**Accurate, practical Excel predictive
analysis: powerful smoothing techniques for serious data
crunchers!**

In *More Predictive Analytics*,
Microsoft Excel® MVP Conrad Carlberg shows how to use
intuitive smoothing techniques to make remarkably accurate
predictions. You won’t have to write a line of code--all you
need is Excel and this all-new, crystal-clear tutorial.

Carlberg goes beyond his highly-praised
*Predictive Analytics*, introducing proven methods for
creating more specific, actionable forecasts. You’ll learn
how to predict what customers will spend on a given product next
year… project how many patients your hospital will admit next
quarter… tease out the effects of seasonality (or patterns
that recur over a day, year, or any other period)…
distinguish real trends from mere “noise.”

Drawing on more than 20 years of experience, Carlberg helps you master powerful techniques such as autocorrelation, differencing, Holt-Winters, backcasting, polynomial regression, exponential smoothing, and multiplicative modeling.

Step by step, you’ll learn how to make the most of built-in Excel tools to gain far deeper insights from your data. To help you get better results faster, Carlberg provides downloadable Excel workbooks you can easily adapt for your own projects.

If you’re ready to make better
forecasts for better decision-making, you’re ready for
*More Predictive Analytics.*

Discover when and how to use smoothing instead of regression

Test your data for trends and seasonality

Compare sets of observations with the autocorrelation function

Analyze trended time series with Excel’s Solver and Analysis ToolPak

Use Holt's linear exponential smoothing to forecast the next level and trend, and extend forecasts further into the future

Initialize your forecasts with a solid baseline

Improve your initial forecasts with backcasting and optimization

Fully reflect simple or complex seasonal patterns in your forecasts

Account for sudden, unexpected changes in trends, from fads to new viral infections

Use range names to control complex forecasting models more easily

Compare additive and multiplicative models, and use the right model for each task

- About This eBook
- Title Page
- Copyright Page
- Contents at a Glance
- Contents
- About the Author
- Dedication
- We Want to Hear from You!
- Reader Services
- Introduction
- 1. Smoothing and Its Alternatives
- 2. Diagnosing Trend and Seasonality
- 3. Working with Trended Time Series
- 4. Initializing Forecasts
- 5. Working with Seasonal Time Series
- 6. Names, Addresses, and Formulas
- 7. Multiplicative and Damped Trend Models
- Index
- Code Snippets