Business Forecasting : International Edition

by Hanke, John E.; Wichern, Dean

• ISBN13: 9780131073852
• ISBN10: 0131073850
• Edition: 8th
• Format: Hardcover
• Copyright: 2009-01-01
• Publisher: Prentice Hall

Summary

The eighth edition ofBusiness Forecastingpresents basic statistical techniques that are useful for preparing individual business forecasts and long-range plans. Written in a simple, straightforward style and making extensive use of practical business examples, the book includes fifty-three cases that provide readers with the necessary link between theoretical concepts and their real-world applications. Readers should have a basic knowledge of statistics and be familiar with computer applications such as word processing and spreadsheets.The book first presents background material such as the nature of forecasting and a quick review of basic statistical concepts; proceeds with the exploration of data patterns and choosing a forecasting technique; covers averaging the smoothing techniques and time series decomposition; emphasizes causal forecasting techniques such as correlation, regression, and multiple regression analysis; and concludes with judgmental forecasting and forecast adjustments.Useful as a reference for professionals with titles such as: forecasting manager, marketing manager, production manager, and analyst.

Table of Contents

Preface	xiii
Introduction to Forecasting	1	(14)
The History of Forecasting	1	(1)
The Need for Forecasting	1	(2)
Types of Forecasts	3	(1)
Macroeconomic Forecasting Considerations	4	(1)
Choosing a Forecasting Method	4	(1)
Forecasting Steps	5	(1)
Managing the Forecasting Process	6	(1)
Computer Forecasting Packages	7	(1)
Online Information	8	(1)
Forecasting Example	8	(1)
Summary	9	(1)
Case 1-1: Mr. Tux	10	(1)
Case 1-2: Consumer Credit Counseling	10	(1)
Minitab Applications	11	(1)
Excel Applications	12	(1)
References	12	(3)
A Review of Basic Statistical Concepts	15	(42)
Describing Data with Numerical Summaries	15	(4)
Displays of Numerical Information	19	(3)
Probability Distributions	22	(4)
Sampling Distributions	26	(2)
Inference from a Sample	28	(1)
Estimation	28	(1)
Hypothesis Testing	29	(3)
p-Value	31	(1)
Correlation Analysis	32	(3)
Scatter Diagrams	32	(3)
Correlation Coefficient	35	(2)
Fitting a Straight Line	37	(2)
Assessing Normality	39	(3)
Application to Management	42	(1)
Glossary	43	(1)
Key Formulas	43	(2)
Problems	45	(5)
Case 2-1: Alcom Electronics	50	(1)
Case 2-2: Mr. Tux	51	(1)
Case 2-3: Alomega Food Stores	52	(1)
Minitab Applications	53	(2)
Excel Applications	55	(1)
References	56	(1)
Exploring Data Patterns and Choosing a Forecasting Technique	57	(44)
Exploring Time Series Data Patterns	58	(2)
Exploring Data Patterns with Autocorrelation Analysis	60	(14)
Are the Data Random?	65	(2)
Do the Data Have a Trend?	67	(2)
Are the Data Seasonal?	69	(5)
Choosing a Forecasting Technique	74	(4)
Forecasting Techniques for Stationary Data	75	(1)
Forecasting Techniques for Data with a Trend	75	(1)
Forecasting Techniques for Seasonal Data	76	(1)
Forecasting Techniques for Cyclical Series	76	(1)
Other Factors to Consider When Choosing a Forecasting Technique	77	(1)
Empirical Evaluation of Forecasting Methods	77	(1)
Measuring Forecasting Error	78	(3)
Basic Forecasting Notation	79	(2)
Determining the Adequacy of a Forecasting Technique	81	(2)
Application to Management	83	(1)
Glossary	84	(1)
Key Formulas	84	(1)
Problems	85	(5)
Case 3-1A: Murphy Brothers Furniture	90	(2)
Case 3-1B: Murphy Brothers Furniture	92	(1)
Case 3-2: Mr. Tux	92	(2)
Case 3-3: Consumer Credit Counseling	94	(1)
Case 3-4: Alomega Food Stores	94	(1)
Minitab Applications	95	(3)
Excel Applications	98	(2)
References	100	(1)
Moving Averages and Smoothing Methods	101	(56)
Naive Models	102	(3)
Forecasting Methods Based on Averaging	105	(9)
Simple Averages	105	(2)
Moving Averages	107	(3)
Double Moving Averages	110	(4)
Exponential Smoothing Methods	114	(16)
Exponential Smoothing Adjusted for Trend: Holt's Method	121	(5)
Exponential Smoothing Adjusted for Trend and Seasonal Variation: Winters' Method	126	(4)
Application to Management	130	(1)
Glossary	131	(1)
Key Formulas	131	(2)
Problems	133	(6)
Case 4-1: The Solar Alternative Company	139	(1)
Case 4-2: Mr. Tux	140	(1)
Case 4-3: Consumer Credit Counseling	141	(1)
Case 4-4: Murphy Brothers Furniture	141	(1)
Case 4-5: Five-Year Revenue Projection for Downtown Radiology	142	(6)
Minitab Applications	148	(2)
Excel Applications	150	(1)
Excel Applications: CB Predictor	151	(4)
References	155	(2)
Time Series and Their Components	157	(54)
Decomposition	158	(2)
Trend	160	(11)
Additional Trend Curves	164	(2)
Forecasting Trend	166	(1)
Seasonality	167	(4)
Seasonally Adjusted Data	171	(6)
Cyclical and Irregular Variations	172	(5)
Forecasting a Seasonal Time Series	177	(2)
The Census II Decomposition Method	179	(2)
Application to Management	181	(1)
Appendix: Price Index	182	(2)
Glossary	184	(1)
Key Formulas	184	(1)
Problems	185	(6)
Case 5-1: The Small Engine Doctor	191	(1)
Case 5-2: Mr. Tux	192	(4)
Case 5-3: Consumer Credit Counseling	196	(1)
Case 5-4: Murphy Brothers Furniture	197	(3)
Case 5-5: AAA Washington	200	(2)
Case 5-6: Alomega Food Stores	202	(1)
Minitab Applications	203	(3)
Excel Applications	206	(3)
References	209	(2)
Simple Linear Regression	211	(58)
Regression Line	212	(4)
Standard Error of the Estimate	216	(1)
Forecasting Y	217	(3)
Decomposition of Variance	220	(4)
Coefficient of Determination	224	(2)
Hypothesis Testing	226	(3)
Analysis of Residuals	229	(2)
Computer Output	231	(2)
Variable Transformations	233	(4)
Growth Curves	237	(5)
Application to Management	242	(1)
Glossary	243	(1)
Key Formulas	243	(2)
Problems	245	(9)
Case 6-1: Tiger Transport	254	(2)
Case 6-2: Butcher Products, Inc.	256	(1)
Case 6-3: Ace Manufacturing	257	(1)
Case 6-4: Mr. Tux	258	(1)
Case 6-5: Consumer Credit Counseling	259	(1)
Case 6-6: AAA Washington	260	(2)
Minitab Applications	262	(3)
Excel Applications	265	(2)
References	267	(2)
Multiple Regression Analysis	269	(58)
Several Predictor Variables	269	(1)
Correlation Matrix	270	(1)
Multiple Regression Model	271	(2)
Statistical Model for Multiple Regression	271	(2)
Interpreting Regression Coefficients	273	(1)
Inference for Multiple Regression Models	274	(6)
Standard Error of the Estimate	275	(1)
Significance of the Regression	276	(2)
Individual Predictor Variables	278	(1)
Forecast of a Future Response	279	(1)
Computer Output	280	(1)
Dummy Variables	281	(4)
Multicollinearity	285	(3)
Selecting the ``Best'' Regression Equation	288	(7)
All Possible Regressions	290	(2)
Stepwise Regression	292	(2)
Final Notes on Stepwise Regression	294	(1)
Regression Diagnostics and Residual Analysis	295	(2)
Forecasting Caveats	297	(1)
Overfitting	297	(1)
Useful Regressions, Large F Ratios	298	(1)
Application to Management	298	(2)
Glossary	300	(1)
Key Formulas	300	(1)
Problems	301	(9)
Case 7-1: The Bond Market	310	(3)
Case 7-2: AAA Washington	313	(2)
Case 7-3: Fantasy Baseball (A)	315	(5)
Case 7-4: Fantasy Baseball (B)	320	(4)
Minitab Applications	324	(2)
Excel Applications	326	(1)
References	326	(1)
Regression with Time Series Data	327	(54)
Time Series Data and the Problem of Autocorrelation	327	(4)
Durbin-Watson Test for Serial Correlation	331	(3)
Solutions to Autocorrelation Problems	334	(12)
Model Specification Error (Omitting a Variable)	335	(2)
Regression with Differences	337	(5)
Autocorrelated Errors and Generalized Differences	342	(3)
Autoregressive Models	345	(1)
Time Series Data and the Problem of Heteroscedasticity	346	(3)
Using Regression to Forecast Seasonal Data	349	(3)
Econometric Forecasting	352	(1)
Application to Management	353	(1)
Glossary	353	(1)
Key Formulas	353	(2)
Problems	355	(7)
Case 8-1: Company of Your Choice	362	(1)
Case 8-2: Business Activity Index for Spokane county	363	(4)
Case 8-3: Restaurant Sales	367	(2)
Case 8-4: Mr. Tux	369	(2)
Case 8-5: Consumer Credit Counseling	371	(1)
Case 8-6: AAA Washington	372	(3)
Case 8-7: Alomega Food Stores	375	(1)
Minitab Applications	376	(1)
Excel Applications	377	(2)
References	379	(2)
The Box-Jenkins (ARIMA) Methodology	381	(82)
Box-Jenkins Methodology	381	(8)
Autoregressive Models	386	(1)
Moving Average Models	387	(1)
Autoregressive Moving Average Models	388	(1)
Summary	389	(1)
Implementing the Model-Building Strategy	389	(39)
Step 1: Model Identification	389	(2)
Step 2: Model Estimation	391	(1)
Step 3: Model Checking	392	(1)
Step 4: Forecasting with the Model	392	(19)
Final Comments	411	(1)
Model Selection Criteria	412	(2)
Models for Seasonal Data	414	(10)
Simple Exponential Smoothing and an ARIMA Model	424	(2)
Advantages and Disadvantages of ARIMA Models	426	(2)
Application to Management	428	(1)
Glossary	429	(1)
Key Formulas	429	(1)
Problems	430	(10)
Case 9-1: Restaurant Sales	440	(2)
Case 9-2: Mr. Tux	442	(2)
Case 9-3: Consumer Credit Counseling	444	(1)
Case 9-4: The Lydia E. Pinkham Medicine Company	444	(3)
Case 9-5: City of College Station	447	(3)
Case 9-6: UPS Air Finance Division	450	(3)
Case 9-7: AAA Washington	453	(2)
Minitab Applications	455	(2)
Excel Applications: CB Predictor	457	(3)
References	460	(3)
Judgmental Forecasting and Forecast Adjustments	463	(22)
The Delphi Method	464	(3)
Scenario Writing	467	(1)
Combining Forecasts	468	(2)
Forecasting and Neural Networks	470	(2)
Summary of Judgmental Forecasting	472	(1)
Other Tools Useful in Making Judgments About the Future	473	(4)
Key Formulas	477	(1)
Problems	478	(1)
Case 10-1: Golden Gardens Restaurant	478	(1)
Case 10-2: Alomega Food Stores	479	(1)
Case 10-3: The Lydia E. Pinkham Medicine Company Revisited	480	(2)
References	482	(3)
Managing the Forecasting Process	485	(18)
The Forecasting Process	485	(1)
Monitoring Forecasts	486	(5)
Forecasting Steps Reviewed	491	(1)
Forecasting Responsibility	492	(1)
Forecasting Costs	493	(1)
Forecasting and the MIS System	493	(1)
Selling Management on Forecasting	494	(1)
The Future of Forecasting	494	(1)
Problems	495	(1)
Case 11-1: Boundary Electronics	495	(1)
Case 11-2: Busby Associates	496	(3)
Case 11-3: Consumer Credit Counseling	499	(1)
Case 11-4: Mr. Tux	500	(1)
Case 11-5: Alomega Food Stores	501	(1)
References	501	(2)
APPENDIX A Derivations	503	(2)
Correlation Derivation	503	(1)
Least Squares Derivation	503	(1)
Partial Derivatives	503	(2)
APPENDIX B Data for Case 7-1	505	(2)
APPENDIX C Tables	507	(10)
Table C-1 Individual Terms of the Binomial Distribution	507	(2)
Table C-2 Table of Areas for Standard Normal Probability Distribution	509	(1)
Table C-3 Critical Values of t	510	(1)
Table C-4 Critical Values of Chi-Square	511	(2)
Table C-5 Table of F Distribution	513	(1)
Table C-6 Durbin-Watson Test Bounds	514	(3)
APPENDIX D Data Sets and Databases	517	(14)
Index	531