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Business Forecasting

ISBN: 9780137607457 | 0137607458
Edition: 6th
Format: Hardcover
Publisher: Prentice Hall
Pub. Date: 1/1/1998

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SummaryTable of Contents
Appropriate for junior/senior and graduate level courses in Forecasting found in Economics or Statistics departments. This top-selling text presents, in a straightforward, application-driven manner, the basic statistical techniques that are useful for preparing individual business forecasts and long-range plans. The emphasis is on the application of techniques by managers for decision-making.
... MORE
Prefacexv(2)
Acknowledgmentsxvii
1 INTRODUCTION TO FORECASTING
1(17)
History of Forecasting
1(1)
Need for Forecasting
2(2)
Types of Forecasts
4(1)
Macroeconomic Forecasting
4(1)
Choosing a Forecasting Method
5(1)
Forecasting Steps
6(1)
Managing the Forecasting Process
7(1)
Computer Forecasting Packages
8(1)
Summary
9(1)
Case Study 1.1: Mr. Tux
10(1)
Case Study 1.2: Consumer Credit Counseling
10(1)
Introduction to the Minitab Computer Package
11(1)
Forecasting Using Spreadsheets
12(1)
Appendix--Dedicated Forecasting Software
13(4)
Selected Bibliography
17(1)
2 A REVIEW OF BASIC STATISTICAL CONCEPTS
18(45)
Descriptive Statistics
18(3)
Probability Distributions
21(5)
Sampling Distributions
26(2)
Estimation
28(1)
Hypothesis Testing
29(5)
Goodness-of-Fit Test
34(2)
Correlation Analysis
36(8)
Scatter Diagrams
37(3)
Correlation Coefficient
40(4)
Application to Management
44(1)
Glossary
45(1)
Key Formulas
46(1)
Problems
47(5)
Case Study 2.1: Alcam Electronics
52(3)
Case Study 2.2: Mr. Tux
55(1)
Minitab Computer Package
56(3)
Forecasting Using Spreadsheets
59(2)
Selected Bibliography
61(2)
3 DATA SOURCES
63(25)
Introduction
63(1)
Data Types
64(1)
Data Sources
65(10)
Secondary Data Sources
66(1)
External Sources
66(1)
Private Data
66(3)
Primary Data Source
69(6)
Application to Management
75(2)
Glossary
77(1)
Problems
77(1)
Case Study 3.1: Argyl Food Products
78(3)
Case Study 3.2: Solomon's Jewelry
81(1)
Case Study 3.3: Mr. Tux
82(1)
Case Study 3.4: Consumer Credit Counseling
83(1)
Minitab Computer Package
84(2)
Forecasting Using Spreadsheets
86(1)
Selected Bibliography
87(1)
4 EXPLORING DATA PATTERNS AND CHOOSING A FORECASTING TECHNIQUE
88(48)
Time Series Components
89(2)
Exploring Data Patterns with Autocorrelation Analysis
91(15)
Choosing a Forecasting Technique
106(5)
Forecasting Techniques for Stationary Data
107(1)
Forecasting Techniques for Data with a Trend
108(1)
Forecasting Techniques for Data with Seasonality
108(1)
Forecasting Techniques for Cyclical Series
109(1)
Other Factors to Consider When Choosing a Forecasting Technique
110(1)
Measuring Forecasting Error
111(4)
Determining the Adequacy of a Forecasting Technique
115(1)
Application to Management
116(2)
Glossary
118(1)
Key Formulas
118(1)
Problems
119(5)
Case Study 4.1: Murphy Brothers Furniture
124(3)
Case Study 4.2: Mr. Tux
127(2)
Case Study 4.3: Consumer Credit Counseling
129(1)
Minitab Computer Package
130(2)
Forecasting Using Spreadsheets
132(3)
Bibliography
135(1)
5 MOVING AVERAGES AND SMOOOTHING METHODS
136(57)
Naive Models
137(4)
Averaging Methods
141(7)
Simple Averages
141(1)
Moving Averages
142(3)
Double Moving Average
145(3)
Exponential Smoothing Methods
148(14)
Tracking
154(2)
Double Exponential Smoothing
156(6)
Exponential Smoothing Adjusted for Trend: Holt's Method
162(3)
Exponential Smoothing Adjusted for Trend and Seasonal Variation: Winter's Model
165(5)
Application to Management
170(1)
Glossary
171(1)
Key Formulas
171(1)
Problems
172(5)
Case Study 5.1: The Solar Alternative Company
177(2)
Case Study 5.2: Mr. Tux
179(1)
Case Study 5.3: Consumer Credit Counseling
180(1)
Case Study 5.4: Five-Year Revenue Projection for Downtown Radiology
180(9)
Minitab Computer Package
189(1)
Forecasting Using Spreadsheets
190(2)
Selected Bibliography
192(1)
6 REGRESSION ANALYSIS
193(50)
Regression Line
195(3)
Standard Error of Estimate
198(1)
Predicting Y
199(4)
Coefficient of Determination
203(3)
Residuals
206(4)
Hypothesis Testing
210(3)
Computer Output
213(3)
Variable Transformations
216(2)
Application to Management
218(5)
Glossary
223(1)
Key Formulas
223(1)
Problems
224(7)
Case Study 6.1: Tiger Transport
231(3)
Case Study 6.2: Butcher Products, Inc.
234(2)
Case Study 6.3: Ace Personnel Department
236(1)
Case Study 6.4: Mr. Tux
237(1)
Case Study 6.5: Consumer Credit Counseling
238(1)
Minitab Computer Package
239(2)
Forecasting Using Spreadsheets
241(1)
Selected Bibliography
242(1)
7 MULTIPLE REGRESSION
243(59)
Predictor Variables
243(1)
Correlation Matrix
244(1)
Multiple Regression Equation
245(3)
Regression Coefficients
248(1)
Statistical Inference in Multiple Regression
249(1)
Residuals
250(2)
Standard Error of Estimate
252(1)
Computer Output
252(2)
Dummy Variables
254(4)
Validation of the Model
258(4)
Heteroscedasticity
259(1)
Collinearity
259(3)
Selecting the Best Regression Equation
262(10)
All Possible Regressions
265(2)
Stepwise Regression
267(5)
Final Notes on Stepwise Regression
272(1)
Using Regression to Forecast Seasonal Data
272(3)
Econometric Forecasting
275(2)
Overfitting
277(1)
Application to Management
277(2)
Glossary
279(1)
Key Formulas
279(1)
Problems
280(7)
Case Study 7.1: The Bond Market
287(3)
Case Study 7.2: Restaurant Sales
290(3)
Case Study 7.3: Mr. Tux
293(2)
Case Study 7.4: Consumer Credit Counseling
295(2)
Minitab Computer Package
297(1)
Forecasting Using Spreadsheets
298(3)
Selected Bibliography
301(1)
8 TIME SERIES ANALYSIS
302(55)
Decomposition
303(1)
Price Index
304(3)
Trend
307(3)
Trend Curves
310(3)
Cyclical Variation
313(7)
Long Term Forecasting
320(1)
Seasonal Variation
321(4)
Seasonal Adjusted Data
325(1)
Short-Term Components
326(6)
Seasonal Trend
326(1)
Cyclical and Irregular Variations
327(5)
Seasonal Forecasting
332(1)
The Census II Decomposition Method
333(1)
Application of Management
334(1)
Glossary
335(1)
Key Formulas
336(1)
Problems
336(5)
Case Study 8.1: The Small Engine Doctor
341(2)
Case Study 8.2: Mr. Tux
343(4)
Case Study 8.3: Consumer Credit Counseling
347(1)
Case Study 8.4: AAA Washington
348(2)
Minitab Computer Package
350(3)
Forecasting Using Spreadsheets
353(3)
Selected Bibliography
356(1)
9 REGRESSION OF TIME SERIES DATA
357(50)
The Problem of Heteroscedasticity When Regressing Time Series Data
357(1)
The Problem of Serial Correlation When Regressing Time Series Data
358(4)
Durbin-Watson Test for Serial Correlation
362(3)
Solutions to Serial Correlation Problems
365(15)
Model Specification Error (Omitting a Variable)
366(3)
Regression of Percentage Changes
369(5)
Autoregressive Models
374(1)
Generalized Least Squares
374(3)
First Differences
377(1)
Iterative Approach
377(3)
Application to Management
380(1)
Glossary
381(1)
Key Formulas
381(1)
Problems
382(6)
Case Study 9.1: Company of Your Choice
388(1)
Case Study 9.2: Business Activity Index for Spokane County
389(6)
Case Study 9.3: Mr. Tux
395(1)
Case Study 9.4: Consumer Credit Counseling
396(1)
Case Study 9.5: AAA Washington
397(3)
Minitab Computer Package
400(1)
Forecasting Using Spreadsheets
401(2)
TSP Example
403(3)
Selected Bibliography
406(1)
10 THE BOX-JENKINS (ARIMA) METHODOLOGY
407(87)
Box-Jenkins Technique
407(5)
Partial Autocorrelations
412(4)
Autoregressive Model
412(2)
Moving-Average Models
414(1)
Autoregressive Moving-Average Models
415(1)
Applying the Methodology
416(25)
Stage 1: Model Identification
416(1)
Stage 2: Model Estimation and Testing of Model Adequacy
416(2)
Stage 3: Forecasting with the Model
418(23)
A Seasonal Analysis
441(11)
Exponential Smoothing
452(1)
Advantages and Disadvantages
453(1)
Application to Management
454(2)
Glossary
456(1)
Key Formulas
456(1)
Problems
457(11)
Case Study 10.1: Restaurant Sales
468(1)
Case Study 10.2: Mr. Tux
469(2)
Case Study 10.3: Consumer Credit Counseling
471(1)
Case Study 10.4: The Lydia E. Pinkham Medicine Company
472(3)
Case Study 10.5: Daily Demand for Trout Tags
475(13)
Minitab Computer Package
488(2)
Forecasting Using Spreadsheets
490(3)
Selected Bibliography
493(1)
11 JUDGMENTAL ELEMENTS IN FORECASTING
494(38)
Judgmental Forecasting
494(4)
Growth Curves
496(1)
The Delphi Method
497(1)
Scenario Writing
497(1)
Combining Forecasts
498(1)
Forecasting and Neural Networks
499(2)
Summary of Judgmental Forecasting
501(1)
Other Judgmental Elements in Forecasting
502(5)
Managing the Forecasting Process
507(2)
The Forecasting Process
508(1)
Monitoring Forecasts
509(5)
Forecasting Steps Reviewed
514(1)
Forecasting Responsibility
515(1)
Forecasting Costs
516(1)
Selling Management on Forecasting
516(1)
Forecasting and the MIS System
517(1)
The Future of Forecasting
517(1)
Glossary
518(1)
Key Formula
518(1)
Case Study 11.1: Boundary Electronics
518(1)
Case Study 11.2: Golden Gardens Restaurant
519(1)
Case Study 11.3: Busby Associates
520(5)
Case Study 11.4: Mr. Tux
525(2)
Case Study 11.5: Consumer Credit Counseling
527(1)
Case Study 11.6: The Lydia E. Pinkham Medicine Company Revisited
527(4)
Selected Bibliography
531(1)
APPENDIXES532(1)
A DERIVATIONS533(2)
B DATA FOR CASE STUDY 7.1535(3)
C TABLES538(13)
D DATA SETS AND DATABASE551(24)
INDEX575

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