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42. Recall that in exercise 39, the admissions officer for Clearwater College de

ID: 3218536 • Letter: 4

Question

42.      Recall that in exercise 39, the admissions officer for Clearwater College developed the following estimated regression equation relating final college GPA to the student’s SAT mathematics score and high-school GPA.

yˆ  = -1.41 + .0235x1 + .00486x2

where

x1 = high-school GPA

x2 = SAT mathematics score

y = final college GPA

A portion of the Minitab computer output follows.

a.       Complete the missing entries in this output.( please make the numbers clear for me to plug in)

b.       Use the F test and a .05 level of significance to see whether a significant relationship is present.

c.       Use the t test and = .05 to test H0: f31 = 0 and H0: f32 = 0.

d.       Did the estimated regression equation provide a good fit to the data? Explain.

The regression equati on is 1.41 SE Coef Predict01 Coef Constant 1.4053 R-sq(adi) R sq Analysis of Variance SOURCE Regression 1.76203 Residual EMT or Total

Explanation / Answer

a) From the given information n-1=9

                                                  n=10

So MSR=0.8810

     MSE =0.0168

Hence F= MSR/MSE

             =0.8810/0.0168

             =52.44

It is clear that F~F=(2,7)

From the F distribution P value=0.000061

Thus the ANOVA table as follows

soure of

variation

degrees

freedom

sum

of squires

mea sum

of squires

significance

F

For the value of intercept t=-1.4053/0.4848

                                        =-2.8987

The value of P using t (-2.8987) =0.017624

For the value of X1

                       t=0.0235/0.0087

                         =2.7011

The value of P using t( 2.7011) =0.02435

For the value of X2

                            t=0.0049/0.0011

                              =4.4545

The value of P using t(4.4545) =0.00159

b)State the hypothesis

From the above test statistic value is 52.44 and corresponding P value is =0.000061

Use the level of significance =0.05

0.000061<( =0.05)

Here P value is less than the significance value , reject the null hypothesis,

i.e. there is a significant difference i the given model

c) State the Hypothesis

Null hypothesis

Ho:1=0

. There is no significant difference in the given model

Alternative Hypothesis

HA:10 .

there is a significant difference in the given model

Rejection Rule

P-value < (=0.05), the reject is null hypothesis

From the given output the test statistic is 2.7011and the corresponding p-value is 0.02435

Here the P-value (0.02435) <( =0.05)

Then reject the null hypothesis

i.e. there is a significant difference i the given model

d) For the above information we can clearly say that the estimated regression equation provides a good fit for the data

soure of

variation

degrees

freedom

sum

of squires

mea sum

of squires

F

significance

F

Regression 2 1.7621 0.8810 52.44 .0.000061 Residuel 7 0.1179 0.0168 Total 9 1.88
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