A researcher wishes to build an appropriate multiple linear model for predicting response variable Y using three predictor variables X1, X2, and X3. He has just made sixteen observations and analysed his data using SPSS. Part of his analysis outputs is as given in the table below. Unstandardized Standardized Coefficients Coefficients Model B Std. Error Beta 1 (Constant) 33.964 13.061 X1 2.960 1.227 .519 X2 .702 .946 .140 X3 -1.769 .702 -.343 2.1 Interpret the unstandardized coefficient of X3. 2.2 Construct the ANOVA table for his model given that SSR = 8417.884 and that MSE = 6.843. %3D 2.3 Compute the adjusted R square for this model and interpret it.

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A researcher wishes to build an appropriate multiple linear model for predicting response
variable Y using three predictor variables X1, X2, and X3. He has just made sixteen
observations and analysed his data using SPSS. Part of his analysis outputs is as given in the
table below.
Unstandardized
Standardized
Coefficients
Coefficients
Model
B
Std. Error
Beta
(Constant)
33.964
13.061
X1
2.960
1.227
.519
X2
.702
.946
.140
X3
-1.769
.702
-.343
2.1
Interpret the unstandardized coefficient of X3.
2.2
Construct the ANOVA table for his model given that SSR = 8417.884 and that
MSE = 6.843.
2.3
Compute the adjusted R square for this model and interpret it.
2.4
Compute observed t-values for all model parameters.
2.5
Construct the 95% confidence intervals for all slope parameters and hence use them to
determine all significant predictors of Y, if any, at 5% level?
Transcribed Image Text:A researcher wishes to build an appropriate multiple linear model for predicting response variable Y using three predictor variables X1, X2, and X3. He has just made sixteen observations and analysed his data using SPSS. Part of his analysis outputs is as given in the table below. Unstandardized Standardized Coefficients Coefficients Model B Std. Error Beta (Constant) 33.964 13.061 X1 2.960 1.227 .519 X2 .702 .946 .140 X3 -1.769 .702 -.343 2.1 Interpret the unstandardized coefficient of X3. 2.2 Construct the ANOVA table for his model given that SSR = 8417.884 and that MSE = 6.843. 2.3 Compute the adjusted R square for this model and interpret it. 2.4 Compute observed t-values for all model parameters. 2.5 Construct the 95% confidence intervals for all slope parameters and hence use them to determine all significant predictors of Y, if any, at 5% level?
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