EXCEL 2016 PREDICTIVE ANALYTICS FOR SERIOUS DATA CRUNCHERS!
Now, you can apply cutting-edge predictive analytics techniques to help
your business win-and you don't need multimillion-dollar software to do
it. All the tools you need are available in Microsoft Excel 2016, 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 problems in areas ranging from sales
and marketing to operations. Carlberg offers unprecedented insight into
building powerful, credible, and reliable forecasts, helping you gain
deep insights from Excel that would be difficult to uncover with costly
tools such as SAS or SPSS.
Fully updated for Excel 2016, this guide contains valuable new coverage
of accounting for seasonality and managing complex consumer choice
scenarios. Throughout, Carlberg provides downloadable Excel 2016
workbooks you can easily adapt to your own needs, plus VBA code-much of
it open-source-to streamline especially 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 the "how" and "why" of using data to make better decisions, and
choose the right technique for each problem
- 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
- Account for trends and seasonality via Holt-Winters smoothing
- Prevent trends from running out of control over long time horizons
- Construct more accurate predictions by using Solver
- Manage large numbers of variables and unwieldy datasets with principal
components analysis and Varimax factor rotation
- Apply ARIMA (Box-Jenkins) techniques to build better forecasts and
clarify their meaning
- Handle complex consumer choice problems with advanced logistic
regression
- Benchmark Excel results against R results
