Matakuliah
Tahun
: L0104/Statistika Psikologi
: 2008
Regresi Ganda
Pertemuan 21
Learning Outcomes
Pada akhir pertemuan ini, diharapkan
mahasiswa
akan mampu :
• Mahasiswa akan dapat menghitung
persamaan normal dan koefisien regresi
ganda.
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Outline Materi
•
•
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•
Model regresi ganda
Persamaan normal regresi ganda
Persamaan regresi dugaan
Koefisien determinasi regresi ganda
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Multiple Regression
•
•
•
•
•
•
Multiple Regression Model
Least Squares Method
Multiple Coefficient of Determination
Model Assumptions
Testing for Significance
Using the Estimated Regression Equation
for Estimation and Prediction
• Qualitative Independent Variables
• Residual Analysis
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The Multiple Regression Model
• The Multiple Regression Model
y = 0 + 1x1 + 2x2 + . . . + pxp + 
• The Multiple Regression Equation
E(y) = 0 + 1x1 + 2x2 + . . . + pxp
• The Estimated Multiple Regression Equation
y = b0 + b1x1 + b2x2 + . . . + bpxp
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The Least Squares Method
• Least Squares Criterion
2
min  ( y i  y i )
• Computation of Coefficients’ Values
The formulas for the regression coefficients b0,
b1, b2, . . . bp involve the use of matrix algebra. We
will rely on computer software packages to perform
the calculations.
• A Note on Interpretation of Coefficients
bi represents an estimate of the change in y
corresponding to a one-unit change in xi when all
other independent variables are held constant.
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•
The Multiple Coefficient of
Determination
Relationship Among SST, SSR, SSE
SST = SSR + SSE
• Multiple Coefficient of Determination
R 2 = SSR/SST
• Adjusted Multiple Coefficient of Determination
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