This is completed downloadable of Solution Manual for Business Forecasting, 9/E 9th Edition John E. Hanke, Dean Wichern
Product Details:
- ISBN-10 ‏ : ‎ 0132301202
- ISBN-13 ‏ : ‎ 978-0132301206
- Author: John E. Hanke, Dean Wichern
Written in a simple, straightforward style, Business Forecasting, 9th Edition presents basic statistical techniques using practical business examples to teach readers how to predict long-term forecasts.
Table of Content:
- CHAPTER 1 Introduction to Forecasting
- The History of Forecasting
- Is Forecasting Necessary?
- Types of Forecasts
- Macroeconomic Forecasting Considerations
- Choosing a Forecasting Method
- Forecasting Steps
- Managing the Forecasting Process
- Forecasting Software
- Online Information
- Forecasting Examples
- Summary
- Case 1-1: Mr. Tux
- Case 1-2: Consumer Credit Counseling
- Minitab Applications
- Excel Applications
- References
- CHAPTER 2 A Review of Basic Statistical Concepts
- Describing Data with Numerical Summaries
- Displays of Numerical Information
- Probability Distributions
- Sampling Distributions
- Inference from a Sample
- Estimation
- Hypothesis Testing
- p-Value
- Correlation Analysis
- Scatter Diagrams
- Correlation Coefficient
- Fitting a Straight Line
- Assessing Normality
- Application to Management
- Glossary
- Key Formulas
- Problems
- Case 2-1: Alcam Electronics
- Case 2-2: Mr. Tux
- Case 2-3: Alomega Food Stores
- Minitab Applications
- Excel Applications
- References
- CHAPTER 3 Exploring Data Patterns and an Introduction to Forecasting Techniques
- Exploring Time Series Data Patterns
- Exploring Data Patterns with Autocorrelation Analysis
- Are the Data Random?
- Do the Data Have a Trend?
- Are the Data Seasonal?
- Choosing a Forecasting Technique
- Forecasting Techniques for Stationary Data
- Forecasting Techniques for Data with a Trend
- Forecasting Techniques for Seasonal Data
- Forecasting Techniques for Cyclical Series
- Other Factors to Consider When Choosing a Forecasting Technique
- Empirical Evaluation of Forecasting Methods
- Measuring Forecast Error
- Determining the Adequacy of a Forecasting Technique
- Application to Management
- Glossary
- Key Formulas
- Problems
- Case 3-1A: Murphy Brothers Furniture
- Case 3-1B: Murphy Brothers Furniture
- Case 3-2: Mr. Tux
- Case 3-3: Consumer Credit Counseling
- Case 3-4: Alomega Food Stores
- Case 3-5: Surtido Cookies
- Minitab Applications
- Excel Applications
- References
- CHAPTER 4 Moving Averages and Smoothing Methods
- Naive Models
- Forecasting Methods Based on Averaging
- Simple Averages
- Moving Averages
- Double Moving Averages
- Exponential Smoothing Methods
- Exponential Smoothing Adjusted for Trend: Holt’s Method
- Exponential Smoothing Adjusted for Trend and Seasonal Variation:Winter’s Method
- Application to Management
- Glossary
- Key Formulas
- Problems
- Case 4-1: The Solar Alternative Company
- Case 4-2: Mr. Tux
- Case 4-3: Consumer Credit Counseling
- Case 4-4: Murphy Brothers Furniture
- Case 4-5: Five-Year Revenue Projection for Downtown Radiology
- Case 4-6: Web Retailer
- Case 4-7: Southwest Medical Center
- Case 4-8: Surtido Cookies
- Minitab Applications
- Excel Applications
- References
- CHAPTER 5 Time Series and Their Components
- Decomposition
- Trend
- Additional Trend Curves
- Forecasting Trend
- Seasonality
- Seasonally Adjusted Data
- Cyclical and Irregular Variations
- Summary Example
- Business Indicators
- Forecasting a Seasonal Time Series
- The Census II Decomposition Method
- Application to Management
- Appendix: Price Index
- Glossary
- Key Formulas
- Problems
- Case 5-1: The Small Engine Doctor
- Case 5-2: Mr. Tux
- Case 5-3: Consumer Credit Counseling
- Case 5-4: Murphy Brothers Furniture
- Case 5-5: AAA Washington
- Case 5-6: Alomega Food Stores
- Case 5-7: Surtido Cookies
- Case 5-8: Southwest Medical Center
- Minitab Applications
- Excel Applications
- References
- CHAPTER 6 Simple Linear Regression
- Regression Line
- Standard Error of the Estimate
- Forecasting Y
- Decomposition of Variance
- Coefficient of Determination
- Hypothesis Testing
- Analysis of Residuals
- Computer Output
- Variable Transformations
- Growth Curves
- Application to Management
- Glossary
- Key Formulas
- Problems
- Case 6-1: Tiger Transport
- Case 6-2: Butcher Products, Inc.
- Case 6-3: Ace Manufacturing
- Case 6-4: Mr. Tux
- Case 6-5: Consumer Credit Counseling
- Case 6-6: AAA Washington
- Minitab Applications
- Excel Applications
- References
- CHAPTER 7 Multiple Regression Analysis
- Several Predictor Variables
- Correlation Matrix
- Multiple Regression Model
- Statistical Model for Multiple Regression
- Interpreting Regression Coefficients
- Inference for Multiple Regression Models
- Standard Error of the Estimate
- Significance of the Regression
- Individual Predictor Variables
- Forecast of a Future Response
- Computer Output
- Dummy Variables
- Multicollinearity
- Selecting the “Best” Regression Equation
- All Possible Regressions
- Stepwise Regression
- Final Notes on Stepwise Regression
- Regression Diagnostics and Residual Analysis
- Forecasting Caveats
- Overfitting
- Useful Regression, Large F Ratios
- Application to Management
- Glossary
- Key Formulas
- Problems
- Case 7-1: The Bond Market
- Case 7-2: AAA Washington
- Case 7-3: Fantasy Baseball (A)
- Case 7-4: Fantasy Baseball (B)
- Minitab Applications
- Excel Applications
- References
- CHAPTER 8 Regression with Time Series Data
- Time Series Data and the Problem of Autocorrelation
- Autocorrelation and the Durbin-Watson Test
- Solutions to Autocorrelation Problems
- Model Specification Error (Omitting a Variable)
- Regression with Differences
- Autocorrelated Errors and Generalized Differences
- Autoregressive Models
- Summary
- Time Series Data and the Problem of Heteroscedasticity
- Using Regression to Forecast Seasonal Data
- Econometric Forecasting
- Cointegrated Time Series
- Application to Management
- Glossary
- Key Formulas
- Problems
- Case 8-1: Company of Your Choice
- Case 8-2: Business Activity Index for Spokane County
- Case 8-3: Restaurant Sales
- Case 8-4: Mr. Tux
- Case 8-5: Consumer Credit Counseling
- Case 8-6: AAA Washington
- Case 8-7: Alomega Food Stores
- Case 8-8: Surtido Cookies
- Case 8-9: Southwest Medical Center
- Minitab Applications
- Excel Applications
- References
- CHAPTER 9 The Box-Jenkins (ARIMA) Methodology
- Box-Jenkins Methodology
- Autoregressive Models
- Moving Average Models
- Autoregressive Moving Average Models
- Summary
- Implementing the Model-Building Strategy
- Step 1: Model Identification
- Step 2: Model Estimation
- Step 3: Model Checking
- Step 4: Forecasting with the Model
- Model-Building Caveats
- Model Selection Criteria
- ARIMA Models for Seasonal Data
- Simple Exponential Smoothing and an ARIMA Model
- Advantages and Disadvantages of ARIMA Models
- Application to Management
- Glossary
- Key Formulas
- Problems
- Case 9-1: Restaurant Sales
- Case 9-2: Mr. Tux
- Case 9-3: Consumer Credit Counseling
- Case 9-4: The Lydia E. Pinkham Medicine Company
- Case 9-5: City of College Station
- Case 9-6: UPS Air Finance Division
- Case 9-7: AAA Washington
- Case 9-8: Web Retailer
- Case 9-9: Surtido Cookies
- Case 9-10: Southwest Medical Center
- Minitab Applications
- References
- CHAPTER 10 Judgmental Forecasting and Forecast Adjustments
- Judgmental Forecasting
- The Delphi Method
- Scenario Writing
- Combining Forecasts
- Forecasting and Neural Networks
- Summary of Judgmental Forecasting
- Other Tools Useful in Making Judgments About the Future
- Key Formulas
- Problems
- Case 10-1: Golden Gardens Restaurant
- Case 10-2: Alomega Food Stores
- Case 10-3: The Lydia E. Pinkham Medicine Company
- References
- CHAPTER 11 Managing the Forecasting Process
- The Forecasting Process
- Monitoring Forecasts
- Forecasting Steps Reviewed
- Forecasting Responsibility
- Forecasting Costs
- Forecasting and Management Information Systems
- Selling Management on Forecasting
- The Future of Forecasting
- Problems
- Case 11-1: Boundary Electronics
- Case 11-2: Busby Associates
- Case 11-3: Consumer Credit Counseling
- Case 11-4: Mr. Tux
- Case 11-5: Alomega Food Stores
- Case 11-6: Southwest Medical Center
- References
- APPENDIX A: Data for Case 7-1
- APPENDIX B: Tables
- Table B-1 Individual Terms of the Binomial Distribution
- Table B-2 Areas for Standard Normal Probability Distribution
- Table B-3 Critical Values of t
- Table B-4 Critical Values of Chi-Square
- Table B-5 F Distribution
- Table B-6 Durbin-Watson Test Bounds
- APPENDIX C: Data Sets and Databases
- Index
- A
- B
- C
- D
- E
- F
- G
- H
- I
- J
- K
- L
- M
- N
- O
- P
- Q
- R
- S
- T
- U
- V
- W
- X
- Y
- Z
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