Predictive Analytics: Microsoft® Excel 2016

Author:   Conrad Carlberg
Publisher:   Pearson Education (US)
Edition:   2nd edition
ISBN:  

9780789758354


Pages:   384
Publication Date:   10 August 2017
Format:   Paperback
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

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Predictive Analytics: Microsoft® Excel 2016


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Overview

Microsoft Excel MVP Conrad Carlberg shows readers 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.   Readers will get an extensive collection of downloadable Excel workbooks that can be easily adapted to their own unique requirements, plus VBA code—much of it open-source—to streamline several of this book’s most complex techniques.   Step by step, readers build on Excel skills they already have, learning advanced techniques that can help them increase revenue, reduce costs, and improve productivity.

Full Product Details

Author:   Conrad Carlberg
Publisher:   Pearson Education (US)
Imprint:   Que Corporation,U.S.
Edition:   2nd edition
Dimensions:   Width: 17.00cm , Height: 2.00cm , Length: 22.00cm
Weight:   0.400kg
ISBN:  

9780789758354


ISBN 10:   0789758350
Pages:   384
Publication Date:   10 August 2017
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

1 Building a Collector 2 Linear Regression 3 Forecasting with Moving Averages 4 Forecasting a Time Series: Smoothing 5 More Advanced Smoothing Models 6 Forecasting a Time Series: Regression 7 Logistic Regression: The Basics 8 Logistic Regression: Further Issues  9 Multinomial Logistic Regression 10 Principal Components Analysis 11 Box-Jenkins ARIMA Models 12 Varimax Factor Rotation in Excel

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Author Information

Conrad Carlberg is a nationally recognised expert on quantitative analysis and on data analysis and management applications such as Microsoft Excel, SAS, and Oracle. He holds a Ph.D. in statistics from the University of Colorado and is a many-time recipient of Microsoft’s Excel MVP designation. Carlberg is a Southern California native. After college he moved to Colorado, where he worked for a succession of startups and attended graduate school. He spent two years in the Middle East, teaching computer science and dodging surly camels. After finishing graduate school, Carlberg worked at US West (a Baby Bell) in product management and at Motorola. In 1995, he started a small consulting business that provides design and analysis services to companies that want to guide their business decisions by means of quantitative analysis—approaches that today we group under the term “analytics.” He enjoys writing about those techniques and, in particular, how to carry them out using the world’s most popular numeric analysis application, Microsoft Excel.

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