Business Analysis Using Regression

A Casebook

By: Dean P. Foster, Robert A. Stine, Richard P. Waterman

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Paperback | 1 August 2001

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368 Pages

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21.1 x 29.8 x 2.3

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Preface Statistics is seldom the most eagerly anticipated course of a business student. It typically has the reputation ofbeing aboring, complicated, and confusing mix of mathematical formulas and computers. Our goal in writing this casebook and the companion volume (Basic Business Statistics) was to change that impression by showing how statistics gives insights and answers interesting business questions. Rather than dwell on underlying formulas, we show how to use statistics to answer questions. Each case study begins with a business question and concludes with an answer. Formulas appear only as needed to address the questions, and we focus on the insights into the problem provided by the mathematics. The mathematics serves a purpose. The material is organized into 12 "classes" of related case studies that develop a single, key idea of statistics. The analysis of data using statistics is seldom very straightforward, and each analysis has many nuances. Part ofthe appeal ofstatistics is this richness, this blending of substantive theories and mathematics. For a newcomer, however, this blend is too rich and they are easily overwhelmed and unable to sort out the important ideas from nuances. Although later cases in these notes suggest this complexity, we do not begin that way. Each class has one main idea, something big like standard error. We begin a class by discussing an application chosen to motivate this key concept, and introduce the necessary terminology.

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You Can Find This Book In

Non-Fiction Sociology & Anthropology Sociology Social Research & Statistics Economics Econometrics Economic Statistics Mathematics Probability & Statistics Business & Management Business Mathematics & Systems Management & Management Techniques

Management Decision Making Computing & I.T.Graphical & Digital Media Applications 3D Graphics & Modelling

Fitting Equations to Data
Assumptions in Regression Modeling
Prediction and Confidence Intervals in Regression
Multiple Regression
Collinearity
Modeling Categorical Factors with Two or More Levels
Summary Regression Case
Comparing Many Mean Values
Analysis of Variance with Two Factors
Modeling a Categorical Response
Modeling Time Series
Table of Contents provided by Publisher. All Rights Reserved.

Business Analysis Using Regression

A Casebook

At a Glance

Paperback

Shipping

How to return your order

Defective items

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