Exhibit 1:   We have the following information about number of violent crimes (Y) and the number of police personnel...

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Exhibit1:  

We have the followinginformation about number of violent crimes (Y) and the number ofpolice personnel (X) for a certain year for a sample of threemetropolitan areas. We also know the following statistics: SST =1250, SSE = 937.5

Crime (Y)

Police Personnel(X)

300

5000

325

3000

350

4000

Question 6

  1. To answer thisquestion, refer to Exhibit 1 in question 1.

    What does value ofr2 tell you?

    A.

    25 percent ofvariation in crime is explained by the number of policepersonnel.

    B.

    50 percent ofvariation in crime is explained by the number of policepersonnel.

    C.

    75 percent ofvariation in crime is explained by the number of policepersonnel.

    D.

    None of the above

Question 7

  1. To answer thisquestion, refer to Exhibit 1 in question 1.

    The coefficient ofcorrelation is (to 2 decimal places)

    A.

    0.87

    B.

    -0.87

    C.

    0.5

    D.

    -0.5

Question 8

  1. To answer thisquestion, refer to Exhibit 1 in question 1.

    What is the estimateof the standard error of the overall regression (to 2 decimalplaces)?

    10.91

    30.62

    45.88

    55.67

  

Question 9

  1. To answer thisquestion, refer to Exhibit 1 in question 1.

    What is the estimateof the standard error of slope estimate (to 3 decimal places)?

    0.001

    0.015

    0.022

    0.053

Question 10

  1. To answer thisquestion, refer to Exhibit 1 in question 1.

    Is police personnel asignificant variable affecting crime in the above data?

    No because we cannotreject the null the slope is 0.

    Yes because we canreject the null the slope is 0.

    Need more informationto answer the question

    Answer & Explanation Solved by verified expert
    3.7 Ratings (480 Votes)
    We use minitab to solve the problem using following steps Stat regression regression fit regression modelOutput 6 Rsquared is a statistical measure of how close the data areto the fitted regression line It is also known as the coefficientof determination    See Answer
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