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Predictive Analytics
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Predictive Analytics

Predictive Analytics

Conrad carlberg (author)

384 pages, parution le 23/07/2017

Résumé

Previous edition: 2013.

Introduction
Chapter 1 Building a Collector

Chapter 2 Linear Regression

Chapter 3 Forecasting with Moving Averages

Chapter 4 Forecasting a Time Series: Smoothing

Chapter 5 Forecasting a Time Series: Regression

Chapter 6 Logistic Regression: The Basics

Chapter 7 Logistic Regression: Further Issues

Chapter 8 Principal Components Analysis

Chapter 9 Box-Jenkins ARIMA Models

Chapter 10 Varimax Factor Rotation in Excel

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

  

Second editionHD30.27Business forecasting - Mathematical models.|Business forecasting - Data processing.1IndianaIndianapolisConrad Carlberg.

Caractéristiques techniques

  PAPIER
Éditeur(s) Que-wajskop (bruno)
Auteur(s) Conrad carlberg (author)
Parution 23/07/2017
Nb. de pages 384
Format 178 x 232
Poids 381g
EAN13 9780789758354

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