SUMMARY OUTPUT – Use this output to answer the next 10 questions
Multiple R 0.9445
R Square 0.8921
Adjusted R Square 0.8742
Standard Error 1.9005
df SS MS F Significance F
Regression 1 180.2143 180.2143 49.6328 0.00041
Residual 6 21.7857 3.631
Total 7 202
Coefficient Standard Error t Stat P-value Lower 95% Upper 95%
Intercept -0.3214 1.4848 -0.2165 0.8358 -3.9545 3.3116
HT(x) 4.1429 0.5881 7.0451 0.0004 2.7039 5.5818
1) Using the summary output above with INQ as the dependent variable, what is the estimated regression equation?
a) INQ = -0.2165 + 7.0451 HT b) INQ = -0.3214 + 4.1429 HT c) HT = 4.1429 – 0.3214 INQ
d) HT = 7.0451 – 0.2165 INQ e) INQ = -3.9545 + 2.7039 HT
2) Interpret the slope estimate
a) As height of ad (HT) increases by one unit, the average number of inquires (INQ) increases by 3.3116 units.
b) As height of ad (HT) increases by one unit, the average number of inquires (INQ) increases by 4.1429 units.
c) As average number of inquires (INQ) increases by 4.1429 units, the height of ad (HT) decreases by one unit.
d) As height of ad (HT) increases by one unit, the average number of inquiries (INQ)
increases by 5.5818
e) As height of ad (HT) increases by 4.1429 units, the average number of inquiries (INQ) increases by one unit.
3) What are the hypotheses in the test for a linear relationship between HT and INQ?
4) Using the estimated regression line from #1, predict the INQ with a HT of 6 inches.
5) At a 2.5 percent level of significance, is there evidence of a significant linear relationship between HT and INQ?
a) Yes, since the test statistic t = 7.0451, reject H0
b) There is not enough information here to solve this problem
c) No, since the p-value = 0.0004, do not reject H0
d) Yes, since the p-value = 0.05, reject H0
e) No, sine the test statistic t =7.0451, do not reject H0
6) Give the coefficient of determination.
7) Give the correlation coefficient between INQ and HT.
8) One pair of data in this sample is (2,5). That is to say HT of 2 inches has 5 INQ. Calculate the residual for the data point, i.e., calculate the difference between the observed inquiries and the predicted inquiries.
9) Find a 95% confidence interval for estimating the value of the slope.
10) What is the standard error of the estimated regression line?
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