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s344n2d4d5 [400]
3 years ago
14

Following is a portion of the regression output for an application relating maintenance expense (dollars per month) to usage (ho

urs 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.
Mathematics
1 answer:
xxMikexx [17]3 years ago
7 0

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:

y=6.1092+0.8931x

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:

t=\frac{b}{S.E._{b}}=\frac{0.8931}{0.149}=5.99

Compute the <em>p</em>-value as follows:

p-value=2\times P (t_{8}

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.

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