Natural Effects: Describes how one can incorporate weather information into a forecasting model to improve the accuracy of demand forecasts …it is preferable to use weather forecasts which are objectively (not subjectively) derived … explains the findings of a study of consumer products company where weather information was used to forecast demand.

Case Study: The client needs to cleanse their data not forecast. In order to have accurate reporting by Canton (County), they use Autobox to identify pulses and level shifts and the historical data is restated without these effects.

Case Study: If you are going to analyze time series data perhaps this discussion will be of help. Regression was originally developed for cross-sectional data but Statisticians / Economists have been applying it (mostly incorrectly) to chronological or longitudinal data with little regard for the Gaussian assumptions.

Business Problem: How to determine how many samples to give to a doctor. Sales Reps call on doctor’s to discuss their drug with scientific discussions on why their drug is better. They also leave behind samples for the doctor to distribute to make it easier for them to adopt their product.

Business Problem: Salmon population droughts over a period of time develops concern. With Salmon population constantly at an unknown, a forecasting solution is sought out for.