Buch, Englisch, 496 Seiten, Format (B × H): 207 mm x 261 mm, Gewicht: 1259 g
with Computer Application for Business and Economics
Buch, Englisch, 496 Seiten, Format (B × H): 207 mm x 261 mm, Gewicht: 1259 g
ISBN: 978-0-415-89932-1
Verlag: Taylor & Francis Ltd (Sales)
Taking into consideration current statistical technology, Introductory Regression Analysis focuses on the use and interpretation of software, while also demonstrating the logic, reasoning, and calculations that lie behind any statistical analysis. Furthermore, the text emphasizes the application of regression tools to real-life business concerns. This multilayered, yet pragmatic approach fully equips students to derive the benefit and meaning of a regression analysis.
This text is designed to serve in a second undergraduate course in statistics, focusing on regression and its component features. The material presented in this text will build from a foundation of the principles of data analysis. Although previous exposure to statistical concepts would prove helpful, all the material needed for an examination of regression analysis is presented here in a clear and complete form.
Autoren/Hrsg.
Fachgebiete
- Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsmathematik und -statistik
- Mathematik | Informatik EDV | Informatik Business Application Mathematische & Statistische Software
- Mathematik | Informatik EDV | Informatik Business Application Tabellenkalkulation Microsoft Excel
- Mathematik | Informatik Mathematik Mathematik Interdisziplinär Finanz- und Versicherungsmathematik
- Wirtschaftswissenschaften Betriebswirtschaft Unternehmensforschung
Weitere Infos & Material
1. Review of Basic Concepts 2. An Introduction to Regression and Correlation Analysis 3. Statistical Inferences in the Simple Regression Model 4. Multiple Regression: Using Two or More Predictor Variables 5. Residual Analysis and Model Specification 6. Using Qualitative and Limited Dependent Variables 7. Heteroscedasticity 8. Autocorrelation 9. Non-Linear Regression and the Selection of the Proper Functional Form 10. Simultaneous Equations: Two Stage Least Squares 11. Forecasting with Time Series Data and Distributed Lag Models