33:799:301 Lecture Notes - Lecture 6: Moving Average, Time Series, Dependent And Independent Variables
5 Mar 2017
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Document Summary
The main purpose of a time series model is to collect and study the past data of a given time series in order to generate probable future values for the series. Forecast for future demand relies on understanding past demand. Creates a baseline forecast that can be evaluated for accuracy, adjusted based on current info and planned activity. Naive forecasting - the forecast for the next time period is equal to the actual result in the last time period. Advantages: simple, works well for mature products with consistent demand. Disadvantages: no consideration for impacts to the demand, no adjustment for extenuating circumstances, can throttle growth or perpetuate decline. Simple moving average - uses a calculated average of historical demand during a specified number of the most recent time periods to generate the forecast. Adv: provides a very consistent demand over long periods of time and smooths out random variations.
