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Managerial Statistics

by Albright, S. Christian; Winston, Wayne L.; Zappe, Christopher

ISBN13: 9780534389314
ISBN10: 0534389317
Additional ISBN(s): 9780534349813, 9780534383664
Edition: CD
Format: Hardcover
Copyright: 2001-05-15
Publisher: South-Western College Pub
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1. Managerial Statistics > ISBN13: 9780534389314

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Summary

This text is designed for the undergraduate or MBA level course in Business and Economic Statistics. The course can be found in schools of business or departments of statistics and mathematics. College algebra is a prerequisite. MANAGERIAL STATISTICS presents core statistical methods in a modern, unified spreadsheet-oriented approach with a focus on applications to business. This text illustrates, in a very hands-on, example-based approach, a variety of statistical methods to help students analyze data sets and uncover important information to aid decision making. This application focus, together with Excel spreadsheet add-ins, provides a complete learning resource for students.

Author Biography

S. Christian Albright Chris Albright got his B.S. degree in Mathematics from Stanford in 1968 and his Ph.D. in Operations Research from Stanford in 1972. Since then he has been teaching in the Operations and Decision Technologies Department in the Kelley School of Business at Indiana University Wayne Winston Wayne L. Winston is Professor of Operations and Decision Technologies in the Kelley School of Business at Indiana University, where he has taught since 1975. Wayne received his B.S. degree in mathematics from MIT and his Ph.D. degree in operations research from Yale Christopher J. Zappe Chris earned his B.A. in mathematics from DePauw University in 1983 and his M.B.A. and Ph.D. in decision sciences from Indiana University in 1987 and 1988, respectively. Since 1993, Chris has been serving as an associate professor in the Department of Management at Bucknell University, where he teaches undergraduate courses in business statistics, decision analysis, and computer simulation. Currently, Chris is a visiting faculty member in the Operations and Decision Technologies Department of the Kelley School of Business at Indiana University in Bloomington

Preface

Introduction to Managerial Statistics

(22)

Introduction

(2)

An Overview of the Book

(5)

Excel versus Stand-alone Statistical Software

(1)

A Sampling of Examples

(9)

Conclusion

(3)

Case Study: Entertainment on a Cruise Ship

(2)

Describing Data: Graphs and Tables

(48)

Introduction

(1)

Basic Concepts

(4)

Frequency Tables and Histograms

(11)

Analyzing Relationships with Scatterplots

(4)

Time Series Plots

(5)

Exploring Data with Pivot Tables

(9)

Pivot Table Changes in Excel 2000

(3)

Conclusion

(9)

Case Study: Customer Arrivals at Bank98

(1)

Case Study: Automobile Production and Purchases

(1)

Case Study: Saving, Spending, and Social Climbing

(1)

Describing Data: Summary Measures

(52)

Introduction

(1)

Measures of Central Location

(2)

Quartiles and Percentiles

(1)

Minimum, Maximum, and Range

(1)

Measures of Variability: Variance and Standard Deviation

(4)

Obtaining Summary Measures with Add-Ins

(5)

Measures of Association: Covariance and Correlation

(4)

Describing Data Sets with Boxplots

(4)

Applying the Tools

(17)

Conclusion

112

(12)

Case Study: The Dow-Jones Averages

120

(2)

Case Study: Other Market Indexes

122

(2)

Getting the Right Data in Excel

124

(54)

Introduction

126

(1)

Cleaning the Data

127

(9)

Using Excel's AutoFilter

136

(7)

Complex Queries with the Advanced Filter

143

(7)

Importing External Data from Access

150

(12)

Creating Pivot Tables from External Data

162

(3)

Web Queries

165

(10)

Conclusion

175

(3)

Case Study: EduToys, Inc.

176

(2)

Probability and Probability Distributions

178

(64)

Introduction

180

(1)

Probability Essentials

181

(6)

Distribution of a Single Random Variable

187

(4)

An Introduction to Simulation

191

(5)

Subjective Versus Objective Probabilities

196

(2)

Derived Probability Distributions

198

(4)

Distribution of Two Random Variables: Scenario Approach

202

(7)

Distribution of Two Random Variables: Joint Probability Approach

209

(10)

Independent Random Variables

219

(5)

Weighted Sums of Random Variables

224

(7)

Conclusion

231

(11)

Case Study: Simpson's Paradox

240

(2)

Normal, Binomial, and Poisson Distributions

242

(56)

Introduction

244

(1)

The Normal Distribution

245

(9)

Applications of the Normal Distribution

254

(12)

The Binomial Distribution

266

(4)

Applications of the Binomial Distribution

270

(12)

The Poisson Distribution

282

(4)

Fitting a Probability Distribution to Data: BestFit

286

(3)

Conclusion

289

(9)

Case Study: EuroWatch Company

295

(1)

Case Study: Cashing in on the Lottery

296

(2)

Decision Making Under Uncertainty

298

(78)

Introduction

300

(1)

Elements of a Decision Analysis

301

(11)

The Precision Tree Add-In

312

(10)

Introduction to Influence Diagrams

322

(6)

More Single-Stage Examples

328

(10)

Multistage Decision Problems

338

(9)

Bayes' Rule

347

(8)

Incorporating Attitudes Toward Risk

355

(8)

Conclusion

363

(13)

Case Study: Jogger Shoe Company

374

(1)

Case Study: Westhouser Paper Company

374

(2)

Sampling and Sampling Distributions

376

(46)

Introduction

378

(1)

Sampling Terminology

378

(1)

Methods for Selecting Random Samples

379

(16)

An Introduction to Estimation

395

(17)

Conclusion

412

(10)

Case Study: Sampling from Videocassette Renters

421

(1)

Confidence Interval Estimation

422

(64)

Introduction

424

(1)

Sampling Distributions

425

(4)

Confidence Interval for a Mean

429

(5)

Confidence Interval for a Total

434

(3)

Confidence Interval for a Proporation

437

(5)

Confidence Interval for a Standard Deviation

442

(4)

Confidence Interval for the Difference Between Means

446

(12)

Confidence Interval for the Difference Between Proportions

458

(8)

Controlling Confidence Interval Length

466

(7)

Conclusion

473

(13)

Case Study: Harrigan University Admissions

480

(1)

Case Study: Employee Retention at D & Y

481

(1)

Case Study: Delivery Times at SnowPea Restaurant

482

(1)

Case Study: The Bodfish Lot Cruise

483

(3)

Hypothesis Testing

486

(60)

Introduction

488

(1)

Concepts in Hypothesis Testing

489

(6)

Hypothesis Tests for a Population Mean

495

(10)

Hypothesis Tests for Other Parameters

505

(21)

Tests for Normality

526

(6)

Chi-Square Test for Independence

532

(5)

Conclusion

537

(9)

Case Study: Regression Toward the Mean

542

(1)

Case Study: Baseball Statistics

543

(1)

Case Study: The Wichita Anti-Drunk Driving Advertising Campaign

543

(3)

Statistical Process Control

546

(62)

Introduction

549

(1)

Deming's 14 Points

550

(3)

Basic Ideas Behind Control Charts

553

(2)

Control Charts for Variables

555

(20)

Control Charts for Attributes

575

(8)

Process Capability

583

(11)

Conclusion

594

(14)

Case Study: The Lamination Process at Intergalactica

599

(2)

Case Study: Paper Production for Fornax at the Pluto Mill

601

(7)

Analysis of Variance and Experimental Design

608

(46)

Introduction

610

(3)

One-Way ANOVA

613

(12)

The Multiple Comparison Problem

625

(6)

Two-Way ANOVA

631

(12)

More About Experimental Design

643

(9)

Conclusion

652

(2)

Case Study: Krentz Appraisal Services

653

(1)

Regression Analysis: Estimating Relationships

654

(68)

Introduction

656

(2)

Scatterplots: Graphing Relationships

658

(9)

Correlations: Indicators of Linear Relationships

667

(2)

Simple Linear Regression

669

(10)

Multiple Regression

679

(6)

Modeling Possibilities

685

(26)

Validation of the Fit

711

(2)

Conclusion

713

(9)

Case Study: Quantity Discounts at the FirmChair Company

720

(1)

Case Study: Housing Price Structure in MidCity

720

(1)

Case Study: Demand for French Bread at Howie's

721

(1)

Case Study: Investing for Retirement

721

(1)

Regression Analysis: Statistical Inference

722

(75)

Introduction

724

(1)

The Statistical Model

725

(3)

Inferences About the Regression Coefficients

728

(6)

Multicollinearity

734

(4)

Include/Exclude Decisions

738

(5)

Stepwise Regression

743

(5)

A Test for the Overall Fit: The ANOVA Table

748

(4)

The Partial F Test

752

(9)

Outliers

761

(6)

Violations of Regression Assumptions

767

(4)

Prediction

771

(8)

Conclusion

779

(18)

Case Study: The Artsy Corporation

790

(1)

Case Study: Heating Oil at Dupree Fuels Company

791

(2)

Case Study: Developing a Flexible Budget at the Gunderson Plant

793

(1)

Case Study: Forecasting Overhead at Wagner Printers

794

(3)

Discriminant Analysis and Logistic Regression

797

(39)

Introduction

799

(1)

Discriminant Analysis

800

(19)

Logistic Regression

819

(15)

Choosing Between the Two Methods

834

(1)

Conclusion

834

(2)

Case Study: Understanding Cereal Brand Preferences

835

(1)

Time Series Analysis and Forecasting

836

(70)

Introduction

838

(1)

Forecasting Methods: An Overview

839

(4)

Random Series

843

(10)

The Random Walk Model

853

(4)

Autoregression Models

857

(6)

Regression-Based Trend Models

863

(7)

Moving Averages

870

(6)

Exponential Smoothing

876

(14)

Deseasonalizing: The Ratio-to-Moving-Averages Method

890

(4)

Estimating Seasonality with Regression

894

(5)

Econometric Models

899

(1)

Conclusion

900

(6)

Case Study: Arrivals at the Credit Union

904

(1)

Case Study: Forecasting Weekly Sales at Amanta

904

(2)

Statistical Reporting

906

(20)

Introduction

907

(1)

Suggestions for Good Statistical Report Writing

908

(5)

Examples of Statistical Reports

913

(12)

Conclusion

925

(1)

References

926

(3)

Index

929

Supplemental Materials

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Managerial Statistics

Summary

Author Biography

Table of Contents

Supplemental Materials

Rewards Program