Following up on our last week’s Webex session on Logistic Regression for credit scoring (you can catch it here), this Sunday we will demonstrate the technique of exponential smoothing in time series forecasting.

More specifically, during the webinar we will take you through the basic decomposition of a time series into its components:

- Trend
- Seasonality
- Cyclic
- Error

We will concentrate on extracting and forecasting the trend and seasonality of a series. Trend component can be extracted using Exponential smoothing (Single, double and triple depending on the slope and pattern) and building a seasonal index to forecast the seasonal variation.

The webinar will demonstrate how this can be done using simple formulas on an excel sheet itself and then introduce the time series function in IBM SPSS. A basic introduction to Box-Jenkins (ARIMA) modelling will also be covered.

A trial version of IBM SPSS version 20 can be downloaded from here. (You will need to fill in some details). Those interested in attending the seminar can drop an email at info@learnanalytics.in or fill in the form at http://www.learnanalytics.in/contact.html and we will mail you the webex invite. The webinar is scheduled on Sunday, 15^{th} Jan, 0930 IST – 0400 GMT.

The webinar is free to attend.

To receive regular updates, please join our linkedin group Learn Analytics.