Regression Analysis Microsoft Excel

Taschenbuch, Sprache: Englisch
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Produktdetails  
Verlag Pearson Education
Auflage 2024
Seiten 368
Format 17,5 x 22,9 x 2,3 cm
Gewicht 594 g
Artikeltyp Englisches Buch
EAN 9780789756558
Bestell-Nr 78975655EA

Produktbeschreibung  

        

This is today s most complete guide to regression analysis with Microsoft® Excel for any business analytics or research task. Drawing on 25 years of advanced statistical experience, Microsoft MVP Conrad Carlberg shows how to use Excel s regression-related worksheet functions to perform a wide spectrum of practical analyses.


Carlberg clearly explains all the theory you ll need to avoid mistakes, understand what your regressions are really doing, and evaluate analyses performed by others. From simple correlations and t-tests through multiple analysis of covariance, Carlberg offers hands-on, step-by-step walkthroughs using meaningful examples.

 

He discusses the consequences of using each option and argument, points out idiosyncrasies and controversies associated with Excel s regression functions, and shows how to use them reliably in fields ranging from medical research to financial analysis to operations.

 

You don t need expensive software or a doctorate in statistics to work with regression analyses. Microsoft Excel has all the tools you need and this book has all the knowledge!

 

  • Understand what regression analysis can and can t do, and why
  • Master regression-based functions built into all recent versions of Excel
  • Work with correlation and simple regression
  • Make the most of Excel s improved LINEST() function
  • Plan and perform multiple regression
  • Distinguish the assumptions that matter from the ones that don t
  • Extend your analysis options by using regression instead of traditional analysis of variance
  • Add covariates to your analysis to reduce bias and increase statistical power

 

Inhaltsverzeichnis:

  • 1 Measuring Variation: How Values Differ
  • 2 Correlation
  • 3 Simple Regression
  • 4 Using the LINEST( ) Function
  • 5 Multiple Regression
  • 6 Assumptions and Cautions Regarding Regression Analysis
  • 7 Using Regression to Test Differences Between Group Means

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