Discover everything you need to prepare for success in business statistics today with this advanced, case-based approach to regression analysis. You’ll begin by reviewing basic probability before moving into a strong topical coverage of hypothesis testing and regression analysis with an emphasis on relevant examples, business cases, and applications. Leading Harvard Business School cases and numerous end-of-chapter cases and problems written by the authors illustrate the use of statistics and regression analysis in business today.
Table of Contents
1. Introduction to Probability Distributions: The Double E Case.
2. Hypothesis Testing: The Consumer Packaging Case.
3. Introduction to Regression: The Autorama Case.
4. Using Regression: The CAPM and Newspaper Cases.
Case Insert 1 The Refrigerator Pricing Case: Introduction to Multiple Regression.
5. Dummy and Slope-Dummy Variables: The California Strawberries and CEO Seek Cases.
6. Graphical Analysis, Non-Linear Regression and Spurious Correlation: The Forestier Wine Case, Snowfall and Unemployment.
7. Multiple Regression, Multicollinearity and the Generalized F-test: The Hot Dog Case.
Case Insert 2 Colonial Broadcasting: Multiple Regression and Omitted Variable Bias.
8. Non-Linear Regression, Logarithms and Heteroskedasticity: An Advertising Example, The Hot Dog Case Revisited.
9. Time and Seasonality in Multiple Regression: The Dada Soda and Harmon Foods Cases.
Case Insert 3 Nopane Advertising Case: Multiple Regression and Interaction Variables.
Case Insert 4 The Wrigley Case: Multiple Regression and Modeling.
A Kstat Mini-Manual.
Simple Properties Of Logarithms.