Verfügbarkeit: Business forecasting | Technische Universität München

Business forecasting:

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Bibliographische Detailangaben
Beteiligte Personen:	Hanke, John E. (VerfasserIn), Reitsch, Arthur G. (VerfasserIn), Wichern, Dean W. (VerfasserIn)
Format:	Buch
Sprache:	Englisch
Veröffentlicht:	Upper Saddle River, NJ Prentice Hall 2001
Ausgabe:	7. ed.
Schlagwörter:	Bedrijfsleven Prognoses Pronóstico de los negocios Prévision commerciale Tijdreeksen Business forecasting Statistik Prognose Management Prognoseverfahren
Links:	http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=009317544&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
Umfang:	XIV, 498 S. graph. Darst.
ISBN:	0130878103

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Datensatz im Suchindex

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adam_text	Contents Preface xiii CHAPTER 1 Introduction to Forecasting 1 History of Forecasting 1 Need for Forecasting 1 Types of Forecasts 3 Macroeconomic Forecasting 4 Choosing a Forecasting Method 4 Forecasting Steps 4 Managing the Forecasting Process 6 Computer Forecasting Packages 6 Forecasting Example 7 Summary 8 Case Study 1.1: Mr. Tux 9 Case Study 1.2: Consumer Credit Counseling 9 Minitab Applications 10 Excel Applications 11 References and Selected Bibliography 12 CHAPTER 2 A Review of Basic Statistical Concepts 13 Describing Data with Numerical Summaries 13 Displays of Numerical Information 17 Probability Distributions 20 Sampling Distributions 23 Inference from a Sample 25 Estimation 25 Hypothesis Testing 26 V Correlation Analysis 29 Scatter Diagrams 29 Correlation Coefficient 32 Fitting a Straight Line 34 Assessing Normality 38 Application to Management 39 Glossary 40 Key Formulas 40 Problems 41 Case Study 2.1: Alcam Electronics 46 Case Study 2.2: Mr. Tux 47 Case Study 2.3: Alomega Food Stores 48 Minitab Applications 49 Excel Applications 51 References and Selected Bibliography 52 CHAPTER 3 Exploring Data Patterns and Choosing a Forecasting Technique 53 Exploring Time Series Data Patterns 54 Exploring Data Patterns with Autocorrelation Analysis 56 Are the Data Random? 61 Do the Data Have a Trend? 62 Are the Data Seasonal? 68 Choosing a Forecasting Technique 69 Forecasting Techniques for Stationary Data 70 Forecasting Techniques for Data with a Trend 71 Forecasting Techniques for Data with Seasonality 71 Forecasting Techniques for Cyclical Series 72 Other Factors to Consider When Choosing a Forecasting Technique 72 Empirical Evaluation of Forecasting Methods 73 Measuring Forecasting Error 74 Determining the Adequacy of a Forecasting Technique 77 Application to Management 78 Glossary 79 Key Formulas 80 Problems 81 Case Study 3.1: Murphy Brothers Furniture 85 Case Study 3.2: Mr. Tux 87 Case Study 3.3: Consumer Credit Counseling 88 Case Study 3.4: Alomega Food Stores 89 Minitab Applications 89 Excel Applications 91 References and Selected Bibliography 93 vi CHAPTER 4 Moving Averages and Smoothing Methods 95 Naive Models 96 Forecasting Methods Based on Averaging 99 Simple Averages 99 Moving Averages 101 Double Moving Averages 104 Exponential Smoothing Methods 107 Exponential Smoothing Adjusted for Trend: Holt s Method 114 Exponential Smoothing Adjusted for Trend and Seasonal Variation: Winters Method 117 Application to Management 123 Glossary 124 Key Formulas 124 Problems 126 Case Study 4.1: The Solar Alternative Company 131 Case Study 4.2: Mr. Tux 132 Case Study 4.3: Consumer Credit Counseling 133 Case Study 4.4: Five Year Revenue Projection for Downtown Radiology 133 Minitab Applications 139 Excel Applications 141 References and Selected Bibliography 142 CHAPTER 5 Time Series and Their Components 143 Decomposition 144 Trend 147 Additional Trend Curves 150 Forecasting Trend 153 Seasonality 153 Seasonally Adjusted Data 158 Cyclical and Irregular Variations 158 Forecasting a Seasonal Time Series 164 The Census II Decomposition Method 165 Application to Management 167 Appendix: Price Index 168 Glossary 170 Key Formulas 170 Problems 171 Case Study 5.1: The Small Engine Doctor 178 Case Study 5.2: Mr. Tux 179 Case Study 5.3: Consumer Credit Counseling 183 Case Study 5.4: AAA Washington 183 vii Case Study 5.5: Alomega Food Stores 185 Minitab Applications 187 Excel Applications 189 References and Selected Bibliography 192 CHAPTER 6 Simple Linear Regression 193 Regression Line 193 Standard Error of the Estimate 198 Forecasting Y 199 Decomposition of Variance 202 Coefficient of Determination 205 Hypothesis Testing 208 Analysis of Residuals 210 Computer Output 213 Variable Transformations 215 Application to Management 219 Glossary 221 Key Formulas 221 Problems 222 Case Study 6.1: Tiger Transport 231 Case Study 6.2: Butcher Products, Inc. 232 Case Study 6.3: Ace Manufacturing 234 Case Study 6.4: Mr. Tux 235 Case Study 6.5: Consumer Credit Counseling 235 Minitab Applications 236 Excel Applications 238 References and Selected Bibliography 240 CHAPTER 7 Multiple Regression Analysis 241 Several Predictor Variables 241 Correlation Matrix 242 Multiple Regression Model 243 Statistical Model for Multiple Regression 244 Interpreting Regression Coefficients 245 Inference for Multiple Regression Models 246 Standard Error of the Estimate 247 Significance of the Regression 248 Individual Predictor Variable 250 Forecast of a Future Response 251 Computer Output 251 Dummy Variables 252 Multicollinearity 256 viii Selecting the Best Regression Equation 259 All Possible Regressions 261 Stepwise Regression 263 Final Notes on Stepwise Regression 266 Regression Diagnostics and Residual Analysis 266 Forecasting Caveats 268 Overfitting 268 Useful Regressions, Large F Ratios 269 Application to Management 269 Glossary 271 Key Formulas 271 Problems 272 Case Study 7.1: The Bond Market 280 Case Study 7.2: Fantasy Baseball (A) 282 Case Study 7.3: Fantasy Baseball (B) 288 Minitab Applications 291 Excel Applications 292 References and Selected Bibliography 293 CHAPTER 8 Regression with Time Series Data 294 Time Series Data and the Problem of Autocorrelation 294 Durbin Watson Test for Serial Correlation 298 Solutions to Autocorrelation Problems 301 Model Specification Error (Omitting a Variable) 302 Regression with Differences 304 Generalized Differences and an Iterative Approach 309 Autoregressive Models 312 Time Series Data and the Problem of Heteroscedasticity 313 Using Regression to Forecast Seasonal Data 316 Econometric Forecasting 319 Application to Management 320 Glossary 320 Key Formulas 320 Problems 322 Case Study 8.1: Company of Your Choice 329 Case Study 8.2: Business Activity Index for Spokane County 329 Case Study 8.3: Restaurant Sales 333 Case Study 8.4: Mr. Tux 335 Case Study 8.5: Consumer Credit Counseling 337 Case Study 8.6: AAA Washington 339 Case Study 8.7: Alomega Food Stores 341 Minitab Applications 342 ix Excel Applications 343 References and Selected Bibliography 345 CHAPTER 9 The Box Jenkins (ARIMA) Methodology 346 Box Jenkins Methodology 346 Autoregressive Models 351 Moving Average Models 352 Autoregressive Moving Average Models 354 Summary 354 Implementing the Model Building Strategy 354 Step 1: Model Identification 354 Step 2: Model Estimation 356 Step 3: Model Checking 357 Step 4: Forecasting with the Model 358 Final Comments 377 Model Selection Criteria 377 Models for Seasonal Data 379 Simple Exponential Smoothing and an ARIMA Model 391 Advantages and Disadvantages of ARIMA Models 391 Application to Management 392 Glossary 393 Key Formulas 393 Problems 394 Case Study 9.1: Restaurant Sales 404 Case Study 9.2: Mr. Tux 405 Case Study 9.3: Consumer Credit Counseling 407 Case Study 9.4: The Lydia E. Pinkham Medicine Company 407 Case Study 9.5: City of College Station 410 Case Study 9.6: UPS Air Finance Division 413 Minitab Applications 416 Excel Applications 418 References and Selected Bibliography 419 CHAPTER 10 Judgmental Elements in Forecasting 421 Growth Curves 422 The Delphi Method 424 Scenario Writing 425 Combining Forecasts 426 Forecasting and Neural Networks 427 Summary of Judgmental Forecasting 429 Other Techniques Useful in Forecasting 430 Key Formulas 433 X Case Study 10.1 Golden Gardens Restaurant 434 Case Study 10.2 The Lydia E. Pinkham Medicine Company Revisited 434 References and Selected Bibliography 437 CHAPTER 11 Managing the Forecasting Process 438 The Forecasting Process 438 Monitoring Forecasts 439 Forecasting Steps Reviewed 443 Forecasting Responsibility 444 Forecasting Costs 445 Forecasting and the MIS System 445 Selling Management on Forecasting 446 The Future of Forecasting 446 Case Study 11.1: Boundary Electronics 447 Case Study 11.2: Busby Associates 447 Case Study 11.3: Consumer Credit Counseling 451 Case Study 11.4: Mr. Tux 452 Case Study 11.5: Alomega Food Stores 453 References and Selected Bibliography 454 APPENDIX A Derivations 457 APPENDIX B Data for Case Study 7.1 459 APPENDIX C Tables 461 APPENDIX D Data Sets and Databases 472 Index 493 xi
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spellingShingle	Hanke, John E. Reitsch, Arthur G. Wichern, Dean W. Business forecasting Bedrijfsleven gtt Prognoses gtt Pronóstico de los negocios Prévision commerciale Tijdreeksen gtt Business forecasting Statistik (DE-588)4056995-0 gnd Prognose (DE-588)4047390-9 gnd Management (DE-588)4037278-9 gnd Prognoseverfahren (DE-588)4358095-6 gnd
subject_GND	(DE-588)4056995-0 (DE-588)4047390-9 (DE-588)4037278-9 (DE-588)4358095-6
title	Business forecasting
title_auth	Business forecasting
title_exact_search	Business forecasting
title_full	Business forecasting John E. Hanke ; Arthur G. Reitsch ; Dean W. Wichern
title_fullStr	Business forecasting John E. Hanke ; Arthur G. Reitsch ; Dean W. Wichern
title_full_unstemmed	Business forecasting John E. Hanke ; Arthur G. Reitsch ; Dean W. Wichern
title_short	Business forecasting
title_sort	business forecasting
topic	Bedrijfsleven gtt Prognoses gtt Pronóstico de los negocios Prévision commerciale Tijdreeksen gtt Business forecasting Statistik (DE-588)4056995-0 gnd Prognose (DE-588)4047390-9 gnd Management (DE-588)4037278-9 gnd Prognoseverfahren (DE-588)4358095-6 gnd
topic_facet	Bedrijfsleven Prognoses Pronóstico de los negocios Prévision commerciale Tijdreeksen Business forecasting Statistik Prognose Management Prognoseverfahren
url	http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=009317544&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
work_keys_str_mv	AT hankejohne businessforecasting AT reitscharthurg businessforecasting AT wicherndeanw businessforecasting

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