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American Poems: Books: Predictive Analytics: Microsoft Excel
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 Home » Books » Predictive Analytics: Microsoft Excel

Predictive Analytics: Microsoft Excel

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  • Sales Rank:44,543
  • Format:Kindle eBook
  • Language:English (Published)
  • Media:Kindle Edition
  • Edition:1
  • Pages:304
  • Publication Date:July 2, 2012
  • ASIN:B008JWQ8CA

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Synopsis

Excel predictive analytics for serious data crunchers!

 

The movie Moneyball made predictive analytics famous: Now you can apply the same techniques to help your business win. You don’t need multimillion-dollar software: All the tools you need are available in Microsoft Excel, and all the knowledge and skills are right here, in this book!

 

Microsoft Excel MVP Conrad Carlberg shows you how to use Excel predictive analytics to solve real-world problems in areas ranging from sales and marketing to operations. Carlberg offers unprecedented insight into building powerful, credible, and reliable forecasts, showing how to gain deep insights from Excel that would be difficult to uncover with costly tools such as SAS or SPSS.

 

You’ll get an extensive collection of downloadable Excel workbooks you can easily adapt to your own unique requirements, plus VBA code—much of it open-source—to streamline several of this book’s most complex techniques.

 

Step by step, you’ll build on Excel skills you already have, learning advanced techniques that can help you increase revenue, reduce costs, and improve productivity. By mastering predictive analytics, you’ll gain a powerful competitive advantage for your company and yourself.

 

   •   Learn both the “how” and “why” of using data to make better tactical decisions

   •   Choose the right analytics technique for each problem

   •   Use Excel to capture live real-time data from diverse sources, including third-party websites

   •   Use logistic regression to predict behaviors such as “will buy” versus “won’t buy”

   •   Distinguish random data bounces from real, fundamental changes

   •   Forecast time series with smoothing and regression

   •   Construct more accurate predictions by using Solver to find maximum likelihood estimates

   •   Manage huge numbers of variables and enormous datasets with principal components analysis and Varimax factor rotation

   •   Apply ARIMA (Box-Jenkins) techniques to build better forecasts and understand their meaning

  

 

 


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