Breakdown of RA2 from 0 to 02 from 0.2 to 0.4 from 0.4 to 0.6 from 0.6 to 0.85 from 0.85 to 1 (excellent) Upload US crime data and focus on the state of Illinois. Your iob is to "cut-&-paste" the data and create 7 columns and label them Murder, Rape, Robbery, Assault, Burglary, Larceny, and Car Theft respectively. Next perform a regression to predict the Burgla_ry count using the remaining 6 variables. Finally, pick the two variables with the best P values and create a new table, this time using these two variables in order to predict the Burglary count. Answer the questions using this new table only_: I) What are the two variables you picked? (10 points) \" a. Rape and Robbery b. Larceny and Car Theft \" c. Robbery and Assault A d. Assault and Larceny \" e. None of the above ll) After getting the new table, choose the variable with larger positive coefcient and describe its interpretation. (10 points) \" a. Rape; On average, as the Rape oount increases by one, the Burglary count decream by 0.04814 0 b. Assault; For every Assault there are 0.00517 Burglaries \" c. Assault; It has the largest coefficient indicating the strongest correlation ' ' d. Larceny; On average, for every Larceny the Burglary count increases by 0.697915 \" e. None of the above III) How good is the fit and why? (5 points) '\" a. Excellent, R-squared is above 0.85 b. Excellent, P-value is below 0.05 '\" 13. Excellent, Both P-values are very small d. None of the above IV) Which of the two variables has a better P-value'l (5 points) a. Rape \"' b. Larceny c. Robbery "' d. Assault " e. None of the above