FORECASTING 16-Jan-19 Dr.B.Sasidhar.

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FORECASTING 16-Jan-19 Dr.B.Sasidhar

Definition Forecast is a prediction of future events used for planning process. 16-Jan-19 Dr.B.Sasidhar

Introduction to Forecasting What is forecasting? Primary Function is to Predict the Future Why are we interested? Affects the decisions we make today Examples: who uses forecasting in their jobs? forecast demand for products and services forecast availability of manpower forecast inventory and materiel needs daily

Forecasting Methods Subjective Forecasting Methods Measures individual or group opinion Objective Forecasting Methods Forecasts made based on past history and a model. Time Series Models: use only past history. Easy to incorporate into computer models. Regression: Causal Model to predict

Objective Forecasting Methods Two primary methods: causal models and time series methods Causal Models Let Y be the quantity to be forecasted and (X1, X2, . . . , Xn) be n variables that have predictive power for Y. A causal model is Y = f (X1, X2, . . . , Xn). “Y depends on X1, X2, . . . , Xn” A typical relationship is a linear one. That is, Y = a0 + a1X1 + . . . + an Xn.

Causal Methods Linear Regression Deviation, or error { Dependent variable Independent variable X Y Regression equation: Y = a + bX Estimate of Y from regression equation Actual value of Y Value of X used to estimate Y 16-Jan-19 Dr.B.Sasidhar 8

Time Series Methods Trend Seasonality Cycles Randomness A time series is just collection of past values of the variable being predicted. Also known as naïve methods. Goal is to isolate patterns in past data. (See Figures on following pages) Trend Seasonality Cycles Randomness