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Statistics, Data Analysis, and Decision Modeling: International Edition

Statistics, Data Analysis, and Decision Modeling: International Edition

James R Evans

(2013)

Additional Information

Book Details

Abstract

For undergraduate and graduate level courses that combines introductory statistics with data analysis or decision modeling.

 

A pragmatic approach to statistics, data analysis and decision modeling.

 

Statistics, Data Analysis & Decision Modeling focuses on the practical understanding of its topics, allowing readers to develop conceptual insight on fundamental techniques and theories. Evans’ dedication to present material in a simple and straightforward fashion is ideal for student comprehension.




Table of Contents

Section Title Page Action Price
Cover Cover
Contents 9
Preface 21
Part I: STATISTICS AND DATA ANALYSIS 25
Chapter 1 DATA AND BUSINESS DECISIONS 27
Introduction 28
Data in the Business Environment 28
Sources and Types of Data 30
Metrics and Data Classification 31
Statistical Thinking 35
Populations and Samples 36
Using Microsoft Excel 37
Basic Excel Skills 38
Skill-Builder Exercise 1.1 38
Copying Formulas and Cell References 38
Skill-Builder Exercise 1.2 39
Functions 40
Skill‐Builder Exercise 1.3 42
Other Useful Excel Tips 42
Excel Add-Ins 43
Skill-Builder Exercise 1.4 44
Displaying Data with Excel Charts 45
Column and Bar Charts 45
Skill-Builder Exercise 1.5 46
Line Charts 47
Skill-Builder Exercise 1.6 47
Pie Charts 47
Skill-Builder Exercise 1.7 47
Area Charts 48
Scatter Diagrams 48
Skill‐Builder Exercise 1.8 48
Miscellaneous Excel Charts 49
Ethics and Data Presentation 49
Skill-Builder Exercise 1.9 50
Basic Concepts Review Questions 51
Problems and Applications 51
Case: A Data Collection and Analysis Project 52
Chapter 2 DESCRIPTIVE STATISTICS AND DATA ANALYSIS 55
Introduction 56
Descriptive Statistics 56
Frequency Distributions, Histograms, and Data Profiles 57
Categorical Data 58
Numerical Data 58
Skill-Builder Exercise 2.1 62
Skill-Builder Exercise 2.2 62
Data Profiles 62
Descriptive Statistics for Numerical Data 63
Measures of Location 63
Measures of Dispersion 64
Skill-Builder Exercise 2.3 66
Measures of Shape 67
Excel Descriptive Statistics Tool 68
Skill-Builder Exercise 2.4 68
Measures of Association 69
Skill-Builder Exercise 2.5 71
Descriptive Statistics for Categorical Data 71
Skill-Builder Exercise 2.6 72
Visual Display of Statistical Measures 73
Box Plots 73
Dot‐Scale Diagrams 73
Skill‐Builder Exercise 2.7 73
Outliers 74
Data Analysis Using PivotTables 74
Skill-Builder Exercise 2.8 77
Skill-Builder Exercise 2.9 77
Basic Concepts Review Questions 78
Problems and Applications 78
Case: The Malcolm Baldrige Award 81
Skill-Builder Exercise 2.10 83
Skill-Builder Exercise 2.11 84
Chapter 3 PROBABILITY CONCEPTS AND DISTRIBUTIONS 89
Introduction 90
Basic Concepts of Probability 90
Basic Probability Rules and Formulas 91
Conditional Probability 92
Skill-Builder Exercise 3.1 94
Random Variables and Probability Distributions 94
Discrete Probability Distributions 97
Expected Value and Variance of a Discrete Random Variable 98
Skill-Builder Exercise 3.2 99
Bernoulli Distribution 99
Binomial Distribution 99
Poisson Distribution 100
Skill-Builder Exercise 3.3 102
Continuous Probability Distributions 102
Uniform Distribution 104
Normal Distribution 105
Skill-Builder Exercise 3.4 108
Triangular Distribution 108
Exponential Distribution 109
Probability Distributions in PHStat 110
Other Useful Distributions 110
Joint and Marginal Probability Distributions 113
Basic Concepts Review Questions 114
Problems and Applications 114
Case: Probability Analysis for Quality Measurements 118
Chapter 4 SAMPLING AND ESTIMATION 123
Introduction 124
Statistical Sampling 124
Sample Design 124
Sampling Methods 125
Errors in Sampling 127
Random Sampling From Probability Distributions 127
Sampling From Discrete Probability Distributions 128
Skill‐Builder Exercise 4.1 129
Sampling From Common Probability Distributions 129
A Statistical Sampling Experiment in Finance 130
Skill-Builder Exercise 4.2 130
Sampling Distributions and Sampling Error 131
Skill-Builder Exercise 4.3 134
Applying the Sampling Distribution of the Mean 134
Sampling and Estimation 134
Point Estimates 135
Unbiased Estimators 136
Skill-Builder Exercise 4.4 137
Interval Estimates 137
Confidence Intervals: Concepts and Applications 137
Confidence Interval for the Mean with Known Population Standard Deviation 138
Skill-Builder Exercise 4.5 140
Confidence Interval for the Mean with Unknown Population Standard Deviation 140
Confidence Interval for a Proportion 142
Confidence Intervals for the Variance and Standard Deviation 143
Confidence Interval for a Population Total 145
Using Confidence Intervals for Decision Making 146
Confidence Intervals and Sample Size 146
Prediction Intervals 148
Additional Types of Confidence Intervals 149
Differences Between Means, Independent Samples 149
Differences Between Means, Paired Samples 149
Differences Between Proportions 150
Basic Concepts Review Questions 150
Problems and Applications 150
Case: Analyzing a Customer Survey 153
Skill-Builder Exercise 4.6 155
Skill-Builder Exercise 4.7 156
Skill-Builder Exercise 4.8 157
Skill-Builder Exercise 4.9 157
Chapter 5 HYPOTHESIS TESTING AND STATISTICAL INFERENCE 162
Introduction 163
Basic Concepts of Hypothesis Testing 163
Hypothesis Formulation 164
Significance Level 165
Decision Rules 166
Spreadsheet Support for Hypothesis Testing 169
One-Sample Hypothesis Tests 169
One-Sample Tests for Means 169
Using p-Values 171
One-Sample Tests for Proportions 172
One Sample Test for the Variance 174
Type II Errors and the Power of A Test 175
Skill-Builder Exercise 5.1 177
Two-Sample Hypothesis Tests 177
Two-Sample Tests for Means 177
Two-Sample Test for Means with Paired Samples 179
Two-Sample Tests for Proportions 179
Hypothesis Tests and Confidence Intervals 180
Test for Equality of Variances 181
Skill-Builder Exercise 5.2 182
Anova: Testing Differences of Several Means 182
Assumptions of ANOVA 184
Tukey–Kramer Multiple Comparison Procedure 184
Chi-Square Test for Independence 186
Skill-Builder Exercise 5.3 188
Basic Concepts Review Questions 188
Problems and Applications 188
Case: HATCO, Inc. 191
Skill-Builder Exercise 5.4 193
Chapter 6 REGRESSION ANALYSIS 196
Introduction 197
Simple Linear Regression 198
Skill-Builder Exercise 6.1 199
Least-Squares Regression 200
Skill-Builder Exercise 6.2 202
A Practical Application of Simple Regression to Investment Risk 202
Simple Linear Regression in Excel 203
Skill-Builder Exercise 6.3 204
Regression Statistics 204
Regression as Analysis of Variance 205
Testing Hypotheses for Regression Coefficients 205
Confidence Intervals for Regression Coefficients 206
Confidence and Prediction Intervals for X-Values 206
Residual Analysis and Regression Assumptions 206
Standard Residuals 208
Skill‐Builder Exercise 6.4 208
Checking Assumptions 208
Multiple Linear Regression 210
Skill‐Builder Exercise 6.5 210
Interpreting Results from Multiple Linear Regression 212
Correlation and Multicollinearity 212
Building Good Regression Models 214
Stepwise Regression 217
Skill-Builder Exercise 6.6 217
Best-Subsets Regression 217
The Art of Model Building in Regression 218
Regression with Categorical Independent Variables 220
Categorical Variables with More Than Two Levels 223
Skill-Builder Exercise 6.7 225
Regression Models with Nonlinear Terms 225
Skill-Builder Exercise 6.8 226
Basic Concepts Review Questions 228
Problems and Applications 228
Case: Hatco 231
Chapter 7 FORECASTING 237
Introduction 238
Qualitative and Judgmental Methods 238
Historical Analogy 239
The Delphi Method 239
Indicators and Indexes for Forecasting 239
Statistical Forecasting Models 240
Forecasting Models for Stationary Time Series 242
Moving Average Models 242
Error Metrics and Forecast Accuracy 244
Skill-Builder Exercise 7.1 246
Exponential Smoothing Models 246
Skill-Builder Exercise 7.2 248
Forecasting Models for Time Series with a Linear Trend 248
Regression-Based Forecasting 248
Advanced Forecasting Models 249
Autoregressive Forecasting Models 250
Skill-Builder Exercise 7.3 252
Forecasting Models with Seasonality 252
Incorporating Seasonality in Regression Models 253
Skill-Builder Exercise 7.4 255
Forecasting Models with Trend and Seasonality 255
Regression Forecasting with Causal Variables 255
Choosing and Optimizing Forecasting Models Using CB Predictor 257
Skill-Builder Exercise 7.5 259
The Practice of Forecasting 262
Basic Concepts Review Questions 263
Problems and Applications 264
Case: Energy Forecasting 265
Chapter 8 INTRODUCTION TO STATISTICAL QUALITY CONTROL 272
Introduction 272
The Role of Statistics and Data Analysis in Quality Control 273
Statistical Process Control 274
Control Charts 274
x- and R-Charts 275
Skill-Builder Exercise 8.1 280
Analyzing Control Charts 280
Sudden Shift in the Process Average 281
Cycles 281
Trends 281
Hugging the Center Line 281
Hugging the Control Limits 282
Skill-Builder Exercise 8.2 282
Skill-Builder Exercise 8.3 284
Control Charts for Attributes 284
Variable Sample Size 286
Skill-Builder Exercise 8.4 288
Process Capability Analysis 288
Skill-Builder Exercise 8.5 290
Basic Concepts Review Questions 290
Problems and Applications 290
Case: Quality Control Analysis 291
Part II: Decision Modeling and Analysis 293
Chapter 9 BUILDING AND USING DECISION MODELS 295
Introduction 295
Decision Models 296
Model Analysis 299
What-If Analysis 299
Skill-Builder Exercise 9.1 301
Skill-Builder Exercise 9.2 302
Skill-Builder Exercise 9.3 302
Model Optimization 302
Tools for Model Building 304
Logic and Business Principles 304
Skill-Builder Exercise 9.4 305
Common Mathematical Functions 305
Data Fitting 306
Skill-Builder Exercise 9.5 308
Spreadsheet Engineering 308
Skill-Builder Exercise 9.6 309
Spreadsheet Modeling Examples 309
New Product Development 309
Skill-Builder Exercise 9.7 311
Single Period Purchase Decisions 311
Overbooking Decisions 312
Project Management 313
Model Assumptions, Complexity, and Realism 315
Skill-Builder Exercise 9.8 317
Basic Concepts Review Questions 317
Problems and Applications 318
Case: An Inventory Management Decision Model 321
Chapter 10 DECISION MODELS WITH UNCERTAINTY AND RISK 324
Introduction 325
Spreadsheet Models with Random Variables 325
Monte Carlo Simulation 326
Skill-Builder Exercise 10.1 327
Monte Carlo Simulation Using Crystal Ball 327
Defining Uncertain Model Inputs 328
Running a Simulation 332
Saving Crystal Ball Runs 334
Analyzing Results 334
Skill-Builder Exercise 10.2 338
Crystal Ball Charts 339
Crystal Ball Reports and Data Extraction 342
Crystal Ball Functions and Tools 342
Applications of Monte Carlo Simulation and Crystal Ball Features 343
Newsvendor Model: Fitting Input Distributions, Decision Table Tool, and Custom Distribution 343
Skill-Builder Exercise 10.3 347
Skill-Builder Exercise 10.4 348
Overbooking Model: Crystal Ball Functions 348
Skill-Builder Exercise 10.5 349
Cash Budgeting: Correlated Assumptions 349
New Product Introduction: Tornado Chart Tool 352
Skill-Builder Exercise 10.6 353
Project Management: Alternate Input Parameters and the Bootstrap Tool 353
Skill-Builder Exercise 10.7 358
Basic Concepts Review Questions 358
Problems and Applications 359
Case: J&G Bank 362
Chapter 11 DECISIONS, UNCERTAINTY, AND RISK 367
Introduction 368
Decision Making Under Certainty 368
Decisions Involving a Single Alternative 369
Skill-Builder Exercise 11.1 369
Decisions Involving Non–mutually Exclusive Alternatives 369
Decisions Involving Mutually Exclusive Alternatives 370
Decisions Involving Uncertainty and Risk 371
Making Decisions with Uncertain Information 371
Decision Strategies for a Minimize Objective 372
Skill-Builder Exercise 11.2 374
Decision Strategies for a Maximize Objective 374
Risk and Variability 375
Expected Value Decision Making 377
Analysis of Portfolio Risk 378
Skill-Builder Exercise 11.3 380
The “Flaw of Averages” 380
Skill-Builder Exercise 11.4 380
Decision Trees 381
A Pharmaceutical R&D Model 381
Decision Trees and Risk 382
Sensitivity Analysis in Decision Trees 384
Skill-Builder Exercise 11.5 384
The Value of Information 384
Decisions with Sample Information 386
Conditional Probabilities and Bayes’s Rule 387
Utility and Decision Making 389
Skill-Builder Exercise 11.6 392
Exponential Utility Functions 393
Skill-Builder Exercise 11.7 394
Basic Concepts Review Questions 394
Problems and Applications 395
Case: The Sandwich Decision 399
Chapter 12 QUEUES AND PROCESS SIMULATION MODELING 402
Introduction 402
Queues and Queuing Systems 403
Basic Concepts of Queuing Systems 403
Customer Characteristics 404
Service Characteristics 405
Queue Characteristics 405
System Configuration 405
Performance Measures 406
Analytical Queuing Models 406
Single-Server Model 407
Skill-Builder Exercise 12.1 408
Little’s Law 408
Process Simulation Concepts 409
Skill-Builder Exercise 12.2 410
Process Simulation with SimQuick 410
Getting Started with SimQuick 411
A Queuing Simulation Model 412
Skill-Builder Exercise 12.3 416
Queues in Series with Blocking 417
Grocery Store Checkout Model with Resources 418
Manufacturing Inspection Model with Decision Points 421
Pull System Supply Chain with Exit Schedules 424
Other SimQuick Features and Commercial Simulation Software 426
Continuous Simulation Modeling 427
Basic Concepts Review Questions 430
Problems and Applications 431
Case: Production/Inventory Planning 434
Chapter 13 LINEAR OPTIMIZATION 435
Introduction 435
Building Linear Optimization Models 436
Characteristics of Linear Optimization Models 439
Implementing Linear Optimization Models on Spreadsheets 440
Excel Functions to Avoid in Modeling Linear Programs 441
Solving Linear Optimization Models 442
Solving the SSC Model Using Standard Solver 442
Solving the SSC Model Using Premium Solver 444
Solver Outcomes and Solution Messages 446
Interpreting Solver Reports 446
Skill-Builder Exercise 13.1 450
How Solver Creates Names in Reports 451
Difficulties with Solver 451
Applications of Linear Optimization 451
Process Selection 453
Skill-Builder Exercise 13.2 454
Blending 454
Skill-Builder Exercise 13.3 456
Portfolio Investment 456
Skill-Builder Exercise 13.4 457
Transportation Problem 457
Interpreting Reduced Costs 461
Multiperiod Production Planning 461
Skill-Builder Exercise 13.5 463
Multiperiod Financial Planning 463
Skill-Builder Exercise 13.6 464
A Model with Bounded Variables 464
A Production/Marketing Allocation Model 469
How Solver Works 473
Basic Concepts Review Questions 474
Problems and Applications 474
Case: Haller’s Pub & Brewery 481
Chapter 14 INTEGER, NONLINEAR, AND ADVANCED OPTIMIZATION METHODS 482
Introduction 482
Integer Optimization Models 483
A Cutting Stock Problem 483
Solving Integer Optimization Models 484
Skill-Builder Exercise 14.1 486
Integer Optimization Models with Binary Variables 487
Project Selection 487
Site Location Model 488
Skill-Builder Exercise 14.2 491
Computer Configuration 491
Skill-Builder Exercise 14.3 494
A Supply Chain Facility Location Model 494
Mixed Integer Optimization Models 495
Plant Location Model 495
A Model with Fixed Costs 497
Nonlinear Optimization 499
Hotel Pricing 499
Solving Nonlinear Optimization Models 501
Markowitz Portfolio Model 503
Skill-Builder Exercise 14.4 506
Evolutionary Solver for Nonsmooth Optimization 506
Rectilinear Location Model 508
Skill-Builder Exercise 14.5 508
Job Sequencing 509
Skill-Builder Exercise 14.6 512
Risk Analysis and Optimization 512
Combining Optimization and Simulation 515
A Portfolio Allocation Model 515
Using OptQuest 516
Skill-Builder Exercise 14.7 524
Basic Concepts Review Questions 524
Problems and Applications 524
Case: Tindall Bookstores 530
Appendix 533
Index 545
A 545
B 545
C 545
D 546
E 547
F 547
G 548
H 548
I 548
J 548
K 548
L 548
M 549
N 549
O 549
P 549
Q 550
R 550
S 551
T 552
U 552
V 552
W 552
X 552
Z 552