Answer:
Both the variables are important for the regression analysis and cannot be deleted.
Step-by-step explanation:
(1)
The hypothesis for for the testing of coefficient β₁ are:
H₀: β₁ = 0 vs. Hₐ: β₁ ≠ 0
The test statistic is:
[tex]t=\frac{b_{1}}{S_{b_{1}}} =\frac{2.815}{0.75}= 3.753[/tex]
It is provided that H₀ is rejected if t > 2.042.
The test statistic value, t = 3.753 > 2.042.
Thus, the null hypothesis is rejected.
Conclusion:
There is a significant relationship between the regression variable and the dependent variable.
(2)
The hypothesis for for the testing of coefficient β₂ are:
H₀: β₂ = 0 vs. Hₐ: β₂ ≠ 0
The test statistic is:
[tex]t=\frac{b_{2}}{S_{b_{2}}} =\frac{-1.249}{0.41}= -3.046[/tex]
It is provided that H₀ is rejected if t < -2.042.
The test statistic value, t = -3.046 < -2.042.
Thus, the null hypothesis is rejected.
Conclusion:
There is a significant relationship between the regression variable and the dependent variable.
Thus, both the variables are important for the regression analysis and cannot be deleted.
