# Regression Analysis

**Topics:**Prediction, Forecasting, Regression analysis

**Pages:**2 (317 words)

**Published:**February 14, 2013

General form of a simple LINEAR FUNCTION

Y=a+bX

This equation describes any straight line. The slope of the linear relationship between X and Y is represented by the letter b. The constant(y intercept) is represented in the equation by the letter a. The dependent(tatget)vatiable is represented by Y. The independent(casual) variable is represented by X. By using this formula we can determine the values of Y Warning: When you use a regression equation, do not use values for the independent variable that are outside the range of values used to create the equation. That is called extrapolation, and it can produce unreasonable estimates.. Example: SIMULATION MODEL/REGRESSION FORECAST

TARGET STORES STAFFING FORECAST MODEL

Y = 8 + .0011(X1) + .00004(X2) + .02(X3)

Y = Number of employees needed to staff the store

X1 = Square feet of sales space

X2 = Population of metropolitan area

X3 = Projected annual disposable income in millions of dollars Y = 8 + .0011(50,000sq ft) + .00004(150,000popul) + .00000002($850 million) Y = 8 + 55 + 6 + 17

Y = 86 employees needed at this store

Regression is a valuable forecasting technique and it enables us to plan and execute recruitment, selection, training and development programs in a planned, proactive fashion to ensure the trained...

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