REGRESSION /MISSING LISTWISE /STATISTICS COEFF OUTS CI(95) R ANOVA /CRITERIA=PIN

ID: 3234030 • Letter: R

Question

REGRESSION

/MISSING LISTWISE

/STATISTICS COEFF OUTS CI(95) R ANOVA

/CRITERIA=PIN(.05) POUT(.10)

/NOORIGIN

/DEPENDENT StartDate

/METHOD=ENTER Q17 Q18 Q19.

Variables Entered/Removeda

Model Variables Entered Variables Removed Method

1 Current job category, Tell us about yourself, Age groupb . Enter

a Dependent Variable: Start Date

b All requested variables entered.

Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate

1 .140a .020 -.060 6 21:23:59.485

a Predictors: (Constant), Current job category, Tell us about yourself, Age group

ANOVAa

Model Sum of Squares df Mean Square F Sig.

1 Regression 261847753029.389 3 87282584343.130 .246 .864b

Residual 13118282652919.643 37 354548179808.639

Total 13380130405949.031 40

a Dependent Variable: Start Date

b Predictors: (Constant), Current job category, Tell us about yourself, Age group

Coefficientsa

Model Unstandardized Coefficients Standardized Coefficients t Sig. 95.0% Confidence Interval for B

B Std. Error Beta Lower Bound Upper Bound

1 (Constant) 13700780792.137 668185.308 20504.463 .000 13699426920.101 13702134664.172

Tell us about yourself -183963.357 285744.179 -.105 -.644 .524 -762936.058 395009.344

Age group 35516.564 79490.523 .073 .447 .658 -125546.535 196579.663

Current job category 43831.359 188870.713 .038 .232 .818 -338857.055 426519.774

a Dependent Variable: Start Date

Is this a good model? Why? In other words, what values make you make that determination?

No, this is not a good model.

We can decide this on the basis of p - value (Sig. column in ANOVA table)

In the given problem,

p - value = 0.864

Since this p - value is very large, we do not reject the null hypothesis and hence, the model is not useful in predicting Start Date.

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