Managerial Statistics

A Case-based Approach

Peter Klibanoff, Alvaro Sandroni, Boaz Moselle, Brett Saraniti

250 pages, parution le 30/11/2005

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Résumé

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.

Sommaire

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

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Thomson
Auteur(s)	Peter Klibanoff, Alvaro Sandroni, Boaz Moselle, Brett Saraniti
Parution	30/11/2005
Nb. de pages	250
Format	20 x 25,5
Couverture	Broché
Poids	485g
Intérieur	Noir et Blanc
EAN13	9780324314465
ISBN13	978-0-324-31446-5