STATISTIKGA

AL MUIZZUDDIN F., SE., ME.

Measures of Regression and

Prediction Intervals

PREDICTION INTERVALS

• Two variables have a bivariate normal distributionif for any fixed values of x the correspondingvalues of y are normally distributed, and for anyfixed values of y the corresponding values of x arenormally distributed.

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• Because regression equations are determinedusing sample data and because x and y areassumed to have a bivariate normal distribution,you can construct a prediction interval for the truevalue of y.To construct the prediction interval, usea t-distribution with n - 2 degrees of freedom.

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TABEL DISTRIBUSI T8

Multiple Regression

FINDING A MULTIPLE REGRESSION EQUATION

• In many instances, a better prediction model can be found for a dependent (response) variable by using more than one independent (explanatory) variable.

• For instance, a more accurate prediction for the carbon dioxide emissions discussed in previous sections might be made by considering the number of cars as well as the gross domestic product. Models that contain more than oneindependent variable are multiple regression models.

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PREDICTING Y-VALUES

• After finding the equation of the multiple regression line, you can use the equation to predict y-values over the range of the data. To predict y-values, substitute the given value for each independent variable into the equation, then calculate yn.

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LATIHAN SOAL

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LATIHAN SOAL18

• Y=104982X+14128,671

• Tc =2,228

• Se=8064.633

• E=21253.7

• Prediction Interval?

• 61,370.57 + 21253.7 (maksimum)

• 61,370.57 - 21253.7 (minimum

• Y est? 61,370.57

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