A multiple regression analysis between yearly income (y in $1000s), college grade point average (x4), age of the individuals (x2), and gender of the individual (3.0 representing female and 1 representing male) was performed on a sample of 10 people, and the following results were obtained using Excel ANOVA Regression Residual Intercept x1 x2 x3 Coefficients 4.0928 10.0230 0.1020 -4.4811 Write the regression equation for the above Oy Po P1x1 P2x2 + xy + OE(Y)-Po 1*1*2*2+ P3X3 Oy 4.0928 +10.0230x10.102x2-4481x3 Oy hat 4 0928 +10.0230x1+0 102x2-44811x3 SS 360.59 23.91 Standard Error 1.4400 1.6512 0.1225 1,4400 MS F

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A multiple regression analysis between yearly income (y in $1000s), college grade point average (x1), age of the individuals (x2), and gender of the individual (x3.0
representing female and 1 representing male) was performed on a sample of 10 people, and the following results were obtained using Excel
ANOVA
Regression
Residual
Intercept
31
x2
x3
Coefficients
4.0928
10.0230
0.1020
-4.4811
Write the regression equation for the above.
Oy Po P1x1 P₂x2 + 3x3 +
OE(y) Po
1x1+ P2x2+ P3x3
Oy 4.0928 +10.0230x10.102x2-4.481x3
Oy hat 40928 +10.0230x1+0 102x2-44811x3
SS
360.59
23.91
Standard Error
1.4400
1.6512
0.1225
1.4400
MS
F
Transcribed Image Text:A multiple regression analysis between yearly income (y in $1000s), college grade point average (x1), age of the individuals (x2), and gender of the individual (x3.0 representing female and 1 representing male) was performed on a sample of 10 people, and the following results were obtained using Excel ANOVA Regression Residual Intercept 31 x2 x3 Coefficients 4.0928 10.0230 0.1020 -4.4811 Write the regression equation for the above. Oy Po P1x1 P₂x2 + 3x3 + OE(y) Po 1x1+ P2x2+ P3x3 Oy 4.0928 +10.0230x10.102x2-4.481x3 Oy hat 40928 +10.0230x1+0 102x2-44811x3 SS 360.59 23.91 Standard Error 1.4400 1.6512 0.1225 1.4400 MS F
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