Will need to be done in R studio. Please include your full explanation, R code and summary output as well. The USArrests data is already included in the default R Library so there is no need to load the data separately, but I have included it down below just in case. Thank you very much.

"" "Murder" "Assault" "UrbanPop" "Rape"

"Alabama" 13.2 236 58 21.2

"Alaska" 10 263 48 44.5

"Arizona" 8.1 294 80 31

"Arkansas" 8.8 190 50 19.5

"California" 9 276 91 40.6

"Colorado" 7.9 204 78 38.7

"Connecticut" 3.3 110 77 11.1

"Delaware" 5.9 238 72 15.8

"Florida" 15.4 335 80 31.9

"Georgia" 17.4 211 60 25.8

"Hawaii" 5.3 46 83 20.2

"Idaho" 2.6 120 54 14.2

"Illinois" 10.4 249 83 24

"Indiana" 7.2 113 65 21

"Iowa" 2.2 56 57 11.3

"Kansas" 6 115 66 18

"Kentucky" 9.7 109 52 16.3

"Louisiana" 15.4 249 66 22.2

"Maine" 2.1 83 51 7.8

"Maryland" 11.3 300 67 27.8

"Massachusetts" 4.4 149 85 16.3

"Michigan" 12.1 255 74 35.1

"Minnesota" 2.7 72 66 14.9

"Mississippi" 16.1 259 44 17.1

"Missouri" 9 178 70 28.2

"Montana" 6 109 53 16.4

"Nebraska" 4.3 102 62 16.5

"Nevada" 12.2 252 81 46

"New Hampshire" 2.1 57 56 9.5

"New Jersey" 7.4 159 89 18.8

"New Mexico" 11.4 285 70 32.1

"New York" 11.1 254 86 26.1

"North Carolina" 13 337 45 16.1

"North Dakota" 0.8 45 44 7.3

"Ohio" 7.3 120 75 21.4

"Oklahoma" 6.6 151 68 20

"Oregon" 4.9 159 67 29.3

"Pennsylvania" 6.3 106 72 14.9

"Rhode Island" 3.4 174 87 8.3

"South Carolina" 14.4 279 48 22.5

"South Dakota" 3.8 86 45 12.8

"Tennessee" 13.2 188 59 26.9

"Texas" 12.7 201 80 25.5

"Utah" 3.2 120 80 22.9

"Vermont" 2.2 48 32 11.2

"Virginia" 8.5 156 63 20.7

"Washington" 4 145 73 26.2

"West Virginia" 5.7 81 39 9.3

"Wisconsin" 2.6 53 66 10.8

"Wyoming" 6.8 161 60 15.6

3' Consider one of the standard R data sets? the USArrests data (type data (USArrests) to load the data and then help (USArrestS) to read about the variables in the USArrests data frame}. For this data set, t a Bayesian linear regression model with the response variable Assault and the predictor variable UrbanPop. Use the standard Uniform prior on the parameters ,8 and U2. Using an appropriate simulation method, simulate posterior samples for the parameters 5 and 02. In your solution you need to include the R code and summaryr output. Does it seem as though the predictor is related to the response? Refer to an appropriate 955'. credible interval to support your