A researcher would like to predict the dependent variable Y fromthe two independent variables X1 and X2 for a sample of N=16subjects. Use multiple linear regression to calculate thecoefficient of multiple determination and test the significance ofthe overall regression model. Use a significance level α=0.05.
X1Â Â Â Â Â Â Â Â Â Â Â Â X2Â Â Â Â Â Â Â Â Â Â Â Â Y
| 48 | 42.3 | 47.1 |
| 36.3 | 58.7 | 65.4 |
| 43.4 | 40.2 | 63.6 |
| 49.5 | 37.9 | 45.6 |
| 45.5 | 37.2 | 50.8 |
| 40.6 | 64.7 | 42.4 |
| 42.5 | 46.7 | 63.1 |
| 42.7 | 40 | 35.8 |
| 55.8 | 10.6 | 52.1 |
| 40.9 | 63 | 60.3 |
| 39.6 | 56.5 | 44 |
| 43.5 | 45.1 | 61.2 |
| 39 | 68.8 | 67.2 |
| 50.4 | 43.7 | 40.6 |
| 46.1 | 42.6 | 58 |
| 55.2 | 19.1 | 49.1 |
SSreg=
SSres=
R2=
F=
P-value =
What is your decision for the hypothesis test?
- Reject the null hypothesis, H0:β1=β2=0
What is your final conclusion?
- The evidence supports the claim that one or more of theregression coefficients is non-zero
- The evidence supports the claim that all of the regressioncoefficients are zero
- There is insufficient evidence to support the claim that atleast one of the regression coefficients is non-zero
- There is insufficient evidence to support the claim that all ofthe regression coefficients are equal to zero
