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:
<em>H</em>₀: β₁ = 0 vs. <em>H</em>ₐ: β₁ ≠ 0
The test statistic is:

It is provided that H₀ is rejected if <em>t</em> > 2.042.
The test statistic value, <em>t</em> = 3.753 > 2.042.
Thus, the null hypothesis is rejected.
<u>Conclusion:</u>
There is a significant relationship between the regression variable and the dependent variable.
(2)
The hypothesis for for the testing of coefficient β₂ are:
<em>H</em>₀: β₂ = 0 vs. <em>H</em>ₐ: β₂ ≠ 0
The test statistic is:

It is provided that H₀ is rejected if <em>t</em> < -2.042.
The test statistic value, <em>t</em> = -3.046 < -2.042.
Thus, the null hypothesis is rejected.
<u>Conclusion:</u>
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.