Business Applications of Multiple Regression

Business Applications of Multiple Regression

by Ronny Richardson
Released August 2011
Publisher(s): Business Expert Press
ISBN: 9781606492321

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Book description

A basic understanding of multiple regression is helpful in carrying out good business practices--specifically in the areas of demand management and data analysis. This book on correlation and regression analysis will have a non-mathematical, applied, data-analytic approach. Readers will benefit from its practitioner language and frequent use of examples. Multiple regression is at the heart of business data analysis because it deals with explanations of why data behaves the way it does and correlations demonstrating this behavior. The applied emphasis of the book provides clear illustrations of these principles and offers complete examples of the types of applications that are possible, including how to arrive at basic forecasts when the absence of historical data makes more sophisticated forecasting techniques impossible, and how to carry out elementary data mining, which can be done using only Excel, without reliance on more specialized data mining software. Students and business readers will learn how to specify regression models that directly address their questions.

Table of contents

  1. Business Applications of Multiple Regression
    1. Copyright
    2. Abstract
    3. Keywords
    4. Introduction
    5. Chapter 1: Correlation Analysis
      1. Terms
      2. Scatterplots
      3. Data Sets
      4. Public Transportation Ridership
      5. Correlation
      6. Some Correlation Examples
      7. Correlation Coefficient Hypothesis Testing¹¹ (1/3)
      8. Correlation Coefficient Hypothesis Testing¹¹ (2/3)
      9. Correlation Coefficient Hypothesis Testing¹¹ (3/3)
      10. Summary
    6. Chapter 2: Simple Regression
      1. Age and Tag Numbers (1/2)
      2. Age and Tag Numbers (2/2)
      3. Federal Civilian Workforce Statistics
      4. Number of Broilers (1/2)
      5. Number of Broilers (2/2)
      6. Some Final Thoughts on Simple Regression
    7. Chapter 3: Multiple Regression
      1. Multiple Regression as Several Simple Regression Runs
      2. Multiple Regression (1/3)
      3. Multiple Regression (2/3)
      4. Multiple Regression (3/3)
      5. The F-Test on a Multiple Regression Model
      6. How Good Is the Fit? (1/2)
      7. How Good Is the Fit? (2/2)
      8. Testing the Significance of the Individual Variables in the Model (1/2)
      9. Testing the Significance of the Individual Variables in the Model (2/2)
      10. Conclusion
    8. Chapter 4: Model Building
      1. Partial F-Test (1/3)
      2. Partial F-Test (2/3)
      3. Partial F-Test (3/3)
      4. Model Building Using Excel (1/4)
      5. Model Building Using Excel (2/4)
      6. Model Building Using Excel (3/4)
      7. Model Building Using Excel (4/4)
      8. Including Qualitative Data in Multiple Regression (1/4)
      9. Including Qualitative Data in Multiple Regression (2/4)
      10. Including Qualitative Data in Multiple Regression (3/4)
      11. Including Qualitative Data in Multiple Regression (4/4)
      12. Testing the Validity of the Regression Model (1/6)
      13. Testing the Validity of the Regression Model (2/6)
      14. Testing the Validity of the Regression Model (3/6)
      15. Testing the Validity of the Regression Model (4/6)
      16. Testing the Validity of the Regression Model (5/6)
      17. Testing the Validity of the Regression Model (6/6)
      18. Summary
    9. Notes
      1. Introduction
      2. Chapter 1
      3. Chapter 2
      4. Chapter 3
      5. Chapter 4
    10. Index (1/2)
    11. Index (2/2)

Product information

  • Title: Business Applications of Multiple Regression
  • Author(s): Ronny Richardson
  • Release date: August 2011
  • Publisher(s): Business Expert Press
  • ISBN: 9781606492321