Answer:
Explained below.
Step-by-step explanation:
The ANOVA and Regression output for an application relating maintenance expense (dollars per month) to usage (hours per week) for a particular brand of computer terminal is provided.
(A)
The estimated regression equation equation is:
Here,
<em>y</em> = maintenance expense (dollars per month)
<em>x</em> = usage (hours per week) for a particular brand of computer terminal
(B)
Consider the Regression output.
The hypothesis to test whether monthly maintenance expense is related to usage is:
<em>H</em>₀: The monthly maintenance expense is not related to usage, i.e. <em>β</em> = 0.
<em>Hₐ</em>: The monthly maintenance expense is related to usage, i.e. <em>β</em> ≠ 0.
Compute the test statistic as follows:
Compute the <em>p</em>-value as follows:
The null hypothesis will be rejected if the <em>p</em>-value is less than the significance level.
<em>p</em>-value = 0.00033 < <em>α</em> = 0.05
Reject the null hypothesis.
(C)
Monthly maintenance expense <u>is related </u>to usage.
(D)
Yes, the estimated regression equation provide a good fit.
Since the regression coefficient is significant it can be concluded that the regression equation estimated is a good fit.