Table of contents for Business forecasting / John E. Hanke, Dean W. Wichern.

Bibliographic record and links to related information available from the Library of Congress catalog.

Note: Contents data are machine generated based on pre-publication provided by the publisher. Contents may have variations from the printed book or be incomplete or contain other coding.


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Contents
Preface	xxx
CHAPTER 1	Introduction to Forecasting	1
The History of Forecasting	1
Is Forecasting Necessary	2
Types of Forecasts	2
Macroeconomic Forecasting Considerations	3
Choosing a Forecasting Method	4
Forecasting Steps	4
Managing the Forecasting Process	6
Forecasting Software	6
Online Information	7
Forecasting Examples	7
Summary	9
Case 1-1: Mr. Tux	10
Case 1-2: Consumer Credit Counseling	10
Minitab Applications	11
Excel Applications	12
References	12
CHAPTER 2	A Review of Basic Statistical Concepts	15
Describing Data with Numerical Summaries	15
Displays of Numerical Information	19
Probability Distributions	22
Sampling Distributions	26
Inference from a Sample	29
Estimation	29
Hypothesis Testing	30
p-Value	32
Correlation Analysis	34
Scatter Diagrams	34
Correlation Coefficient	37
Fitting a Straight Line	39
Assessing Normality	42
Application to Management	44
Glossary	44
Key Formulas	45
Problems	46
Case 2-1: Alcam Electronics	53
Case 2-2: Mr. Tux	54
Case 2-3: Alomega Food Stores	56
Minitab Applications	56
Excel Applications	58
References	60
CHAPTER 3	Exploring Data Patterns and an Introduction to Forecasting Techniques	61
Exploring Time Series Data Patterns	62
Exploring Data Patterns with Autocorrelation Analysis	64
Are the Data Random?	69
Do the Data Have a Trend?	72
Are the Data Seasonal?	76
Choosing a Forecasting Technique	76
Forecasting Techniques for Stationary Data	78
Forecasting Techniques Data with a Trend	78
Forecasting Techniques for Seasonal Data	79
Forecasting Techniques for Cyclical Series	79
Other Factors to Consider When Choosing a Forecasting Technique	79
Empirical Evaluation of Forecasting Methods	81
Measuring Forecast Error	81
Determining the Adequacy of a Forecasting Technique	84
Application to Management	86
Glossary	87
Key Formulas	87
Problems	88
Case 3-1A: Murphy Brothers Furniture	94
Case 3-1B: Murphy Brothers Furniture	96
Case 3-2: Mr. Tux	97
Case 3-3: Consumer Credit Counseling	98
Case 3-4: Alomega Food Stores	99
Case 3-5: Surtido Cookies	100
Minitab Applications	101
Excel Applications	103
References	105
CHAPTER 4	Moving Averages and Smoothing Methods	107
Naive Models	108
Forecasting Methods Based on Averaging	111
Simple Averages	111
Moving Averages	113
Double Moving Averages	116
Exponential Smoothing Methods	119
Exponential Smoothing Adjusted for Trend: Holt's Method	126
Exponential Smoothing Adjusted for Trend and Seasonal Variation: Winter's Method	130
Application to Management	135
Glossary	136
Key Formulas	136
Problems	138
Case 4-1: The Solar Alternative Company	145
Case 4-2: Mr. Tux	147
Case 4-3: Consumer Credit Counseling	148
Case 4-4: Murphy Brothers Furniture	148
Case 4-5: Five-Year Revenue Projection for Downtown Radiology	149
Case 4-6: Web Retailer	154
Case 4-7: Southwest Medical Center	158
Case 4-8: Surtido Cookies	159
Minitab Applications	159
Excel Applications	161
References	163
>CHAPTER 5	Time Series and Their Components	165
Decomposition	166
Trend	168
Additional Trend Curves	171
Forecasting Trend	174
Seasonality	175
Seasonally Adjusted Data	179
Cyclical and Irregular Variations	180
Summary Example	180
Business Indicators	184
Forecasting a Seasonal Time Series	185
The Census II Decomposition Method	187
Application to Management	189
Appendix: Price Index	190
Glossary	192
Key Formulas	192
Problems	193
Case 5-1: The Small Engine Doctor	201
Case 5-2: Mr. Tux	202
Case 5-3: Consumer Credit Counseling	206
Case 5-4: Murphy Brothers Furniture	207
Case 5-5: AAA Washington	210
Case 5-6: Alomega Food Stores	212
Case 5-7: Surtido Cookies	213
Case 5-8: Southwest Medical Center	214
Minitab Applications	214
Excel Applications	217
References	219
CHAPTER 6	Simple Linear Regression	221
Regression Line	222
Standard Error of the Estimate	226
Forecasting Y	227
Decomposition of Variance	230
Coefficient of Determination	234
Hypothesis Testing	236
Analysis of Residuals	239
Computer Output	241
Variable Transformations	243
Growth Curves	246
Application to Management	250
Glossary	252
Key Formulas	253
Problems	254
Case 6-1: Tiger Transport	266
Case 6-2: Butcher Products, Inc.	268
Case 6-3: Ace Manufacturing	269
Case 6-4: Mr. Tux	270
Case 6-5: Consumer Credit Counseling	270
Case 6-6: AAA Washington	271
Minitab Applications	274
Excel Applications	277
References	279
CHAPTER 7	Multiple Regression Analysis	281
Several Predictor Variables	281
Correlation Matrix	282
Multiple Regression Model	283
Statistical Model for Multiple Regression	283
Interpreting Regression Coefficients	285
Inference for Multiple Regression Models	286
Standard Error of the Estimate	287
Significance of the Regression	288
Individual Predictor Variables	290
Forecast of a Future Response	291
Computer Output	292
Dummy Variables	293
Multicollinearity	297
Selecting the ?Best? Regression Equation	300
All Possible Regressions	302
Stepwise Regression	304
Final Notes on Stepwise Regression	306
Regression Diagnostics and Residual Analysis	307
Forecasting Caveats	309
Overfitting	309
Useful Regression, Large F Ratios	310
Application to Management	310
Glossary	312
Key Formulas	312
Problems	313
Case 7-1: The Bond Market	324
Case 7-2: AAA Washington	328
Case 7-3: Fantasy Baseball (A)	330
Case 7-4: Fantasy Baseball (B)	334
Minitab Applications	336
Excel Applications	337
References	338
CHPATER 8	Regression with Time Series Data	339
Time Series Data and the Problem of Autocorrelation	339
Autocorrelation and the Durbin-Watson Test	343
Solutions to Autocorrelation Problems	347
Model Specification Error (Omitting a Variable)	348
Regression with Differences	350
Autocorrelated Errors and Generalized Differences	354
Autoregression Models	357
Summary	358
Time Series Data and the Problem of Heteroscedasticity	358
Using Regression to Forecast Seasonal Data	361
Econometric Forecasting	364
Cointegrated Time Series	365
Application to Management	367
Glossary	367
Key Formulas	367
Problems	369
Case 8-1: Company of Your Choice	378
Case 8-2: Business Activity Index for Spokane County	379
Case 8-3: Restaurant Sales	383
Case 8-4: Mr. Tux	385
Case 8-5: Consumer Credit Counseling	388
Case 8-6: AAA Washington	389
Case 8-7: Alomega Food Stores	392
Case 8-8: Surtido Cookies	393
Case 8-9: Southwest Medical Center	394
Minitab Applications	395
Excel Applications	396
References	398
CHAPTER 9	The Box-Jenkins (ARIMA) Methodology	399
Box-Jenkins Methodology	399
Autoregression Models	404
Moving Average Models	405
Autoregressive Moving Average Models	407
Summary	407
Implementing the Model-Building Strategy	407
Step 1: Model Identification	407
Step 2: Model Estimation	409
Step 3: Model Checking	410
Step 4: Forecasting with the Model	411
Model-Building Caveats	430
Model Selection Criteria	431
ARIMA Models for Seasonal Data	432
Simple Exponential Smoothing and an ARIMA Model	442
Advantages and Disadvantages of ARIMA Models	443
Application to Management	444
Glossary	445
Key Formulas	445
Problems	446
Case 9-1: Restaurant Sales	457
Case 9-2: Mr. Tux	459
Case 9-3: Consumer Credit Counseling	460
Case 9-4: The Lydia E. Pinkham Medicine Company	461
Case 9-5: City of College Station	463
Case 9-6: UPS Air Finance Division	466
Case 9-7: AAA Washington	469
Case 9-8: Web Retailer	471
Case 9-9: Surtido Cookies	474
Case 9-10: Southwest Medical Center	476
Minitab Applications	478
References	480
CHAPTER 10	Judgmental Forecasting and Forecast Adjustments	481
Judgmental Forecasting	483
The Delphi Method	483
Scenario Writing	485
Combining Forecasts	486
Forecasting and Neural Networks	488
Summary of Judgmental Forecasting	490
Other Tools Useful in Making Judgments About the Future	491
Key Formulas	496
Problems	496
Case 10-1: Golden Gardens Restaurant	497
Case 10-2: Alomega Food Stores	497
Case 10-3: The Lydia E. Pinkham Medicine Company	498
References	501
CHAPTER 11	Managing the Forecasting Process	503
The Forecasting Process	503
Monitoring Forecasts	504
Forecasting Steps Reviewed	509
Forecasting Responsibility	510
Forecasting Costs	511
Forecasting and Management Information Systems	511
Selling Management on Forecasting	512
The Future of Forecasting	512
Problems	513
Case 11-1: Boundary Electronics	513
Case 11-2: Busby Associates	514
Case 11-3: Consumer Credit Counseling	517
Case 11-4: Mr. Tux	518
Case 11-5: Alomega Food Stores	519
Case 11-6: Southwest Medical Center	520
References	520
Appendix A	Data for Case 7-1	000
Appendix B	Tables	000
Table B-1	Individual Terms of the Binomial Distribution	000
Table B-2	Areas for Standard Normal Probability Distribution	000
Table B-3	Critical Values of t	000
Table B-4	Critical Values of Chi-Square	000
Table B-5	F Distribution	000
Table B-6	Durbin-Watson Test Bounds	000
Appendix C	Data Sets and Databases	000
Index	000

Library of Congress Subject Headings for this publication:

Business forecasting.