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Does prison really deter violent crime? Let x represent percent change in the late of violent crime and y represent percent change in the late of imprisonment in the genelal U.S. population. For 7 recent years, the following data have been obtained. 6.5 5.9 3.7 5.2 6.2 6.5 11.1 1.8 3.9 6.2 4.0 3.6 D.l 4.4 I USE SA Complete parts (a) through {e}, given Ex : 45.1, 2y = 16.8, 2X2 : 321-59: 2Y2 : 105-22. Exy = 105.52, and r2: 0.0583. (a) Draw a scatter diaglam displaying the data. r Graph Layers LLLL'. E I No Solution ' Iliehnslgn. stapling Tun! (b) Verify the given sums Ex, Ely, 2x2, Eyz, they, and the value of the sample correlation coefcient r. {Round your value for r to four decimal places.) Ex =|:| Ely =|:| 2x2 =|:| Eyz =|:| my =|:| r =|:| (c) Find :r, and ;. Then nd the equation of the leastisquares line? = a + bx. (Round your answer to four decimal places.) } ?= E t (d) Graph the leastsquares line. Be sure to plot the point (:r, i) as a point on the line. 3' 3" i x ' . i . i . . . x O 2 4 6 B 10 12 14 O 2 4 6 8 10 12 14 (e) Find the value of the ooeFcient of determination (2. what percentage of the variation in y can be explained by the corresponding variation in x and the least-squares line? What percentage is unexplained? {Round your answer for r2 to four decimal places. Round your answers for the percentages to two decimal place.) .2 = :I explained \\:I % unexplained \\:| % (t) Considering the values of r and r2f does it make sense to use the leastsquares line for prediction? Explain your answer. Q The correlation between the variables is so low that it does not make sense to use the leastsquares line for prediction. 0 The correlation between the variables is so high that it makes sense to use the leastsquares line for prediction. 0 The correlation between the variables is so high that it does not make sense to use the leastsquares line for prediction. 0 The correlation between the variables is so low that it makes sense to use the least-squares line for prediction