Forecasting and predictive analytics: with ForecastX

Chapter 1 Introduction to Business Forecasting and Predictive Analytics
Chapter 2 The Forecast Process, Data Considerations, and Model Selection
Chapter 3 Extrapolation 1. Moving Averages and Exponential Smoothing
Chapter 4 Extrapolation 2. Introduction to Forecasting with Regression Trend Models
Chapter 5 Explanatory Models 1. Forecasting with Multiple Regression Causal Models
Chapter 6 Explanatory Models 2. Time-Series Decomposition
Chapter 7 Explanatory Models 3. ARIMA (Box-Jenkins) Forecasting Models
Chapter 8 Predictive Analytics: Helping to Make Sense of Big Data
Chapter 9 Classification Models: The Most Used Models in Analytics
Chapter 10 Ensemble Models and Clustering
Chapter 11 Text Mining
Chapter 12 Forecast/Analytics Implementation

OVERVIEW


The seventh edition of Forecasting and Predictive Analytics with ForecastX™ builds on the success of the previous editions. While a number of significant changes have been made in this edition, it remains a book about prediction methods for managers, forecasting practitioners, data scientists, and students aspiring to become business professionals and have a need to understand practical issues related to prediction in all its forms. The text is designed to lead through the most helpful techniques in any prediction effort. Most of the examples in the book are based on actual historical data and the techniques are explained as procedures that users may replicate with their own data.