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LOS 8.a: Formulate a multiple regression equation to READING 8: MULTIPLE REGRESSION AND ISSUES IN REGRESSION ANALYSIS
describe the relation between a dependent variable and
several independent variables and determine the MODULE 8.1: MULTIPLE REGRESSION: INTRODUCTION
statistical significance of each independent variable.

Can future 10-year real Earnings Growth in the S&P 500 (EG10) be explained by the trailing dividend Payout Ratio of
the stocks in the index (PR) and the Yield Curve Slope (YCS)?

Say 46 observations!
Results in figure 8.1 below….

LOS 8.b: Interpret estimated regression coefficients and their p-values

Same as in simple linear regression for the intercept but very
different for the slope coefficients:

• Intercept term = value of the dependent variable when the independent variables are all
equal to zero.

• Slope coefficient/s = ∆ in the dependent variable for a one-unit ∆ in that independent
variable (citeris paribus, hence also called partial slope coefficients)
Suppose Y = 2.0 + 4.5X1, then If X1 increases by 1 unit, we would expect Y to increase by 4.5 units.

What happened to coefficient of X1?
Now suppose we add X2 as next independent variable, we get: Y = 1.0 + 2.5X1 + 6.0X2
It dropped from 4.5 to 2.5!
Each time you add another variable, the whole equation interacts/recalibrates (assuming obviously, that X1 and X2 are related); New
interpretation?