About the Book
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 Baseball Case: Multiple Regression and Modeling Appendices. A Kstat Mini-Manual. Prediction Intervals. Correlation Review. Simple Properties Of Logarithms.
About the Author :
Alvaro Sandroni is an Associate Professor from J.L. Kellogg Graduate School of Management, Department of Managerial Economics and Decision Sciences, Northwestern University, Evanston, Illinois. Alvaro is currently an Associate Professor, Department of Economics, University of Rochester. He completed his Ph.D. in Economics at the University of Pennsylvania as well as a Ph.D. in mathematics at the Instituto de Matematica Pura e Aplicada, Brazil. He has had articles published in Econometrica, Games & Economic Behavior, International Journal of Game Theory, and Journal of Econometric Theory. Since 1998 he has received research grants from the following organizations: National Science Foundation, Bi-National Science Foundation (US-Israel), & Bergmann Memorial Research Grant. He received the following honors while attending the University of Pennsylvania: 1997 ' William Polk Cary Prize in Economics for Best Ph.D. Dissertation, 1996 ' Dean's Scholar, and 1995 ' Hiram C. Haney Fellowship Award in Economics. Boaz Moselle is a former Assistant Professor of Managerial Economics and Decisions Sciences at the Kellogg Graduate School of Management, Northwestern University, Evanston, Illinois. He is currently Managing Director Corporate Strategy, OFGEM (Office of Gas and Electricity Markets), London, UK.. Brett Saraniti holds a Ph.D. in Managerial Economics and Decision Sciences from the Kellogg Graduate School of Management, Northwestern University, Evanston, Illinois. He is currently an Associate Professor of Economics at Hawaii Pacific University, Honolulu, Hawaii. He spends each summer teaching as a visiting professor. He has also held visiting teaching positions at the Sasin Graduate Institute of Business, Bangkok and the Helsinki School of Economics and Business Administration. His primary teaching interests are in quantitative methods and industrial organization. Peter Klibanoff is currently Associate Professor of Managerial Economics and Decision Sciences with tenure at the Kellogg Graduate School of Management, Northwestern University, Evanston, Illinois. He completed his Ph.D. in economics at Massachusetts Institute of Technology. The title of his dissertation is 'Essays on Uncertainty in Economics.' He also holds a Bachelor of Arts degree in applied mathematics from Harvard University, where he graduated summa cum laude. He has had articles published in The Journal of Economic Theory, Economic Theory, Journal of Mathematical Economics, The Journal of Finance, and The Review of Economic Studies. He has presented his recent research at approximately 25 conferences and universities in both the USA and globally. He is currently a referee on the following journals: American Economic Review, Canadian Journal of Economics, Econometrica, Economic Theory, European Economic Review, Games & Economic Behavior, International Economic Review, Journal of Economic Behavior & Organization, Journal of Economic Theory, Journal of Mathematical Economics, Management Science, National Science Foundation, Quarterly Journal of Economics, RAND Journal of Economics, Review of Economic Studies, Social Choice and Welfare, & Theory and Decision. He currently holds professional memberships in the following organizations: American Economic Association, The Econometric Society, and Society for the Promotion of Economic Theory.
Review :
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. Appendices. A Kstat Mini-Manual. Prediction Intervals. Correlation Review. Simple Properties Of Logarithms.
