Following is a portion of the regression output for an application relating maintenance expense (dollars per month) to usage (hours per week) for a particular brand of computer terminal.
ANOVA
df SS MS F Significance F
Regression 1 1575.76
Residual 8 349.14
Total 9 1924.90
Coefficient Standard Error t Stat P-value
Intercept 6.1092 0.9361
Usage 0.8931 0.149
A) Write the estimated regression equation (to 4 decimals).
B) Use a t test to determine whether monthly maintenance expense is related to usage at the .05 level of significance (to 2 decimals, if necessary).
1. Reject the null hypothesis
2. Do not reject the null hypothesis
C) Monthly maintenance expense______to usage.
1. Is related
2. Is not related
D) Did the estimated regression equation provide a good fit?
1. yes
2. no
E) Explain.

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:

[tex]y=6.1092+0.8931x[/tex]

Here,

y = maintenance expense (dollars per month)

x = 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:

H₀: The monthly maintenance expense is not related to usage, i.e. β = 0.

Hₐ: The monthly maintenance expense is related to usage, i.e. β ≠ 0.

Compute the test statistic as follows:

[tex]t=\frac{b}{S.E._{b}}=\frac{0.8931}{0.149}=5.99[/tex]

Compute the p-value as follows:

[tex]p-value=2\times P (t_{8}<5.99}=0.00033[/tex]

The null hypothesis will be rejected if the p-value is less than the significance level.

p-value = 0.00033 < α = 0.05

Reject the null hypothesis.

(C)

Monthly maintenance expense is related 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.

fichoh fichoh · Answer 2 · 2025-03-29T15:32:23-04:00

From the regression output given, the solution to the questions given are outlined thus ;

[tex] Null \: hypothesis : H_{0} : β = 0 [/tex]

[tex] Alternative \: hypothesis : H_{1} : β ≠ 0 [/tex]

1.)

Regression equation :

y = bx + c
b = slope ; c = intercept

Hence, the estimated regression equation is;

y = 0.8931x + 6.1092

2.)

We can calculate the T-statistic value thus ;

[tex] T-statistic = \frac{b}{SE_{b}}[/tex]
[tex]SE_{b} = Standard \: error \: of \: slope[/tex]
df = 8

Hence, the T-statistic is given as ;

[tex] T-statistic = \frac{0.8931}{0.149} = 5.99[/tex]

Pvalue (2 tailed) = 0.00033

Decison Region :

[tex] Reject \: H_{0} \: if \: Pvalue \: < \: α [/tex]

Since 0.00033 < 0.05 ; we reject the Null hypothesis.

3.)

Hence, we conclude that monthly expense is related to usage.

4.)

Since, the correlation Coefficient, β ≠ 0 ; Yes, the correlation provides a good fit as it is significant.

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