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REGRESSION

DIVIDED IS

PREDICTOR VARIABLE

CREDIT VARIABLE

on which we base our predictions

variable being predicted

es

y

es

x

IS

how to predict a variable through its score

The larger the value of x, the greater the prediction will be.

linear regression

consists

FIND THE LINE THAT BEST FITS THE POINTS.

REGRATION LINE

CONSISTS

FEATURES

PREDICTED SCORE IN Y FOR EACH POSSIBLE VALUE IN X.

PREDICTION ERRORS

THE POINT VALUE MINUS THE PREDICTED VALUE

IS

LINE OF BEST FIT

IS

MINIMIZE THE SUM OF THE PREDICTION SQUARE ERRORS

COMPUTING THE REGRESSION LINE

The calculations are based on the statistics shown in Table 3. Mx is the mean of X, My is the mean of Y, sx is the standard deviation of X, sy is the standard deviation of Y, andris the correlation between X and Y.

STANDARDIZED VARIABLES

ARE

EQUAL TO 0 AND THE DEVIATIONS ARE EQUAL TO 1

PENDING

IS EQUAL TO R

DIVISION OF THE VARIATION OF Y

THE VARIATION OF PREDICTED SCORES

VARIATION OF PREDICTION ERRORS

SUM OF THE SQUARE DEVIATIONS OF Y FROM THE MEAN OF Y