter 2 Descriptive Statistics: Tabular and Graphical Presentations

(53)

Statistics in Practice: Colgate-Palmolive Company

(1)

2.1 Summarizing Qualitative Data

(6)

Frequency Distribution

(1)

Relative Frequency and Percent Frequency Distributions

(1)

Bar Graphs and Pie Charts

(5)

2.2 Summarizing Quantitative Data

(9)

Frequency Distribution

(1)

Relative Frequency and Percent Frequency Distributions

(1)

Dot Plot

(1)

Histogram

(1)

Cumulative Distributions

(2)

Ogive

(4)

2.3 Exploratory Data Analysis: The Stein-and-Leaf Display

(5)

2.4 Crosstabulations and Scatter Diagrams

(9)

Crosstabulation

(2)

Simpson's Paradox

(2)

Scatter Diagram and Trendline

(5)

Summary

(2)

Glossary

(1)

Key Formulas

(1)

Supplementary Exercises

(6)

Case Problem Pelican Stores

(1)

Appendix 2.1 Using Minitab for Tabular and Graphical Presentations

(2)

Appendix 2.2 Using Excel for Tabular and Graphical Presentations

(10)

Chapter 3 Descriptive Statistics: Numerical Measures

(63)

Statistics in Practice: Small Fry Design

(1)

3.1 Measures of Location

(9)

Mean

(1)

Median

(1)

Mode

(1)

Percentiles

(1)

Quartiles

(5)

3.2 Measures of Variability

(7)

Range

(1)

Interquartile Range

(1)

Variance

(2)

Standard Deviation

(1)

Coefficient of Variation

(3)

3.3 Measures of Distribution Shape, Relative Location, and Detecting

Outliers

(1)

Distribution Shape

(1)

z-Scores

(2)

Chebyshev's Theorem

(1)

Empirical Rule

(1)

Detecting Outliers

(3)

3.4 Exploratory Data Analysis

101

(4)

Five-Number Summary

101

(1)

Box Plot

102

(3)

3.5 Measures of Association Between Two Variables

105

(9)

Covariance

106

(1)

Interpretation of the Covariance

107

(3)

Correlation Coefficient

110

(1)

Interpretation of the Correlation Coefficient

111

(3)

3.6 The Weighted Mean and Working with Grouped Data

114

(6)

Weighted Mean

115

(1)

Grouped Data

116

(4)

Summary

120

(1)

Glossary

121

(1)

Key Formulas

122

(2)

Supplementary Exercises

124

(5)

Case Problem 1 Pelican Stores

129

(1)

Case Problem 2 National Health Care Association

130

(1)

Case Problem 3 Business Schools of Asia-Pacific

131

(2)

Appendix 3.1 Descriptive Statistics Using Minitab

133

(2)

Appendix 3.2 Descriptive Statistics Using Excel

135

(4)

Chapter 4 Introduction to Probability

139

(45)

Statistics in Practice: Morton International

140

(1)

4.1 Experiments, Counting Rules, and Assigning Probabilities

141

(10)

Counting Rules, Combinations, and Permutations

142

(4)

Assigning Probabilities

146

(2)

Probabilities for the KP&L Project

148

(3)

4.2 Events and Their Probabilities

151

(4)

4.3 Some Basic Relationships of Probability

155

(6)

Complement of an Event

155

(1)

Addition Law

156

(5)

4.4 Conditional Probability

161

(8)

Independent Events

165

(1)

Multiplication Law

165

(4)

4.5 Bayes' Theorem

169

(6)

Tabular Approach

173

(2)

Summary

175

(1)

Glossary

175

(1)

Key Formulas

176

(1)

Supplementary Exercises

177

(4)

Case Problem Hamilton County Judges

181

(3)

Chapter 5 Discrete Probability Distributions

184

(39)

Statistics in Practice: Citibank

185

(1)

5.1 Random Variables

185

(3)

Discrete Random Variables

186

(1)

Continuous Random Variables

187

(1)

5.2 Discrete Probability Distributions

188

(6)

5.3 Expected Value and Variance

194

(4)

Expected Value

194

(1)

Variance

194

(4)

5.4 Binomial Probability Distribution

198

(10)

A Binomial Experiment

199

(1)

Martin Clothing Store Problem

200

(4)

Using Tables of Binomial Probabilities

204

(1)

Expected Value and Variance for the Binomial Distribution

205

(3)

5.5 Poisson Probability Distribution

208

(4)

An Example Involving Time Intervals

209

(2)

An Example Involving Length or Distance Intervals

211

(1)

5.6 Hypergeometric Probability Distribution

212

(3)

Summary

215

(1)

Glossary

216

(1)

Key Formulas

217

(1)

Supplementary Exercises

218

(2)

Appendix 5.1 Discrete Probability Distributions with Minitab

220

(1)

Appendix 5.2 Discrete Probability Distributions with Excel

221

(2)

Chapter 6 Continuous Probability Distributions

223

(34)

Statistics in Practice: Procter & Gamble

224

(1)

6.1 Uniform Probability Distribution

225

(4)

Area as a Measure of Probability

226

(3)

6.2 Normal Probability Distribution

229

(14)

Normal Curve

229

(2)

Standard Normal Probability Distribution

231

(6)

Computing Probabilities for Any Normal Distribution

237

(1)

Grear Tire Company Problem

238

(5)

6.3 Normal Approximation of Binomial Probabilities

243

(3)

6.4 Exponential Probability Distribution

246

(4)

Computing Probabilities for the Exponential Distribution

246

(2)

Relationship Between the Poisson and Exponential Distributions

248

(2)

Summary

250

(1)

Glossary

250

(1)

Key Formulas

250

(1)

Supplementary Exercises

251

(3)

Case Problem Specialty Toys

254

(1)

Appendix 6.1 Continuous Probability Distributions with Minitab

255

(1)

Appendix 6.2 Continuous Probability Distributions with Excel

256

(1)

Chapter 7 Sampling and Sampling Distributions

257

(40)

Statistics in Practice: MeadWestvaco Corporation

258

(1)

7.1 The Electronics Associates Sampling Problem

259

(1)

7.2 Simple Random Sampling

260

(4)

Sampling from a Finite Population

260

(1)

Sampling from an Infinite Population

261

(3)

7.3 Point Estimation

264

(3)

7.4 Introduction to Sampling Distributions

267

(3)

7.5 Sampling Distribution of x

270

(9)

Expected Value of x

270

(1)

Standard Deviation of x

271

(1)

Form of the Sampling Distribution of x

272

(1)

Sampling Distribution of x for the EAI Problem

273

(1)

Practical Value of the Sampling Distribution of x

274

(1)

Relationship Between the Sample Size and the Sampling Distribution of x

275

(4)

7.6 Sampling Distribution of p

279

(5)

Expected Value of p

280

(1)

Standard Deviation of p

280

(1)

Form of the Sampling Distribution of p

281

(1)

Practical Value of the Sampling Distribution of p

281

(3)

7.7 Properties of Point Estimators

284

(3)

Unbiased

285

(1)

Efficiency

286

(1)

Consistency

287

(1)

7.8 Other Sampling Methods

287

(3)

Stratified Random Sampling

287

(1)

Cluster Sampling

288

(1)

Systematic Sampling

288

(1)

Convenience Sampling

289

(1)

Judgment Sampling

289

(1)

Summary

290

(1)

Glossary

290

(1)

Key Formulas

291

(1)

Supplementary Exercises

292

(2)

Appendix 7.1 The Expected Value and Standard Deviation of x

294

(1)

Appendix 7.2 Random Sampling with Minitab

295

(1)

Appendix 7.3 Random Sampling with Excel

296

(1)

Chapter 8 Interval Estimation

297

(39)

Statistics in Practice: Food Lion

298

(1)

8.1 Population Mean: σ Known

299

(6)

Margin of Error and the Interval Estimate

300

(3)

Practical Advice

303

(2)

8.2 Population Mean: σ Unknown

305

(9)

Margin of Error and the Interval Estimate

306

(3)

Practical Advice

309

(1)

Using a Small Sample

309

(2)

Summary of Interval Estimation Procedures

311

(3)

8.3 Determining the Sample Size

314

(3)

8.4 Population Proportion

317

(5)

Determining the Sample Size

319

(3)

Summary

322

(1)

Glossary

323

(1)

Key Formulas

324

(1)

Supplementary Exercises

324

(3)

Case Problem 1 Bock Investment Services

327

(1)

Case Problem 2 Gulf Real Estate Properties

327

(3)

Case Problem 3 Metropolitan Research, Inc.

330

(1)

Appendix 8.1 Interval Estimation with Minitab

331

(1)

Appendix 8.2 Interval Estimation Using Excel

332

(4)

Chapter 9 Hypothesis Testing

336

(57)

Statistics in Practice: John Morrell & Company

337

(1)

9.1 Developing Null and Alternative Hypotheses

338

(2)

Testing Research Hypotheses

338

(1)

Testing the Validity of a Claim

338

(1)

Testing in Decision-Making Situations

339

(1)

Summary of Forms for Null and Alternative Hypotheses

339

(1)

9.2 Type I and Type II Errors

340

(3)

9.3 Population Mean: σ Known

343

(15)

One-Tailed Test

343

(6)

Two-Tailed Test

349

(3)

Summary and Practical Advice

352

(1)

Relationship Between Interval Estimation and Hypothesis Testing

353

(5)

9.4 Population Mean: σ Unknown

358

(7)

One-Tailed Test

358

(2)

Two-Tailed Test

360

(1)

Summary and Practical Advice

361

(4)

9.5 Population Proportion

365

(5)

Summary

367

(3)

9.6 Hypothesis Testing and Decision Making

370

(1)

9.7 Calculating the Probability of Type II Errors

371

(5)

9.8 Determining the Sample Size for Hypothesis Test About a Population Mean

376

(4)

Summary

380

(1)

Glossary

380

(1)

Key Formulas

381

(1)

Supplementary Exercises

381

(3)

Case Problem 1 Quality Associates, Inc.

384

(1)

Case Problem 2 Unemployment Study

385

(1)

Appendix 9.1 Hypothesis Testing with Minitab

386

(2)

Appendix 9.2 Hypothesis Testing with Excel

388

(5)

Chapter 10 Statistical Inference About Means and Proportions with Two Populations

393

(39)

Statistics in Practice: Fisons Corporation

394

(1)

10.1 Inferences About the Difference Between Two Population Means: σl and σ2, Known

395

(7)

Interval Estimate of μ1-μ2

395

(2)

Hypothesis Tests About μ1-μ2

397

(2)

Practical Advice

399

(3)

10.2 Inferences About the Difference Between Two Population Means: σl and σ2 Unknown

402

(9)

Interval Estimation of μ1-μ2

402

(1)

Hypothesis Tests About μ1-μ2

403

(2)

Practical Advice

405

(6)

10.3 Inferences About the Difference Between Two Population Means: Matched Samples

411

(6)

10.4 Inferences About the Difference Between Two Population Proportions

417

(5)

Interval Estimation of ρ1-ρ2

417

(2)

Hypothesis Tests About μ1-μ2

419

(3)

Summary

422

(1)

Glossary

423

(1)

Key Formulas

423

(2)

Supplementary Exercises

425

(2)

Case Problem Par, Inc.

427

(1)

Appendix 10.1 Inferences About Two Populations Using Minitab

428

(2)

Appendix 10.2 Inferences About Two Populations Using Excel

430

(2)

Chapter 11 Inferences About Population Variances

432

(25)

Statistics in Practice: U.S. General Accounting Office

433

(1)

11.1 Inferences About a Population Variance

434

(9)

Interval Estimation

434

(4)

Hypothesis Testing

438

(5)

11.2 Inferences About Two Population Variances

443

(7)

Summary

450

(1)

Key Formulas

450

(1)

Supplementary Exercises

451

(1)

Case Problem Air Force Training Program

452

(2)

Appendix 11.1 Population Variances with Minitab

454

(1)

Appendix 11.2 Population Variances with Excel

455

(2)

Chapter 12 Tests of Goodness of Fit and Independence

457

(33)

Statistics in Practice: United Way

458

(1)

12.1 Goodness of Fit Test: A Multinomial Population

459

(5)

12.2 Test of Independence

464

(7)

12.3 Goodness of Fit Test: Poisson and Normal Distributions

471

(10)

Poisson Distribution

472

(3)

Normal Distribution

475

(6)

Summary

481

(1)

Glossary

481

(1)

Key Formulas

481

(1)

Supplementary Exercises

482

(3)

Case Problem A Bipartisan Agenda for Change

485

(1)

Appendix 12.1 Tests of Goodness of Fit and Independence Using Minitab

486

(1)

Appendix 12.2 Tests of Goodness of Fit and Independence Using Excel

487

(3)

Chapter 13 Analysis of Variance and Experimental Design

490

(63)

Statistics in Practice: Burke Marketing Services, Inc.

491

(1)

13.1 An Introduction to Analysis of Variance

491

(4)

Assumptions for Analysis of Variance

493

(1)

A Conceptual Overview

493

(2)

13.2 Analysis of Variance: Testing for the Equality of k Population Means

495

(10)

Between-Treatments Estimate of Population Variance

496

(1)

Within-Treatments Estimate of Population Variance

497

(1)

Comparing the Variance Estimates: The F Test

498

(2)

ANOVA Table

500

(1)

Computer Results for Analysis of Variance

500

(5)

13.3 Multiple Comparison Procedures

505

(6)

Fisher's LSD

506

(2)

Type I Error Rates

508

(3)

13.4 An Introduction to Experimental Design

511

(2)

Data Collection

512

(1)

13.5 Completely Randomized Designs

513

(6)

Between-Treatments Estimate of Population Variance

514

(1)

Within-Treatments Estimate of Population Variance

514

(1)

Comparing the Variance Estimates: The F Test 514

ANOVA Table

515

(1)

Pairwise Comparisons

515

(4)

13.6 Randomized Block Design

519

(7)

Air Traffic Controller Stress Test

520

(1)

ANOVA Procedure

521

(1)

Computations and Conclusions

522

(4)

13.7 Factorial Experiments

526

(8)

ANOVA Procedure

527

(1)

Computations and Conclusions

528

(6)

Summary

534

(1)

Glossary

534

(1)

Key Formulas

535

(2)

Supplementary Exercises

537

(8)

Case Problem 1 Wentworth Medical Center

545

(1)

Case Problem 2 Compensation for ID Professionals

546

(1)

Appendix 13.1 Analysis of Variance and Experimental Design with Minitab

547

(1)

Appendix 13.2 Analysis of Variance and Experimental Design with Excel

548

(5)

Chapter 14 Simple Linear Regression

553

(82)

Statistics in Practice: Alliance Data Systems

554

(1)

14.1 Simple Linear Regression Model

555

(3)

Regression Model and Regression Equation

555

(1)

Estimated Regression Equation

556

(2)

14.2 Least Squares Method

558

(11)

14.3 Coefficient of Determination

569

(7)

Correlation Coefficient

572

(4)

14.4 Model Assumptions

576

(2)

14.5 Testing for Significance

578

(9)

Estimate of σ2

578

(1)

t Test

579

(1)

Confidence Interval for β1

580

(1)

F Test

581

(2)

Some Cautions About the Interpretation of Significance Tests

583

(4)

14.6 Using the Estimated Regression Equation for Estimation and Prediction

587

(6)

Point Estimation

587

(1)

Interval Estimation

587

(1)

Confidence Interval for the Mean Value of y

588

(1)

Prediction Interval for an Individual Value of y

589

(4)

14.7 Computer Solution

593

(5)

14.8 Residual Analysis: Validating Model Assumptions

598

(9)

Residual Plot Against x

599

(1)

Residual Plot Against y

600

(1)

Standardized Residuals

600

(3)

Normal Probability Plot

603

(4)

14.9 Residual Analysis: Outliers and Influential Observations

607

(7)

Detecting Outliers

607

(2)

Detecting Influential Observations

609

(5)

Summary

614

(1)

Glossary

615

(1)

Key Formulas

616

(2)

Supplementary Exercises

618

(5)

Case Problem 1 Spending and Student Achievement

623

(2)

Case Problem 2 U.S. Department of Transportation

625

(1)

Case Problem 3 Alumni Giving

626

(2)

Case Problem 4 Major League Baseball Team Values

628

(1)

Appendix 14.1 Calculus-Based Derivation of Least Squares Formulas

629

(1)

Appendix 14.2 A Test for Significance Using Correlation

630

(1)

Appendix 14.3 Regression Analysis with Minitab

631

(1)

Appendix 14.4 Regression Analysis with Excel

632

(3)

Chapter 15 Multiple Regression

635

(68)

Statistics in Practice: International Paper

636

(1)

15.1 Multiple Regression Model

637

(1)

Regression Model and Regression Equation

637

(1)

Estimated Multiple Regression Equation

637

(1)

15.2 Least Squares Method

638

(8)

An Example: Butler Trucking Company

639

(2)

Note on Interpretation of Coefficients

641

(5)

15.3 Multiple Coefficient of Determination

646

(3)

15.4 Model Assumptions

649

(1)

15.5 Testing for Significance

650

(8)

F Test

651

(3)

t Test

654

(1)

Multicollinearity

654

(4)

15.6 Using the Estimated Regression Equation for Estimation and Prediction

658

(2)

15.7 Qualitative Independent Variables

660

(8)

An Example: Johnson Filtration, Inc.

660

(2)

Interpreting the Parameters

662

(2)

More Complex Qualitative Variables

664

(4)

15.8 Residual Analysis

668

(7)

Detecting Outliers

669

(1)

Studentized Deleted Residuals and Outliers

670

(1)

Influential Observations

671

(1)

Using Cook's Distance Measure to Identify Influential Observations

671

(4)

15.9 Logistic Regression

675

(12)

Logistic Regression Equation

676

(1)

Estimating the Logistic Regression Equation

677

(2)

Testing for Significance

679

(1)

Managerial Use

680

(1)

Interpreting the Logistic Regression Equation

680

(3)

Logit Transformation

683

(4)

Summary

687

(1)

Glossary

687

(1)

Key Formulas

688

(2)

Supplementary Exercises

690

(5)

Case Problem 1 Consumer Research, Inc.

695

(1)

Case Problem 2 NFL Quarterback Rating

696

(2)

Case Problem 3 Predicting Student Proficiency Test Scores

698

(1)

Case Problem 4 Alumni Giving

699

(1)

Appendix 15.1 Multiple Regression with Minitab

699

(1)

Appendix 15.2 Multiple Regression with Excel

699

(3)

Appendix 15.3 Logistic Regression with Minitab

702

(1)

Chapter 16 Regression Analysis: Model Building

703

(54)

Statistics in Practice: Monsanto Company

704

(1)

16.1 General Linear Model

705

(15)

Modeling Curvilinear Relationships

705

(4)

Interaction

709

(2)

Transformations Involving the Dependent Variable

711

(4)

Nonlinear Models That Are Intrinsically Linear

715

(5)

16.2 Determining When to Add or Delete Variables

720

(7)

General Case

722

(1)

Use of ρ-Values

723

(4)

16.3 Analysis of a Larger Problem

727

(3)

16.4 Variable Selection Procedures

730

(7)

Stepwise Regression

731

(1)

Forward Selection

732

(1)

Backward Elimination

733

(1)

Best-Subsets Regression

733

(1)

Making the Final Choice

734

(3)

16.5 Residual Analysis

737

(7)

Autocorrelation and the Durbin-Watson Test

738

(6)

16.6 Multiple Regression Approach to Analysis of Variance and Experimental Design

744

(4)

Summary

748

(1)

Glossary

748

(1)

Key Formulas

749

(1)

Supplementary Exercises

749

(4)

Case Problem 1 Unemployment Study

753

(2)

Case Problem 2 Fuel Economy for Cars

755

(1)

Case Problem 3 Predicting Graduation Rates for Colleges and Universities

755

(2)

Chapter 17 Index Numbers

757

(21)

Statistics in Practice: U.S. Department of Labor, Bureau of Labor Statistics

758

(1)

17.1 Price Relatives

759

(1)

17.2 Aggregate Price Indexes

759

(4)

17.3 Computing an Aggregate Price Index from Price Relatives

763

(2)

17.4 Some Important Price Indexes

765

(2)

Consumer Price Index

765

(1)

Producer Price Index

765

(1)

Dow Jones Averages

766

(1)

17.5 Deflating a Series By Price Indexes

767

(4)

17.6 Price Indexes: Other Considerations

771

(1)

Selection of Items

771

(1)

Selection of a Base Period

771

(1)

Quality Changes

771

(1)

17.7 Quantity Indexes

772

(2)

Summary

774

(1)

Glossary

774

(1)

Key Formulas

774

(1)

Supplementary Exercises

775

(3)

Chapter 18 Forecasting

778

(47)

Statistics in Practice: Nevada Occupational Health Clinic

779

(1)

18.1 Components of a Time Series

780

(3)

Trend Component

780

(2)

Cyclical Component

782

(1)

Seasonal Component

783

(1)

Irregular Component

783

(1)

18.2 Smoothing Methods

783

(10)

Moving Averages

783

(2)

Weighted Moving Averages

785

(2)

Exponential Smoothing

787

(6)

18.3 Trend Projection

793

(6)

18.4 Trend and Seasonal Components

799

(10)

Multiplicative Model

799

(1)

Calculating the Seasonal Indexes

800

(4)

Deseasonalizing the Time Series

804

(1)

Using the Deseasonalized Time Series to Identify Trend

804

(3)

Seasonal Adjustments

807

(1)

Models Based on Monthly Data

807

(1)

Cyclical Component

807

(2)

18.5 Regression Analysis

809

(2)

18.6 Qualitative Approaches

811

(1)

Delphi Method

811

(1)

Expert Judgment

812

(1)

Scenario Writing

812

(1)

Intuitive Approaches

812

(1)

Summary

812

(1)

Glossary

813

(1)

Key Formulas

814

(1)

Supplementary Exercises

814

(5)

Case Problem 1 Forecasting Food and Beverage Sales

819

(1)

Case Problem 2 Forecasting Lost Sales

820

(1)

Appendix 18.1 Forecasting with Minitab

821

(2)

Appendix 18.2 Forecasting with Excel

823

(2)

Chapter 19 Nonparametric Methods

825

(34)

Statistics in Practice: West Shell Realtors

826

(2)

19.1 Sign Test

828

(5)

Small-Sample Case

828

(2)

Large-Sample Case

830

(1)

Hypothesis Test About a Median

831

(2)

19.2 Wilcoxon Signed-Rank Test

833

(5)

19.3 Mann-Whitney-Wilcoxon Test

838

(8)

Small-Sample Case

838

(2)

Large-Sample Case

840

(6)

19.4 Kruskal-Wallis Test

846

(4)

19.5 Rank Correlation

850

(4)

Test for Significant Rank Correlation

852

(2)

Summary

854

(1)

Glossary

855

(1)

Key Formulas

855

(1)

Supplementary Exercises

856

(3)

Chapter 20 Statistical Methods for Quality Control

859

(30)

Statistics in Practice: Dow Chemical U.S.A.

860

(1)

20.1 Statistical Process Control

861

(14)

Control Charts

862

(1)

x Chart: Process Mean and Standard Deviation Known

863

(2)

x Chart: Process Mean and Standard Deviation Unknown

865

(2)

R Chart

867

(2)

ρ Chart

869

(3)

nρ Chart

872

(1)

Interpretation of Control Charts

872

(3)

20.2 Acceptance Sampling

875

(9)

KALI, Inc.: An Example of Acceptance Sampling

876

(1)

Computing the Probability of Accepting a Lot

877

(3)

Selecting an Acceptance Sampling Plan

880

(1)

Multiple Sampling Plans

881

(3)

Summary

884

(1)

Glossary

884

(1)

Key Formulas

885

(1)

Supplementary Exercises

886

(2)

Appendix 20.1 Control Charts with Minitab

888

(1)

Chapter 21 Decision Analysis

889

(37)

Statistics in Practice: Ohio Edison Company

890

(1)

21.1 Problem Formulation

891

(2)

Payoff Tables

892

(1)

Decision Trees

892

(1)

21.2 Decision Making with Probabilities

893

(8)

Expected Value Approach

893

(2)

Expected Value of Perfect Information

895

(6)

21.3 Decision Analysis with Sample Information

901

(11)

Decision Tree

902

(1)

Decision Strategy

903

(3)

Expected Value of Sample Information

906

(6)

21.4 Computing Branch Probabilities Using Bayes' Theorem

912

(4)

Summary

916

(1)

Glossary

917

(1)

Key Formulas

918

(1)

Case Problem Lawsuit Defense Strategy

918

(1)

Appendix 21.1 Solving the PDC Problem with TreePlan

919

Chapter 22 Sample Survey On CD

Appendix A References and Bibliography

926

(2)

Appendix B Tables

928

(29)

Appendix C Summation Notation

957

(2)

Appendix D Self-Test Solutions and Answers to Even-Numbered Exercises

959

(51)

Index

1010

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Statistics for Business and Economics

Statistics for Business and Economics

9780324200829

032420082X

Summary

Table of Contents

Supplemental Materials

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Amazon no longer offers textbook rentals. We do!

Statistics for Business and Economics

Statistics for Business and Economics

9780324200829

032420082X

Summary

Table of Contents

Supplemental Materials

Write a Review

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