SUMMARY OUTPUT – Use this output to answer the next 10 questions

SUMMARY OUTPUT – Use this output to answer the next 10 questions

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                Regression Statistics

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Multiple R                                        0.9445

R Square                                          0.8921

Adjusted R Square                      0.8742

Standard Error                               1.9005

Observations                                            8

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                                                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

Intercept             -0.3214                 1.4848           -0.2165        0.8358                    -3.9545                 3.3116

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?