P worksheet 03g quantitative analysis answers

Copyright 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. WCN 02-200-203

This is an electronic version of the print textbook. Due to electronic rights restrictions, some third party content may be suppressed. Editorial review has deemed that any suppressed

content does not materially affect the overall learning experience. The publisher reserves the right to remove content from this title at any time if subsequent rights restrictions require it. For

valuable information on pricing, previous editions, changes to current editions, and alternate formats, please visit www.cengage.com/highered to search by ISBN, author, title, or keyword for

materials in your areas of interest.

Important notice: Media content referenced within the product description or the product text may not be available in the eBook version.

Copyright 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. WCN 02-200-203

Overview of Applications in the Book, by Discipline

Accounting Accounts receivable 285, 297 Auditing for price errors 329 Developing a flexible budget 537 Estimating total tax refunds 325 Estimating total taxable income 325 Overhead cost analysis 423, 437, 471, 490, 520, 524

Economics/Government Demand and cost for electricity 461 Demand for desktops and laptops 402 Demand for French bread 481 Demand for heating oil 536 Demand for microwaves 182 Electricity pricing 736 Home and condo prices 78 Housing price structure 480 Presidential elections 19 Sales of new houses 566, 572

Finance Bond investment strategy 893 Capital budgeting 714 Cash management 852 DJIA index 58, 77 Investing for college 892 Investing for retirement 481, 857 Investment strategy 703 Investor’s after-tax profit 181 Land purchase decision 274 Liquidity risk management 829 Market return scenarios 152, 157 Mutual fund returns 171, 195 New car development 847 Pension fund management 708 Portfolio analysis 743 Random walk of stock prices 562 Stock hedging 757

Human Resources Employee empowerment 389 Employee retention 361 Gender discrimination 450, 457, 514 Jobs in statistics and mathematics 897 Personnel testing 178 Productivity due to exercise 384

Copyright 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. WCN 02-200-203

Marketing Catalog marketing 503, 508 Churn in cellular phone market 136 Clustering shoe customers 934 Customer complaints 349, 378 Customer valuation 865 DVD movie renters 310 Electronics sales 108 Frozen lasagna dinner buyers 125, 915, 919, 923 Furniture pricing 480 Marketing and selling condos 873 New pizza style decisions 365, 373 New product decisions 233, 240, 243, 260 Olympics sponsors 363 Response to new sandwich 319, 346, 348 Running shoe style decisions 274 Sales presentation ratings 339 Sales response to coupons 343 Sales versus promotions 421, 433 Soft-drink can style decisions 380 Supermarket sales 197 Supermarket transactions 27 Value of free maintenance agreement 868

Miscellaneous Statistical Crime in the U.S. 54 Cruise ship entertainment 16 Election returns 200 Family income sampling 283 Forecasting U.S. population 557 IQ and bell curve 166 Predictors of successful movies 79, 482 Questionnaire responses 23 Relationship between smoking and drinking 82 Removing Vioxx from market 412 Sample size determination in legal case 279 Saving, spending, social climbing 136 Simpson’s paradox 165 University admissions 360

Operations Management Aggregate planning 693 Airline boarding strategies 759 Airline hub location decisions 729 Arrivals at bank 135 Automobile production 755 Battery lifetimes 191 Bidding for contracts 831 Blending oil 670 Developing Army helicopter component 276

Copyright 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. WCN 02-200-203

Developing electronic timing system 275 Delivery times at restaurant 361 Distribution of metal strip widths 396 Employee scheduling 663 Expensive watch production 219 Forecasting sales 551, 554, 559, 566, 572, 576, 581, 586 Inventory management 208 Learning curve for production 466 Manufacturing plastics operations 599 Ordering decisions 781, 784, 796, 806, 812, 815 Out-of-spec products 350 Overbooking at airlines 198 Product mix decisions 603, 631, 721 Production quantity decisions 827, 828 Production scheduling 641, 840 Production, inventory, distribution decisions 661 Quality control at paper company 179 Reliability of motors 336 Site selection of motor inns 417 Timing uncertainty in construction 144 Transportation, logistics decisions 677, 686 Variability in machine parts 333 Warranty costs 835

Sports/Gaming Baseball salaries 31, 40, 46, 49, 88 Games at McDonald’s 139 Golf stats on PGA tour 95 NCAA basketball tournament simulation 882 Revenue management at casino 539 Streak shooting in basketball 201 Wheel of fortune simulation 300 Winning at craps 879 Winning the lottery 220

Copyright 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. WCN 02-200-203

Australia • Brazil • Mexico • Singapore • United Kingdom • United States

Business Analytics: Data Analysis and Decision Making

6th Edition

S. Christian Albright Kelly School of Business, Indiana University, Emeritus

Wayne L. Winston Kelly School of Business, Indiana University

Copyright 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. WCN 02-200-203

Business Analytics: Data Analysis & Decision Making, Sixth Edition

S. Christian Albright and Wayne L. Winston

Vice President, General Manager, Social Science & Qualitative Business: Balraj Kalsi

Product Director: Mike Schenk

Product Manager: Aaron Arnsparger

Associate Content Developer: Brad Sullender

Product Assistant: Audrey Jacobs

Sr. Marketing Manager: Nathan Anderson

Manufacturing Planner: Ron J. Montgomery

Art and Cover Direction, Production Management, and Composition: Lumina Datamatics, Inc.

Cover Image: iStockphoto.com/derrrek

Intellectual Property

Analyst: Brittani Morgan

Project Manager: Nick Barrows

© 2017, 2015 Cengage Learning®

For product information and technology assistance, contact us at Cengage Learning Customer & Sales Support, 1-800-354-9706

For permission to use material from this text or product, submit all requests online at www.cengage.com/permissions

Further permissions questions can be emailed to permissionrequest@cengage.com

ALL RIGHTS RESERVED. No part of this work covered by the copyright herein may be reproduced or distributed in any form or by any means, except as permitted by U.S. copyright law, without the prior written permission of the copyright owner.

Library of Congress Control Number: 2016934323

ISBN: 978-1-305-94754-2

Loose Leaf Edition ISBN: 978-1-305-86647-8

Cengage Learning 20 Channel Center Street Boston, MA 02210 USA

Cengage Learning is a leading provider of customized learning solutions with employees residing in nearly 40 different countries and sales in more than 125 countries around the world. Find your local representative at www.cengage.com.

Cengage Learning products are represented in Canada by Nelson Education, Ltd.

To learn more about Cengage Learning Solutions, visit www.cengage.com

Purchase any of our products at your local college store or at our preferred online store www.cengagebrain.com

Printed in the United States of America Print Number: 01 Print Year: 2016

Copyright 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. WCN 02-200-203

To my wonderful wife Mary—my best friend and travel mate; to Sam, Lindsay, Teddy, and Archie; and to Bryn, our ball-playing Welsh corgi!Archie; and to Bryn, our ball-playing Welsh corgi! S.C.A

To my wonderful familyTo my wonderful family W.L.W.

Copyright 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. WCN 02-200-203

iv

S. Christian Albright got his B.S. degree in Mathematics from Stanford in 1968 and his PhD in Operations Research from Stanford in 1972. He taught in the Operations & Decision Technologies Department in the Kelley School of Business at Indiana University (IU) for close to 40 years, before retiring from teaching in 2011. While at IU, he taught courses in management science, computer simulation, statistics, and computer programming to all levels of business students, including undergraduates, MBAs, and doctoral students. In addition,

he taught simulation modeling at General Motors and Whirlpool, and he taught database analysis for the Army. He published over 20 articles in leading operations research journals in the area of applied probability, and he has authored the books Statistics for Business and Economics, Practical Management Science, Spreadsheet Modeling and Applications, Data Analysis for Managers, and VBA for Modelers. He worked for several years after “retirement” with the Palisade Corporation developing training materials for its software products, he has developed a commercial version of his Excel® tutorial, called ExcelNow!, and he continues to revise his textbooks.

On the personal side, Chris has been married for 44 years to his wonderful wife, Mary, who retired several years ago after teaching 7th grade English for 30 years. They have one son, Sam, who lives in Philadelphia with his wife Lindsay and their two sons, Teddy and Archer. Chris has many interests outside the academic area. They include activities with his family (especially traveling with Mary), going to cultural events at IU, power walking while listening to books on his iPod, and reading. And although he earns his livelihood from statistics and management science, his real passion is for playing real passion is for playing real classical piano music.

Wayne L. Winston taught in the Operations & Decision Technologies Department in the Kelley School of Business at Indiana University for close to 40 before retiring a few years ago. Wayne received his B.S. degree in Mathematics from MIT and his PhD in Operations Research from Yale. He has written the successful textbooks Operations Research: Applications and Algorithms, Mathematical Programming: Applications and Algorithms, Simulation Modeling Using @RISK, Practical Management Science, Data Analysis and Decision Making, Financial Models

Using Simulation and Optimization, and Mathletics. Wayne has published more than 20 articles in leading journals and has won many teaching awards, including the school-wide MBA award four times. He has taught classes at Microsoft, GM, Ford, Eli Lilly, Bristol-Myers Squibb, Arthur Andersen, Roche, PricewaterhouseCoopers, and NCR, and in “retirement,” he is currently teaching several courses at the

About the Authors

© C

en ga

ge L

ea rn

in g

© C

en ga

ge L

ea rn

in g

Copyright 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. WCN 02-200-203

v

University of Houston. His current interest is showing how spreadsheet models can be used to solve business problems in all disciplines, particularly in finance and marketing.

Wayne enjoys swimming and basketball, and his passion for trivia won him an appearance several years ago on the television game show Jeopardy!, where he won two games. He is married to the lovely and talented Vivian. They have two children, Gregory and Jennifer.

Copyright 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. WCN 02-200-203

vi

Brief Contents

Preface xviii 1 Introduction to Business Analytics 1

Part 1 Exploring Data 17 2 Describing the Distribution of a Single Variable 19 3 Finding Relationships among Variables 79

Part 2 Probability and Decision Making Under Uncertainty 137

4 Probability and Probability Distributions 139 5 Normal, Binomial, Poisson, and Exponential Distributions 166 6 Decision Making under Uncertainty 222

Part 3 Statistical Inference 277 7 Sampling and Sampling Distributions 279 8 Confidence Interval Estimation 311 9 Hypothesis Testing 363

Part 4 Regression Analysis and Time Series Forecasting 415 10 Regression Analysis: Estimating Relationships 417 11 Regression Analysis: Statistical Inference 482 12 Time Series Analysis and Forecasting 539

Part 5 Optimization and Simulation Modeling 597 13 Introduction to Optimization Modeling 599 14 Optimization Models 661 15 Introduction to Simulation Modeling 759 16 Simulation Models 829

Part 6 Advanced Data Analysis 895 17 Data Mining 897

Introduction to Spreadsheet Modeling (only in MindTap)

Copyright 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. WCN 02-200-203

Brief Contents vii

Part 7 Bonus Online Material* 18-1 18 Importing Data into Excel 18-3 19 Analysis of Variance and Experimental Design 19-1 20 Statistical Process Control 20-1 Appendix A Statistical Reporting A-1

•Bonus Online Material for this text can be found on the text companion website at cengagebrain.com.

References 943 Index 945

Copyright 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. WCN 02-200-203

viii

Contents

Preface xviii

1 Introduction to Business Analytics 1 1-1 Introduction 3 1-2 Overview of the Book 4

1-2a The Methods 4 1-2b The Software 7

1-3 Modeling and Models 10 1-3a Graphical Models 10 1-3b Algebraic Models 11 1-3c Spreadsheet Models 12 1-3d A Seven-Step Modeling Process 13

1-4 Conclusion 15

PART 1 EXPLORING DATA 17

2 Describing the Distribution of a Single Variable 19 2-1 Introduction 21 2-2 Basic Concepts 22

2-2a Populations and Samples 22 2-2b Data Sets, Variables, and Observations 23 2-2c Types of Data 24

2-3 Descriptive Measures for Categorical Variables 26 2-4 Descriptive Measures for Numerical Variables 30

2-4a Numerical Summary Measures 31 2-4b Numerical Summary Measures with StatTools 40 2-4c Analysis ToolPak Add-In 45 2-4d Charts for Numerical Variables 45

2-5 Time Series Data 54 2-6 Outliers and Missing Values 61

2-6a Outliers 61 2-6b Missing Values 61

2-7 Excel Tables for Filtering, Sorting, and Summarizing 63 2-8 Conclusion 71

Copyright 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. WCN 02-200-203

Contents ix

3 Finding Relationships among Variables 79 3-1 Introduction 80 3-2 Relationships among Categorical Variables 82 3-3 Relationships among Categorical Variables and a Numerical Variable 86

3-3a Stacked and Unstacked Formats 86 3-4 Relationships among Numerical Variables 95

3-4a Scatterplots 95 3-4b Correlation and Covariance 101

3-5 Pivot Tables 108 3-6 Conclusion 131

PART 2 PROBABILITY AND DECISION MAKING UNDER UNCERTAINTY 137

4 Probability and Probability Distributions 139 4-1 Introduction 140 4-2 Probability Essentials 142

4-2a Rule of Complements 142 4-2b Addition Rule 142 4-2c Conditional Probability and the Multiplication Rule 143 4-2d Probabilistic Independence 146 4-2e Equally Likely Events 147 4-2f Subjective Versus Objective Probabilities 147

4-3 Probability Distribution of a Single Random Variable 150 4-3a Summary Measures of a Probability Distribution 151 4-3b Conditional Mean and Variance 154

4-4 Introduction to Simulation 156 4-5 Conclusion 160

5 Normal, Binomial, Poisson, and Exponential Distributions 166 5-1 Introduction 167 5-2 The Normal Distribution 168

5-2a Continuous Distributions and Density Functions 168 5-2b The Normal Density 169 5-2c Standardizing: Z-ValuesZ-ValuesZ 170 5-2d Normal Tables and Z-ValuesZ-ValuesZ 172 5-2e Normal Calculations in Excel 174 5-2f5-2f Empirical Rules Revisited 177 5-2g Weighted Sums of Normal Random Variables 177

5-3 Applications of the Normal Distribution 178

Copyright 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. WCN 02-200-203

x Contents

5-4 The Binomial Distribution 190 5-4a Mean and Standard Deviation of the Binomial Distribution 193 5-4b The Binomial Distribution in the Context of Sampling 193 5-4c The Normal Approximation to the Binomial 194

5-5 Applications of the Binomial Distribution 195 5-6 The Poisson and Exponential Distributions 207

5-6a The Poisson Distribution 207 5-6b The Exponential Distribution 210

5-7 Conclusion 212

6 Decision Making under Uncertainty 222 6-1 Introduction 223 6-2 Elements of Decision Analysis 225

6-2a Identifying the Problem 225 6-2b Possible Decisions 226 6-2c Possible Outcomes 226 6-2d Probabilities of Outcomes 226 6-2e Payoffs and Costs 227 6-2f6-2f Decision Criterion 227 6-2g More about the EMV Criterion 228 6-2h Decision Trees 230

6-3 One-Stage Decision Problems 232 6-4 The PrecisionTree Add-In 236 6-5 Multistage Decision Problems 239 6-6 The Role of Risk Aversion 257

6-6a Utility Functions 258 6-6b Exponential Utility 259 6-6c Certainty Equivalents 262 6-6d Is Expected Utility Maximization Used? 263

6-7 Conclusion 264

PART 3 STATISTICAL INFERENCE 277

7 Sampling and Sampling Distributions 279 7-1 Introduction 280 7-2 Sampling Terminology 280 7-3 Methods for Selecting Random Samples 282

7-3a Simple Random Sampling 282 7-3b Systematic Sampling 287 7-3c Stratified Sampling 288 7-3d Cluster Sampling 289 7-3e Multistage Sampling Schemes 290

Copyright 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. WCN 02-200-203