Forecasting and Predictive Analytics with Forecast X (TM)
– Connect: A highly reliable, easy-to-use homework and learning management solution that embeds learning science and award-winning adaptive tools to improve student results.
– This edition presents a broad-based survey of business forecasting methods including subjective and objective approaches.
– The author team deliver practical how-to forecasting techniques, along with dozens of real world data sets while theory and math are held to a minimum.

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Table of Contents

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Program Details

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