Final Exam: Coding Part
Name: Jack Prangle
Instructions
This is the R portion of your final exam.
Follow the instructions carefully and write your R code in the provided chunks. You will be graded on the correctness of your code, the quality of your analysis, and your interpretation of the results.
Submission: Please make sure the RMD is knittable and submit the RMD file along with the generated HTML report.
Troubleshooting: If you find errors in your code
that prevent the RMD file from knitting, please comment them
out (add # before the code). I will give you
partial credit based on your logic.
Good luck!
Part I: Logistic Regression
0. Background
Context: You have been hired by a retail consulting firm to analyze the sales performance of a company selling child car seats. The company wants to identify the key drivers of high sales performance to optimize their marketing and store layout strategies.
They have provided you with a dataset (store_sales.csv) containing data from 400 different store locations. Your goal is to build classification models to predict whether a store will have “High Sales” (Yes) or not.
Data Dictionary:
High_Sales(Target): Factor with levels Yes and No. Indicates if the store sold more than 8,000 units.CompPrice: Price charged by the nearest competitor at each location.Income: Community income level (in thousands of dollars).Advertising: Local advertising budget for the company at each location.Population: Population size of the region (in thousands).Price: Price charged for the car seats at each site.ShelveLoc: A factor indicating the quality of the shelving location for the car seats at the site (Good, Bad, or Medium).Age: Average age of the local population.Education: Education level at each location.Urban: Factor (Yes/No) indicating if the store is in an urban location.US: Factor (Yes/No) indicating if the store is in the US.
1. Data Preparation (0.5 point)
- Load the data from the file
store_sales.csvand name itstore_sales.
- Split the data into training (70%) and test (30%) sets. Use
set.seed(2025)to ensure reproducibility.
# a) Load data
# Your code here
store_sales <- read.csv("store_sales.csv")
# b) Split data into training and test sets
set.seed(2025)
# Your code here
sample_index <- sample(1:nrow(store_sales), round(0.7*nrow(store_sales)))
store_sales_train <- store_sales[sample_index, ]
store_sales_test <- store_sales[-sample_index, ]
store_sales_train## CompPrice Income Advertising Population Price ShelveLoc Age Education Urban
## 397 139 23 3 37 120 Medium 55 11 No
## 279 114 113 2 129 151 Good 40 15 No
## 187 120 51 0 93 86 Medium 46 17 No
## 266 130 35 10 402 129 Bad 39 17 Yes
## 369 109 22 10 348 79 Good 74 14 No
## 388 142 73 14 238 115 Medium 73 14 No
## 27 107 115 11 496 131 Good 50 11 No
## 379 133 88 3 105 119 Medium 79 12 Yes
## 373 121 50 0 508 98 Medium 65 11 No
## 59 103 93 15 188 103 Bad 74 16 Yes
## 159 142 90 1 189 112 Good 39 10 No
## 142 140 42 0 331 131 Bad 28 15 Yes
## 37 122 76 0 270 100 Good 60 18 No
## 288 95 44 4 208 72 Bad 44 17 Yes
## 63 139 45 0 146 133 Bad 77 17 Yes
## 285 106 46 11 414 96 Bad 79 17 No
## 289 116 40 0 74 97 Medium 76 15 No
## 252 139 111 5 310 132 Bad 62 13 Yes
## 345 138 80 0 108 126 Good 70 13 No
## 118 145 53 0 507 119 Medium 41 12 Yes
## 88 131 67 7 272 126 Good 54 16 No
## 195 112 98 18 481 128 Medium 45 11 Yes
## 174 135 91 5 207 128 Medium 66 18 Yes
## 371 126 41 22 403 119 Bad 42 12 Yes
## 306 115 29 26 394 132 Medium 33 13 Yes
## 391 108 75 9 61 111 Medium 67 12 Yes
## 317 122 36 5 369 72 Good 35 10 Yes
## 16 149 95 5 400 144 Medium 76 18 No
## 325 136 65 4 133 150 Bad 53 13 Yes
## 52 121 90 0 150 108 Bad 75 16 Yes
## 186 130 100 11 449 107 Medium 64 10 Yes
## 144 122 88 7 36 159 Bad 28 17 Yes
## 49 116 52 0 349 98 Bad 69 18 Yes
## 50 157 93 0 51 149 Good 32 17 Yes
## 114 131 29 11 335 127 Bad 33 12 Yes
## 185 132 33 7 35 97 Medium 60 11 No
## 107 102 33 0 217 139 Medium 70 18 No
## 302 99 93 0 198 87 Medium 57 16 Yes
## 24 121 31 0 292 109 Medium 79 10 Yes
## 276 107 119 11 210 132 Medium 53 11 Yes
## 267 128 93 12 343 112 Good 73 17 No
## 307 131 32 1 85 133 Medium 48 12 Yes
## 394 109 51 10 26 120 Medium 30 17 No
## 396 138 108 17 203 128 Good 33 14 Yes
## 214 149 84 5 220 139 Medium 33 10 Yes
## 304 133 52 16 290 99 Medium 43 11 Yes
## 338 130 38 0 283 102 Medium 80 15 Yes
## 81 113 100 16 353 79 Bad 68 11 Yes
## 232 132 69 0 123 122 Medium 27 11 No
## 153 128 78 0 341 128 Good 45 13 No
## 38 121 41 5 412 110 Medium 54 10 Yes
## 242 136 63 0 160 94 Medium 38 12 Yes
## 260 123 36 10 467 100 Bad 74 11 No
## 241 159 80 0 362 121 Medium 26 18 Yes
## 5 141 64 3 340 128 Bad 38 13 Yes
## 372 152 81 0 191 126 Medium 54 16 Yes
## 336 120 70 15 464 110 Medium 72 15 Yes
## 41 119 98 0 18 126 Bad 73 17 No
## 182 121 83 0 79 91 Medium 68 11 Yes
## 280 141 57 13 376 158 Medium 64 18 Yes
## 87 150 84 9 432 134 Medium 64 15 Yes
## 104 123 91 0 334 96 Bad 78 17 Yes
## 15 107 117 11 148 118 Good 52 18 Yes
## 308 138 92 0 13 120 Bad 61 12 Yes
## 12 117 94 4 503 94 Good 50 13 Yes
## 230 98 104 0 404 72 Medium 27 18 No
## 213 145 69 19 501 105 Medium 45 11 Yes
## 300 135 40 17 497 96 Medium 54 17 No
## 264 116 26 6 434 115 Medium 25 17 Yes
## 136 96 94 14 384 120 Medium 36 18 No
## 23 128 46 6 497 138 Medium 42 13 Yes
## 332 135 63 15 213 134 Medium 32 10 Yes
## 154 150 36 7 488 150 Medium 25 17 No
## 269 123 57 0 66 105 Medium 39 11 Yes
## 392 153 63 0 49 124 Bad 56 16 Yes
## 231 115 60 0 119 114 Bad 38 14 No
## 368 95 106 0 256 53 Good 52 17 Yes
## 175 139 24 0 358 185 Medium 79 15 No
## 196 117 93 4 420 112 Bad 66 11 Yes
## 389 135 89 11 245 78 Bad 79 16 Yes
## 315 133 33 10 333 129 Good 71 14 Yes
## 140 146 62 10 310 94 Medium 30 13 No
## 96 134 25 10 237 148 Medium 59 13 Yes
## 399 100 79 7 284 95 Bad 50 12 Yes
## 295 148 76 3 126 99 Good 60 11 Yes
## 71 89 81 15 237 99 Good 74 12 Yes
## 377 141 60 19 319 92 Good 44 11 Yes
## 395 130 58 19 366 139 Bad 33 16 Yes
## 228 113 64 10 68 101 Medium 57 16 Yes
## 349 132 102 20 459 107 Good 49 11 Yes
## 117 135 75 0 202 128 Medium 80 10 No
## 254 124 24 5 288 122 Medium 57 12 No
## 340 134 44 4 219 126 Good 44 15 Yes
## 310 131 111 13 33 80 Bad 68 18 Yes
## 164 130 64 0 40 106 Bad 39 17 No
## 246 114 43 0 199 88 Good 57 10 No
## 74 118 90 10 54 104 Good 31 11 No
## 376 132 46 4 206 124 Medium 73 11 Yes
## 160 119 60 0 372 70 Bad 30 18 No
## 19 110 110 0 408 68 Good 46 17 No
## 170 104 41 15 492 77 Good 73 18 Yes
## 218 106 44 0 481 111 Medium 70 14 No
## 305 123 98 12 408 134 Good 29 10 Yes
## 179 104 71 14 89 81 Medium 25 14 No
## 127 153 68 2 60 133 Good 59 16 Yes
## 374 137 71 0 402 116 Medium 78 17 Yes
## 148 140 54 9 402 119 Good 41 16 No
## 78 118 71 12 44 89 Medium 67 18 No
## 110 115 65 0 217 90 Medium 60 17 No
## 210 98 21 11 326 90 Bad 76 11 No
## 10 132 113 0 131 124 Medium 76 17 No
## 347 132 107 0 144 125 Medium 33 13 No
## 18 147 74 13 251 131 Good 52 10 Yes
## 158 121 58 8 249 90 Medium 48 13 No
## 180 144 25 3 70 116 Medium 77 18 Yes
## 284 135 110 0 112 117 Medium 80 16 No
## 177 138 107 9 480 154 Medium 47 11 No
## 240 123 105 0 149 118 Bad 62 16 Yes
## 6 124 113 13 501 72 Bad 78 16 No
## 90 128 66 3 493 119 Medium 45 16 No
## 203 121 78 4 413 130 Bad 46 10 No
## 250 125 67 0 86 117 Bad 65 11 Yes
## 25 145 119 16 294 113 Bad 42 12 Yes
## 262 121 42 4 188 118 Medium 54 15 Yes
## 121 128 105 11 249 131 Medium 63 13 Yes
## 256 123 81 8 198 81 Bad 80 15 Yes
## 287 117 118 11 429 113 Medium 67 18 No
## 68 126 61 14 152 115 Medium 47 16 Yes
## 45 85 79 6 325 95 Medium 69 13 Yes
## 342 98 120 0 268 93 Medium 72 10 No
## 390 128 42 8 328 107 Medium 35 12 Yes
## 53 153 40 3 112 129 Bad 39 18 Yes
## 132 108 69 3 208 94 Medium 77 16 Yes
## 236 126 32 8 95 132 Medium 50 17 Yes
## 346 121 68 0 279 149 Good 79 12 Yes
## 28 98 118 0 19 107 Medium 64 17 Yes
## 163 122 74 0 424 149 Medium 51 13 Yes
## 56 143 81 5 60 154 Medium 61 18 Yes
## 152 111 58 17 407 103 Good 75 17 No
## 238 151 28 8 499 135 Medium 48 10 Yes
## 341 140 29 0 105 91 Bad 43 16 Yes
## 353 133 103 14 288 122 Good 61 17 Yes
## 201 144 92 0 349 146 Medium 62 12 No
## 8 136 81 15 425 120 Good 67 10 Yes
## 363 131 55 0 26 110 Bad 79 12 Yes
## 299 148 63 0 312 130 Good 63 15 Yes
## 268 134 82 7 473 112 Bad 51 12 No
## 95 115 97 5 134 84 Bad 55 11 Yes
## 22 134 29 12 239 109 Good 62 18 No
## 172 93 106 12 416 55 Medium 75 15 Yes
## 92 97 46 11 267 107 Medium 80 15 Yes
## 130 143 120 7 279 147 Bad 40 10 No
## 339 112 24 0 164 101 Medium 45 11 Yes
## 31 125 94 0 447 89 Good 30 12 Yes
## 126 89 78 0 181 49 Medium 43 15 No
## 206 113 22 1 317 132 Medium 28 12 Yes
## 47 127 90 14 16 70 Medium 48 15 No
## 212 117 118 14 445 120 Medium 32 15 Yes
## 168 106 73 0 216 93 Medium 60 13 Yes
## 277 135 69 14 296 130 Medium 73 15 Yes
## 131 94 84 13 497 77 Medium 51 12 Yes
## 398 162 26 12 368 159 Medium 40 18 Yes
## 255 108 104 23 353 129 Good 37 17 Yes
## 184 118 74 6 426 102 Medium 80 18 Yes
## 357 142 109 0 111 164 Good 72 12 Yes
## 39 109 73 0 454 102 Medium 65 15 Yes
## 147 114 83 0 412 131 Bad 39 14 Yes
## 318 142 30 0 472 136 Good 80 15 No
## 167 119 67 17 151 137 Medium 55 11 Yes
## 40 130 60 0 144 138 Bad 38 10 No
## 166 147 58 7 100 191 Bad 27 15 Yes
## 67 127 92 0 508 91 Medium 56 18 Yes
## 222 124 44 0 125 107 Medium 80 11 Yes
## 209 86 54 0 497 64 Bad 33 12 Yes
## 145 132 68 0 264 123 Good 34 11 No
## 58 93 91 0 22 117 Bad 75 11 Yes
## 60 118 71 4 148 114 Medium 80 13 Yes
## 137 131 75 0 10 120 Bad 31 18 No
## 292 118 70 0 106 89 Bad 39 17 Yes
## 29 103 74 0 359 97 Bad 55 11 Yes
## 51 99 32 18 341 108 Bad 80 16 Yes
## 330 100 54 9 433 89 Good 45 12 Yes
## 275 135 93 2 67 119 Medium 34 11 Yes
## 386 131 73 13 455 132 Medium 62 17 Yes
## 106 104 100 8 398 97 Medium 61 11 Yes
## 370 135 100 22 463 122 Medium 36 14 Yes
## 21 125 90 2 367 131 Medium 35 18 Yes
## 344 117 42 10 371 121 Bad 26 14 Yes
## 188 117 32 0 142 96 Bad 62 17 Yes
## 100 121 47 3 220 107 Bad 56 16 No
## 151 122 84 8 176 114 Good 57 10 No
## 169 129 89 0 425 117 Medium 45 10 Yes
## 64 119 88 10 170 101 Medium 61 13 Yes
## 364 111 75 1 377 108 Good 25 12 Yes
## 207 162 67 0 27 160 Medium 77 17 Yes
## 382 124 65 21 496 151 Bad 77 13 Yes
## 199 112 80 5 500 128 Medium 69 10 Yes
## 98 161 82 5 287 129 Bad 33 16 Yes
## 322 123 39 5 499 98 Medium 34 15 Yes
## 204 131 82 0 132 157 Bad 25 14 Yes
## 296 118 35 14 502 137 Medium 79 10 No
## 393 129 42 13 315 130 Bad 34 13 Yes
## 326 144 69 11 131 104 Medium 47 11 Yes
## 243 124 46 0 199 135 Medium 52 14 No
## 13 122 35 2 393 136 Medium 62 18 Yes
## 77 102 87 10 346 70 Medium 64 15 Yes
## 273 113 33 0 14 63 Good 38 12 Yes
## 270 159 69 0 438 166 Medium 46 17 Yes
## 366 154 30 0 122 162 Medium 57 17 No
## 65 100 67 12 184 104 Medium 32 16 No
## 171 128 39 12 356 118 Medium 71 10 Yes
## 259 108 38 0 251 81 Bad 72 14 No
## 359 123 96 10 71 118 Bad 69 11 Yes
## 198 124 61 0 333 138 Medium 76 16 Yes
## 281 121 86 10 496 145 Bad 51 10 Yes
## 155 129 69 10 289 110 Medium 50 16 No
## 327 133 30 0 152 122 Medium 53 17 Yes
## 200 122 88 5 335 126 Medium 64 14 Yes
## 4 117 100 4 466 97 Medium 55 14 Yes
## 89 117 42 7 144 111 Medium 62 10 Yes
## 314 103 81 3 491 54 Medium 66 13 Yes
## 202 138 83 0 139 134 Medium 54 18 Yes
## 320 127 45 19 459 129 Medium 57 11 No
## 224 110 45 9 276 125 Medium 62 14 Yes
## 2 111 48 16 260 83 Good 65 10 Yes
## 73 115 45 0 432 116 Medium 25 15 Yes
## 333 106 33 20 354 104 Medium 61 12 Yes
## 361 118 86 7 265 114 Good 52 15 No
## 70 127 59 0 339 99 Medium 65 12 Yes
## 303 108 77 13 388 110 Bad 74 14 Yes
## 143 124 84 0 300 104 Medium 77 15 Yes
## 365 122 21 16 488 131 Good 30 14 Yes
## 61 122 102 19 469 123 Bad 29 13 Yes
## 116 139 35 0 95 129 Medium 42 13 Yes
## 400 134 37 0 27 120 Good 49 16 Yes
## 42 157 53 0 403 124 Bad 58 16 Yes
## 294 123 84 0 74 89 Good 59 10 Yes
## 352 124 115 16 458 105 Medium 62 16 No
## 387 152 116 0 170 160 Medium 39 16 Yes
## 321 136 70 12 171 152 Medium 44 18 Yes
## 215 115 115 3 48 107 Medium 73 18 Yes
## 293 113 66 16 322 74 Good 76 15 Yes
## 156 98 72 0 59 69 Medium 65 16 Yes
## 367 124 56 11 447 134 Medium 53 12 No
## 312 146 68 12 328 132 Bad 51 14 Yes
## 91 115 22 0 491 103 Medium 64 11 No
## 278 136 48 12 326 125 Medium 36 16 Yes
## 135 132 31 0 327 131 Medium 76 16 Yes
## 248 123 114 0 298 151 Bad 34 16 Yes
## 384 98 117 0 76 68 Medium 63 10 Yes
## 134 132 98 2 265 97 Bad 62 12 Yes
## 334 136 60 7 303 147 Medium 41 10 Yes
## 290 143 77 25 448 156 Medium 43 17 Yes
## 119 112 88 2 243 99 Medium 62 11 Yes
## 375 131 47 7 90 118 Medium 47 12 Yes
## 44 123 42 11 16 134 Medium 59 13 Yes
## 343 137 102 13 422 118 Medium 71 10 No
## 94 145 30 0 67 104 Medium 55 17 Yes
## 109 107 79 2 488 103 Bad 65 16 Yes
## 298 118 83 13 276 104 Bad 75 10 Yes
## 323 140 50 10 300 139 Good 60 15 Yes
## 122 125 89 10 380 87 Bad 28 10 Yes
## 263 120 77 15 86 132 Medium 48 18 Yes
## 57 133 82 0 54 84 Medium 50 17 Yes
## 324 107 105 18 428 103 Medium 34 12 Yes
## 26 139 32 0 176 82 Good 54 11 No
## 32 136 58 16 241 131 Medium 44 18 Yes
## 120 130 94 8 137 128 Medium 64 12 Yes
## 82 116 72 0 237 128 Good 70 13 Yes
## 311 175 65 29 419 166 Medium 53 12 Yes
## 66 122 26 0 197 128 Medium 55 13 No
## 99 122 77 24 382 127 Good 36 16 No
## 253 133 97 0 70 117 Medium 32 16 Yes
## 43 77 69 0 25 24 Medium 50 18 Yes
## 14 115 28 11 29 86 Good 53 18 Yes
## 79 134 48 1 139 145 Medium 65 12 Yes
## 356 130 100 0 306 146 Good 42 11 Yes
## 247 120 56 20 266 90 Bad 78 18 Yes
## 216 116 83 15 170 144 Bad 71 11 Yes
## 274 116 106 8 244 86 Medium 58 12 Yes
## US High_Sales
## 397 Yes 0
## 279 Yes 0
## 187 No 1
## 266 Yes 0
## 369 Yes 1
## 388 Yes 1
## 27 Yes 1
## 379 Yes 0
## 373 No 0
## 59 Yes 0
## 159 Yes 1
## 142 No 0
## 37 No 1
## 288 Yes 0
## 63 Yes 0
## 285 No 0
## 289 No 0
## 252 Yes 0
## 345 Yes 1
## 118 No 1
## 88 Yes 1
## 195 Yes 0
## 174 Yes 0
## 371 Yes 0
## 306 Yes 1
## 391 Yes 0
## 317 Yes 1
## 16 No 1
## 325 Yes 0
## 52 No 0
## 186 Yes 1
## 144 Yes 0
## 49 No 0
## 50 No 1
## 114 Yes 0
## 185 Yes 1
## 107 No 0
## 302 Yes 0
## 24 No 0
## 276 Yes 0
## 267 Yes 1
## 307 Yes 0
## 394 Yes 0
## 396 Yes 1
## 214 Yes 1
## 304 Yes 1
## 338 No 1
## 81 Yes 1
## 232 No 1
## 153 No 0
## 38 Yes 0
## 242 No 1
## 260 Yes 0
## 241 No 1
## 5 No 0
## 372 No 1
## 336 Yes 0
## 41 No 0
## 182 No 0
## 280 Yes 0
## 87 No 1
## 104 Yes 0
## 15 Yes 1
## 308 No 0
## 12 Yes 1
## 230 No 1
## 213 Yes 1
## 300 Yes 1
## 264 Yes 0
## 136 Yes 0
## 23 No 0
## 332 Yes 1
## 154 Yes 0
## 269 No 0
## 392 No 0
## 231 No 0
## 368 No 1
## 175 No 0
## 196 Yes 0
## 389 Yes 1
## 315 Yes 0
## 140 Yes 1
## 96 Yes 0
## 399 Yes 0
## 295 Yes 1
## 71 Yes 1
## 377 Yes 1
## 395 Yes 0
## 228 Yes 1
## 349 Yes 1
## 117 No 0
## 254 Yes 0
## 340 Yes 1
## 310 Yes 1
## 164 No 0
## 246 Yes 1
## 74 Yes 1
## 376 No 0
## 160 No 1
## 19 Yes 1
## 170 Yes 1
## 218 No 0
## 305 Yes 1
## 179 Yes 1
## 127 Yes 1
## 374 No 0
## 148 Yes 1
## 78 Yes 0
## 110 No 1
## 210 Yes 0
## 10 Yes 0
## 347 No 1
## 18 Yes 1
## 158 Yes 1
## 180 Yes 0
## 284 No 0
## 177 Yes 0
## 240 Yes 0
## 6 Yes 1
## 90 No 0
## 203 Yes 0
## 250 No 0
## 25 Yes 1
## 262 Yes 0
## 121 Yes 0
## 256 Yes 0
## 287 Yes 0
## 68 Yes 1
## 45 Yes 0
## 342 No 0
## 390 Yes 1
## 53 Yes 0
## 132 No 0
## 236 Yes 0
## 346 No 0
## 28 No 0
## 163 No 0
## 56 Yes 0
## 152 Yes 1
## 238 Yes 1
## 341 No 0
## 353 Yes 1
## 201 No 0
## 8 Yes 1
## 363 Yes 0
## 299 No 1
## 268 Yes 0
## 95 Yes 1
## 22 Yes 1
## 172 Yes 1
## 92 Yes 0
## 130 Yes 0
## 339 No 0
## 31 No 1
## 126 No 1
## 206 No 0
## 47 Yes 1
## 212 Yes 1
## 168 No 0
## 277 Yes 0
## 131 Yes 1
## 398 Yes 0
## 255 Yes 1
## 184 Yes 0
## 357 No 0
## 39 No 0
## 147 No 0
## 318 No 0
## 167 Yes 0
## 40 No 0
## 166 Yes 0
## 67 No 1
## 222 No 0
## 209 No 0
## 145 No 1
## 58 No 0
## 60 No 0
## 137 No 0
## 292 No 0
## 29 Yes 0
## 51 Yes 0
## 330 Yes 1
## 275 Yes 0
## 386 Yes 0
## 106 Yes 0
## 370 Yes 1
## 21 Yes 0
## 344 Yes 0
## 188 No 0
## 100 Yes 0
## 151 Yes 1
## 169 No 0
## 64 Yes 1
## 364 No 1
## 207 Yes 0
## 382 Yes 0
## 199 Yes 0
## 98 Yes 0
## 322 No 0
## 204 No 0
## 296 Yes 0
## 393 Yes 0
## 326 Yes 1
## 243 No 0
## 13 No 0
## 77 Yes 1
## 273 No 1
## 270 No 0
## 366 No 0
## 65 Yes 0
## 171 Yes 1
## 259 No 0
## 359 Yes 0
## 198 No 0
## 281 Yes 0
## 155 Yes 0
## 327 No 0
## 200 Yes 0
## 4 Yes 0
## 89 Yes 0
## 314 No 1
## 202 No 0
## 320 Yes 0
## 224 Yes 0
## 2 Yes 1
## 73 No 0
## 333 Yes 0
## 361 Yes 1
## 70 No 0
## 303 Yes 0
## 143 No 0
## 365 Yes 1
## 61 Yes 1
## 116 No 1
## 400 Yes 1
## 42 No 0
## 294 No 1
## 352 Yes 1
## 387 No 0
## 321 Yes 0
## 215 Yes 0
## 293 Yes 1
## 156 No 0
## 367 Yes 0
## 312 Yes 0
## 91 No 0
## 278 Yes 0
## 135 No 0
## 248 No 0
## 384 No 1
## 134 Yes 0
## 334 Yes 0
## 290 Yes 1
## 119 Yes 0
## 375 Yes 1
## 44 Yes 0
## 343 Yes 0
## 94 No 1
## 109 No 0
## 298 Yes 0
## 323 Yes 1
## 122 Yes 1
## 263 Yes 0
## 57 No 1
## 324 Yes 1
## 26 No 1
## 32 Yes 1
## 120 Yes 0
## 82 No 0
## 311 Yes 1
## 66 No 0
## 99 Yes 1
## 253 No 1
## 43 No 1
## 14 Yes 1
## 79 Yes 0
## 356 No 0
## 247 Yes 0
## 216 Yes 0
## 274 Yes 1store_sales_test## CompPrice Income Advertising Population Price ShelveLoc Age Education Urban
## 1 138 73 11 276 120 Bad 42 17 Yes
## 3 113 35 10 269 80 Medium 59 12 Yes
## 7 115 105 0 45 108 Medium 71 15 Yes
## 9 132 110 0 108 124 Medium 76 10 No
## 11 121 78 9 150 100 Bad 26 10 No
## 17 118 32 0 284 110 Good 63 13 Yes
## 20 129 76 16 58 121 Medium 69 12 Yes
## 30 104 99 15 226 102 Bad 58 17 Yes
## 33 107 32 12 236 137 Good 64 10 No
## 34 114 38 13 317 128 Good 50 16 Yes
## 35 115 54 0 406 128 Medium 42 17 Yes
## 36 131 84 11 29 96 Medium 44 17 No
## 46 141 63 0 168 135 Bad 44 12 Yes
## 48 126 98 0 173 108 Bad 55 16 Yes
## 54 109 64 13 39 119 Medium 61 17 Yes
## 55 134 103 13 25 144 Medium 76 17 No
## 62 105 32 0 358 107 Medium 26 13 No
## 69 149 69 20 366 134 Good 60 13 Yes
## 72 148 51 16 148 150 Medium 58 17 No
## 75 150 68 5 125 136 Medium 64 13 No
## 76 88 111 23 480 92 Bad 36 16 No
## 80 134 67 0 286 90 Bad 41 13 Yes
## 83 151 83 4 325 139 Good 28 17 Yes
## 84 109 36 7 468 94 Bad 56 11 Yes
## 85 111 25 0 52 121 Bad 43 18 No
## 86 125 103 0 304 112 Medium 49 13 No
## 93 114 113 0 97 125 Medium 29 12 Yes
## 97 147 42 10 407 132 Good 73 16 No
## 101 113 69 11 94 106 Medium 76 12 No
## 102 128 93 0 89 118 Medium 34 18 Yes
## 103 113 22 0 57 97 Medium 65 16 No
## 105 121 96 0 472 138 Medium 51 12 Yes
## 108 134 107 0 104 108 Medium 60 12 Yes
## 111 128 62 7 125 116 Medium 43 14 Yes
## 112 132 118 12 272 151 Medium 43 14 Yes
## 113 116 99 5 298 125 Good 62 12 Yes
## 115 122 87 9 17 106 Medium 65 13 Yes
## 123 119 100 5 45 108 Medium 75 10 Yes
## 124 127 103 0 125 155 Good 29 15 No
## 125 131 113 0 181 120 Good 63 14 Yes
## 128 125 48 3 192 116 Medium 51 14 Yes
## 129 133 100 3 350 126 Bad 55 13 Yes
## 133 125 87 9 232 136 Good 72 10 Yes
## 138 128 42 0 436 118 Medium 80 11 Yes
## 139 125 103 12 371 109 Medium 44 10 Yes
## 141 133 60 10 277 129 Medium 45 18 Yes
## 146 144 63 11 27 117 Medium 47 17 Yes
## 149 110 119 0 384 97 Medium 72 14 No
## 150 121 120 13 140 87 Medium 56 11 Yes
## 157 146 34 0 220 157 Good 51 16 Yes
## 161 111 28 0 486 111 Medium 29 12 No
## 162 143 21 5 81 160 Medium 67 12 No
## 165 148 64 0 58 141 Medium 27 13 No
## 173 104 102 13 123 110 Good 35 16 Yes
## 176 115 89 0 38 122 Medium 25 12 Yes
## 178 138 72 0 148 94 Medium 27 17 Yes
## 181 137 112 15 434 149 Bad 66 13 Yes
## 183 137 60 4 230 140 Bad 25 13 Yes
## 189 116 37 0 426 90 Medium 76 15 Yes
## 190 118 117 18 509 104 Medium 26 15 No
## 191 130 37 13 297 101 Medium 37 13 No
## 192 156 42 13 170 173 Good 74 14 Yes
## 193 108 26 0 408 93 Medium 56 14 No
## 194 139 70 7 71 96 Good 61 10 Yes
## 197 130 28 6 410 133 Bad 72 16 Yes
## 205 155 80 0 237 124 Medium 37 14 Yes
## 208 111 105 0 466 97 Bad 61 10 No
## 211 125 41 2 357 123 Bad 47 14 No
## 217 141 33 0 243 144 Medium 34 17 Yes
## 219 138 61 12 156 120 Medium 25 14 Yes
## 220 116 79 19 359 116 Good 58 17 Yes
## 221 131 120 15 262 124 Medium 30 10 Yes
## 223 136 119 6 178 145 Medium 35 13 Yes
## 225 134 82 0 464 141 Medium 48 13 No
## 226 107 25 0 412 82 Bad 36 14 Yes
## 227 119 33 0 245 122 Good 56 14 Yes
## 229 149 73 13 381 163 Bad 26 11 No
## 233 137 80 10 24 105 Good 61 15 Yes
## 234 123 76 18 218 120 Medium 29 14 No
## 235 115 62 11 289 129 Good 56 16 No
## 237 141 34 16 361 108 Medium 69 10 Yes
## 239 121 24 0 200 133 Good 73 13 Yes
## 244 124 25 13 87 110 Medium 57 10 Yes
## 245 130 30 0 391 100 Medium 26 18 Yes
## 249 111 52 0 12 101 Medium 61 11 Yes
## 251 137 105 10 435 156 Good 72 14 Yes
## 257 147 40 0 277 144 Medium 73 10 Yes
## 258 125 62 14 477 112 Medium 80 13 Yes
## 261 129 117 8 400 101 Bad 36 10 Yes
## 265 128 29 5 324 159 Good 31 15 Yes
## 271 119 26 0 284 89 Good 26 10 Yes
## 272 111 56 0 504 110 Medium 62 16 Yes
## 282 122 69 7 303 105 Good 45 16 No
## 283 150 96 0 80 154 Good 61 11 Yes
## 286 146 26 11 261 131 Medium 39 10 Yes
## 291 107 111 14 400 103 Medium 41 11 No
## 297 127 44 13 160 123 Good 63 18 Yes
## 301 116 78 1 158 99 Medium 45 11 Yes
## 309 126 80 19 436 126 Medium 52 10 Yes
## 313 137 117 5 337 135 Bad 38 10 Yes
## 316 131 21 8 220 171 Good 29 14 Yes
## 319 116 72 10 456 130 Good 41 14 No
## 328 112 38 17 316 104 Medium 80 16 Yes
## 329 117 66 1 65 111 Bad 55 11 Yes
## 331 122 59 0 501 112 Bad 32 14 No
## 335 93 117 9 489 83 Bad 42 13 Yes
## 337 138 35 6 60 143 Bad 28 18 Yes
## 348 96 39 0 161 112 Good 27 14 No
## 350 134 27 18 467 96 Medium 49 14 No
## 351 111 101 17 266 91 Medium 63 17 No
## 354 107 67 12 430 92 Medium 35 12 No
## 355 133 31 1 80 145 Medium 42 18 Yes
## 358 103 73 3 276 72 Medium 34 15 Yes
## 360 130 62 11 396 130 Bad 66 14 Yes
## 362 131 25 10 183 104 Medium 56 15 No
## 378 132 61 0 263 125 Medium 41 12 No
## 380 125 111 0 404 107 Bad 54 15 Yes
## 381 106 64 10 17 89 Medium 68 17 Yes
## 383 121 28 19 315 121 Medium 66 14 Yes
## 385 123 37 15 348 112 Good 28 12 Yes
## US High_Sales
## 1 Yes 1
## 3 Yes 1
## 7 No 0
## 9 No 0
## 11 Yes 1
## 17 No 0
## 20 Yes 1
## 30 Yes 0
## 33 Yes 0
## 34 Yes 1
## 35 Yes 0
## 36 Yes 1
## 46 Yes 0
## 48 No 0
## 54 Yes 0
## 55 Yes 0
## 62 No 0
## 69 Yes 1
## 72 Yes 0
## 75 Yes 0
## 76 Yes 1
## 80 No 1
## 83 Yes 1
## 84 Yes 0
## 85 No 0
## 86 No 1
## 93 No 0
## 97 Yes 1
## 101 Yes 0
## 102 No 0
## 103 No 0
## 105 No 0
## 108 No 1
## 111 Yes 1
## 112 Yes 0
## 113 Yes 0
## 115 Yes 1
## 123 Yes 0
## 124 Yes 1
## 125 No 1
## 128 Yes 0
## 129 Yes 0
## 133 Yes 1
## 138 No 0
## 139 Yes 1
## 141 Yes 0
## 146 Yes 1
## 149 Yes 0
## 150 Yes 1
## 157 No 0
## 161 No 0
## 162 Yes 0
## 165 Yes 1
## 173 Yes 1
## 176 No 0
## 178 Yes 1
## 181 Yes 0
## 183 No 0
## 189 No 1
## 190 Yes 1
## 191 Yes 1
## 192 Yes 0
## 193 No 0
## 194 Yes 1
## 197 Yes 0
## 205 No 1
## 208 No 1
## 211 Yes 0
## 217 No 0
## 219 Yes 1
## 220 Yes 1
## 221 Yes 1
## 223 Yes 0
## 225 No 0
## 226 No 0
## 227 No 0
## 229 Yes 0
## 233 Yes 1
## 234 Yes 1
## 235 Yes 1
## 237 Yes 1
## 239 No 0
## 244 Yes 0
## 245 No 1
## 249 Yes 0
## 251 Yes 1
## 257 No 0
## 258 Yes 1
## 261 Yes 0
## 265 Yes 0
## 271 No 1
## 272 No 0
## 282 Yes 1
## 283 No 0
## 286 Yes 0
## 291 Yes 1
## 297 Yes 1
## 301 Yes 1
## 309 Yes 1
## 313 Yes 0
## 316 Yes 0
## 319 Yes 1
## 328 Yes 0
## 329 Yes 0
## 331 No 0
## 335 Yes 0
## 337 No 0
## 348 No 0
## 350 Yes 1
## 351 Yes 1
## 354 Yes 1
## 355 Yes 0
## 358 Yes 1
## 360 Yes 0
## 362 Yes 1
## 378 No 0
## 380 No 0
## 381 Yes 1
## 383 Yes 0
## 385 Yes 12. Logistic Regression (5 points)
- Fit a logistic regression model to predict
High_Salesusing all other variables as predictors. Please use the training dataset.
# Your code here
store_sales_glm <- glm(High_Sales ~ ., data = store_sales_train, family = "binomial")
store_sales_glm##
## Call: glm(formula = High_Sales ~ ., family = "binomial", data = store_sales_train)
##
## Coefficients:
## (Intercept) CompPrice Income Advertising
## -6.787364 0.201653 0.034553 0.371516
## Population Price ShelveLocGood ShelveLocMedium
## -0.002566 -0.179454 9.338531 4.270635
## Age Education UrbanYes USYes
## -0.087756 -0.133422 0.140172 -1.626954
##
## Degrees of Freedom: 279 Total (i.e. Null); 268 Residual
## Null Deviance: 375.2
## Residual Deviance: 106.2 AIC: 130.2- Use the
summary()function to examine your fitted model. What is the estimated coefficient forPrice? Is it statistically significant? Please interpret the number using the odds ratio?
# Your code here
summary(store_sales_glm)##
## Call:
## glm(formula = High_Sales ~ ., family = "binomial", data = store_sales_train)
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -6.787364 3.390753 -2.002 0.04531 *
## CompPrice 0.201653 0.034124 5.909 3.43e-09 ***
## Income 0.034553 0.010828 3.191 0.00142 **
## Advertising 0.371516 0.075899 4.895 9.84e-07 ***
## Population -0.002566 0.001927 -1.332 0.18296
## Price -0.179454 0.026173 -6.856 7.06e-12 ***
## ShelveLocGood 9.338531 1.407041 6.637 3.20e-11 ***
## ShelveLocMedium 4.270635 0.891648 4.790 1.67e-06 ***
## Age -0.087756 0.019324 -4.541 5.59e-06 ***
## Education -0.133422 0.103935 -1.284 0.19924
## UrbanYes 0.140172 0.594386 0.236 0.81357
## USYes -1.626954 0.830909 -1.958 0.05023 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 375.21 on 279 degrees of freedom
## Residual deviance: 106.23 on 268 degrees of freedom
## AIC: 130.23
##
## Number of Fisher Scoring iterations: 7exp(-0.179454)## [1] 0.8357264Comments:
The estimated coefficient for Price is -0.179454. The coefficient is statistically significant. With the odds ratio, we get 0.8357264.
- Generate predicted probabilities on the testing dataset. Then, obtain the predicted classes using 0.6 as the cutoff value (threshold).
# Your code here
pred_store_test_glm <- predict(store_sales_glm, newdata = store_sales_test, type = "response")
pred_store_class_test_glm <- as.numeric(pred_store_test_glm > 0.6)
pred_store_test_glm## 1 3 7 9 11 17
## 1.157325e-01 8.679169e-01 3.602412e-02 6.718566e-02 5.195827e-01 4.651615e-01
## 20 30 33 34 35 36
## 7.428930e-01 1.044761e-02 1.668735e-02 4.724336e-01 1.345831e-04 9.970722e-01
## 46 48 54 55 62 69
## 4.162308e-04 9.575538e-03 1.698010e-02 2.720861e-02 1.244826e-02 9.998689e-01
## 72 75 76 80 83 84
## 2.229800e-01 1.460593e-01 2.101886e-01 6.159187e-01 9.953430e-01 1.005983e-03
## 85 86 93 97 101 102
## 9.516365e-06 3.397414e-01 9.028151e-02 9.213292e-01 8.167088e-02 4.648729e-01
## 103 105 108 111 112 113
## 1.259301e-02 1.215173e-03 8.615046e-01 4.432965e-01 9.223529e-02 3.766606e-01
## 115 123 124 125 128 129
## 6.091053e-01 1.084842e-01 6.983759e-02 9.738395e-01 2.468652e-02 9.532738e-04
## 133 138 139 141 146 149
## 4.917953e-01 2.742818e-03 9.710408e-01 1.671238e-01 9.789576e-01 1.179054e-02
## 150 157 161 162 165 173
## 9.991060e-01 1.149129e-01 1.122862e-02 1.088691e-04 1.620102e-01 9.941107e-01
## 176 178 181 183 189 190
## 1.304405e-01 9.881844e-01 1.381137e-03 6.038800e-03 2.606047e-02 9.978266e-01
## 191 192 193 194 197 205
## 9.867588e-01 2.610870e-01 1.264157e-02 9.999553e-01 4.856875e-06 9.751246e-01
## 208 211 217 219 220 221
## 2.315668e-03 4.409301e-05 1.077275e-02 9.877998e-01 9.942278e-01 9.947318e-01
## 223 225 226 227 229 233
## 1.792816e-01 6.047329e-03 6.653986e-03 1.860492e-01 6.734906e-03 9.998652e-01
## 234 235 237 239 244 245
## 9.697155e-01 3.550736e-01 9.792052e-01 9.946575e-03 5.976173e-01 7.761091e-01
## 249 251 257 258 261 265
## 8.165277e-03 2.204428e-01 3.526629e-03 1.778538e-01 7.520191e-01 1.273507e-02
## 271 272 282 283 286 291
## 9.993047e-01 1.270966e-03 9.918927e-01 8.312449e-01 8.157933e-01 8.692320e-01
## 297 301 309 313 316 319
## 9.315542e-01 2.435940e-01 8.320895e-01 1.090878e-02 1.114910e-02 6.350951e-01
## 328 329 331 335 337 348
## 8.175433e-02 2.227808e-04 2.010502e-03 2.404372e-02 2.340082e-03 1.836541e-01
## 350 351 354 355 358 360
## 9.972800e-01 9.621623e-01 8.722449e-01 3.175979e-04 8.569082e-01 3.954597e-04
## 362 378 380 381 383 385
## 6.907155e-01 1.094528e-01 1.011670e-02 2.784145e-01 1.469050e-01 9.995331e-01pred_store_class_test_glm## [1] 0 1 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 1 0 0 0 1 1 0 0 0 0 1 0 0 0 0 1 0 0 0 1
## [38] 0 0 1 0 0 0 0 1 0 1 0 1 0 0 0 0 1 0 1 0 0 0 1 1 0 0 1 0 1 0 0 0 1 1 1 0 0
## [75] 0 0 0 1 1 0 1 0 0 1 0 0 0 0 1 0 1 0 1 1 1 1 1 0 1 0 0 1 0 0 0 0 0 0 1 1 1
## [112] 0 1 0 1 0 0 0 0 1- Create a confusion matrix using the testing dataset and report Misclassification Rate (MR).
# Your code here
confusion_mat_store_glm <- table(actual = store_sales_test$High_Sales, pred = pred_store_class_test_glm)
confusion_mat_store_glm## pred
## actual 0 1
## 0 63 3
## 1 16 381 - sum(diag(confusion_mat_store_glm))/sum(confusion_mat_store_glm)## [1] 0.1583333Comments:
The misclassification is 0.158333, or 15.8%.
- Draw an ROC curve and calculate the AUC (Area Under Curve) for this logistic regression model on the testing dataset. Do you think the prediction performance is acceptable?
# Your code here
library(pROC)## Warning: package 'pROC' was built under R version 4.5.2## Type 'citation("pROC")' for a citation.##
## Attaching package: 'pROC'## The following objects are masked from 'package:stats':
##
## cov, smooth, varstore_glm_roc <- roc(store_sales_test$High_Sales, pred_store_test_glm)## Setting levels: control = 0, case = 1## Setting direction: controls < casesplot(store_glm_roc)
auc(store_glm_roc)## Area under the curve: 0.9374Comments:
The setting levels are control = 0, and case = 1. The setting direction is controls < cases. Finally, area under the curve is 0.9374. With the Plot looking not organized. In conclusion, it’s not acceptable.
Part II: Regression Tree
0. Background
You have been hired by a health insurance company to improve their pricing strategy. They want to understand which factors contribute most to high individual medical costs.
Data Dictionary:
charges(Target): Individual medical costs billed by health insurance.
age: Age of primary beneficiary.
sex: Insurance contractor gender (female, male).
bmi: Body mass index (providing an understanding of body weights that are relatively high or low relative to height).
children: Number of children covered by health insurance / Number of dependents.
smoker: Smoking status (yes, no).
region: The beneficiary’s residential area in the US (northeast, southeast, southwest, northwest).
1. Data Preparation (0.5 point)
- Load the data from the file
insurance.csvand name itinsurance.
- Split the data into training (70%) and test (30%) sets. Use
set.seed(2025)to ensure reproducibility. Hint: useround()function to retain only the integer part of a number.
# Your code here
insurance <- read.csv("insurance.csv")
# b) Split data into training and test sets
set.seed(2025)
# Your code here
sample_index_2 <- sample(1:nrow(insurance), round(0.7*nrow(insurance)))
insurance_train <- insurance[sample_index_2, ]
insurance_test <- insurance[-sample_index_2, ]
insurance_train## age sex bmi children smoker region charges
## 909 63 male 39.800 3 no southwest 15170.069
## 460 40 female 33.000 3 no southeast 7682.670
## 932 39 female 32.500 1 no southwest 6238.298
## 279 59 male 31.790 2 no southeast 12928.791
## 187 26 female 29.920 2 no southeast 3981.977
## 1290 44 male 34.320 1 no southeast 7147.473
## 461 49 female 36.630 3 no southeast 10381.479
## 972 34 female 23.560 0 no northeast 4992.376
## 891 64 female 26.885 0 yes northwest 29330.983
## 571 31 female 29.100 0 no southwest 3761.292
## 907 27 male 32.585 3 no northeast 4846.920
## 159 30 male 35.530 0 yes southeast 36950.257
## 142 26 male 32.490 1 no northeast 3490.549
## 549 25 female 28.595 0 no northeast 3213.622
## 797 30 male 44.220 2 no southeast 4266.166
## 764 27 male 26.030 0 no northeast 3070.809
## 857 48 female 33.110 0 yes southeast 40974.165
## 630 44 female 38.950 0 yes northwest 42983.459
## 1112 38 male 38.390 3 yes southeast 41949.244
## 1219 46 female 34.600 1 yes southwest 41661.602
## 686 53 male 26.410 2 no northeast 11244.377
## 940 53 male 29.480 0 no southeast 9487.644
## 371 61 female 21.090 0 no northwest 13415.038
## 59 53 female 22.880 1 yes southeast 23244.790
## 1210 59 male 37.100 1 no southwest 12347.172
## 144 29 male 29.735 2 no northwest 18157.876
## 49 60 female 24.530 0 no southeast 12629.897
## 399 64 male 25.600 2 no southwest 14988.432
## 1074 54 female 28.880 2 no northeast 12096.651
## 626 29 female 26.030 0 no northwest 3736.465
## 185 44 male 30.690 2 no southeast 7731.427
## 1131 39 female 23.870 5 no southeast 8582.302
## 433 42 male 26.900 0 no southwest 5969.723
## 964 46 male 24.795 3 no northeast 9500.573
## 536 38 male 28.025 1 no northeast 6067.127
## 986 44 female 25.800 1 no southwest 7624.630
## 1332 23 female 33.400 0 no southwest 10795.937
## 539 46 female 28.050 1 no southeast 8233.097
## 1168 29 female 24.600 2 no southwest 4529.477
## 214 34 female 26.730 1 no southeast 5002.783
## 850 55 male 32.775 0 no northwest 10601.632
## 593 20 male 31.130 2 no southeast 2566.471
## 1177 52 female 24.130 1 yes northwest 23887.663
## 440 26 male 29.450 0 no northeast 2897.323
## 432 29 female 20.235 2 no northwest 4906.410
## 772 53 female 26.700 2 no southwest 11150.780
## 336 64 male 34.500 0 no southwest 13822.803
## 1014 48 male 32.300 1 no northwest 8765.249
## 363 19 female 21.700 0 yes southwest 13844.506
## 41 24 female 26.600 0 no northeast 3046.062
## 1206 35 male 17.860 1 no northwest 5116.500
## 599 43 male 32.600 2 no southwest 7441.501
## 1128 35 female 35.860 2 no southeast 5836.520
## 15 27 male 42.130 0 yes southeast 39611.758
## 524 38 female 37.730 0 no southeast 5397.617
## 725 50 female 27.075 1 no northeast 10106.134
## 387 58 female 39.050 0 no southeast 11856.412
## 1047 43 female 25.080 0 no northeast 7325.048
## 1178 40 female 27.400 1 no southwest 6496.886
## 1002 24 male 32.700 0 yes southwest 34472.841
## 873 42 male 24.860 0 no southeast 5966.887
## 743 53 male 34.105 0 yes northeast 43254.418
## 1073 21 male 31.255 0 no northwest 1909.527
## 1005 47 male 19.190 1 no northeast 8627.541
## 878 33 male 33.440 5 no southeast 6653.789
## 652 53 female 39.600 1 no southeast 10579.711
## 340 46 female 27.720 1 no southeast 8232.639
## 608 59 female 23.655 0 yes northwest 25678.778
## 583 39 male 45.430 2 no southeast 6356.271
## 37 62 female 32.965 3 no northwest 15612.193
## 228 58 female 41.910 0 no southeast 24227.337
## 468 56 female 33.820 2 no northwest 12643.378
## 846 60 female 32.450 0 yes southeast 45008.955
## 117 58 male 49.060 0 no southeast 11381.325
## 937 44 male 29.735 2 no northeast 32108.663
## 1287 28 female 17.290 0 no northeast 3732.625
## 1265 49 female 33.345 2 no northeast 10370.913
## 758 47 female 27.830 0 yes southeast 23065.421
## 586 33 female 28.270 1 no southeast 4779.602
## 1188 62 female 32.680 0 no northwest 13844.797
## 672 29 female 31.160 0 no northeast 3943.595
## 981 54 male 25.460 1 no northeast 25517.114
## 1194 48 female 36.575 0 no northwest 8671.191
## 218 27 male 23.100 0 no southeast 2483.736
## 1261 32 female 20.520 0 no northeast 4544.235
## 691 21 male 27.360 0 no northeast 2104.113
## 639 39 male 26.410 0 yes northeast 20149.323
## 791 39 female 41.800 0 no southeast 5662.225
## 148 51 female 37.730 1 no southeast 9877.608
## 405 31 male 20.400 0 no southwest 3260.199
## 110 63 male 35.090 0 yes southeast 47055.532
## 1234 58 male 23.300 0 no southwest 11345.519
## 10 60 female 25.840 0 no northwest 28923.137
## 911 22 male 28.310 1 no northwest 2639.043
## 18 23 male 23.845 0 no northeast 2395.172
## 1182 24 female 29.925 0 no northwest 2850.684
## 692 47 male 36.200 1 no southwest 8068.185
## 284 55 female 32.395 1 no northeast 11879.104
## 1201 37 male 24.320 2 no northwest 6198.752
## 504 19 male 30.250 0 yes southeast 32548.340
## 240 44 male 38.060 1 no southeast 7152.671
## 1030 37 female 17.290 2 no northeast 6877.980
## 1114 28 female 26.315 3 no northwest 5312.170
## 308 30 female 33.330 1 no southeast 4151.029
## 1049 25 female 22.515 1 no northwest 3594.171
## 774 19 female 28.880 0 yes northwest 17748.506
## 1295 58 male 25.175 0 no northeast 11931.125
## 121 44 male 37.100 2 no southwest 7740.337
## 314 49 male 35.860 0 no southeast 8124.408
## 295 25 male 26.800 3 no southwest 3906.127
## 1243 22 female 21.280 3 no northwest 4296.271
## 301 36 male 27.550 3 no northeast 6746.743
## 922 62 female 33.200 0 no southwest 13462.520
## 331 61 female 36.385 1 yes northeast 48517.563
## 429 21 female 16.815 1 no northeast 3167.456
## 500 62 female 39.200 0 no southwest 13470.860
## 1288 36 female 25.900 1 no southwest 5472.449
## 671 30 male 31.570 3 no southeast 4837.582
## 53 48 male 28.000 1 yes southwest 23568.272
## 644 23 female 34.960 3 no northwest 4466.621
## 959 43 male 34.960 1 yes northeast 41034.221
## 438 35 male 28.900 3 no southwest 5926.846
## 1029 54 male 31.600 0 no southwest 9850.432
## 955 34 male 27.835 1 yes northwest 20009.634
## 316 52 male 33.250 0 no northeast 9722.770
## 1052 64 male 26.410 0 no northeast 14394.558
## 163 54 male 39.600 1 no southwest 10450.552
## 1337 21 female 25.800 0 no southwest 2007.945
## 152 48 male 29.700 0 no southeast 7789.635
## 280 51 female 21.560 1 no southeast 9855.131
## 320 32 male 37.335 1 no northeast 4667.608
## 828 36 male 28.025 1 yes northeast 20773.628
## 427 38 female 27.265 1 no northeast 6555.070
## 1105 37 male 29.800 0 no southwest 20420.605
## 713 43 female 30.685 2 no northwest 8310.839
## 1032 55 female 35.200 0 yes southeast 44423.803
## 416 43 female 35.640 1 no southeast 7345.727
## 474 47 female 33.345 0 no northeast 20878.784
## 428 18 female 29.165 0 no northeast 7323.735
## 348 46 male 33.345 1 no northeast 8334.458
## 1154 35 female 35.815 1 no northwest 5630.458
## 872 26 female 29.480 1 no southeast 3392.365
## 799 58 female 33.100 0 no southwest 11848.141
## 559 35 female 34.105 3 yes northwest 39983.426
## 1267 55 female 30.500 0 no southwest 10704.470
## 680 49 female 23.180 2 no northwest 10156.783
## 643 61 male 33.915 0 no northeast 13143.865
## 184 44 female 26.410 0 no northwest 7419.478
## 656 52 female 25.300 2 yes southeast 24667.419
## 551 63 male 30.800 0 no southwest 13390.559
## 1171 18 male 27.360 1 yes northeast 17178.682
## 808 19 female 36.575 0 no northwest 2136.882
## 835 36 male 33.820 1 no northwest 5377.458
## 222 53 female 33.250 0 no northeast 10564.885
## 209 63 female 31.800 0 no southwest 13880.949
## 1169 32 male 35.200 2 no southwest 4670.640
## 1082 32 male 27.835 1 no northwest 4454.403
## 905 60 female 35.100 0 no southwest 12644.589
## 1274 35 male 27.610 1 no southeast 4747.053
## 285 52 female 31.200 0 no southwest 9625.920
## 510 57 female 28.700 0 no southwest 11455.280
## 1258 54 female 27.645 1 no northwest 11305.935
## 831 63 male 33.100 0 no southwest 13393.756
## 533 59 male 29.700 2 no southeast 12925.886
## 268 59 female 32.395 3 no northeast 14590.632
## 612 38 female 34.800 2 no southwest 6571.544
## 169 19 female 31.825 1 no northwest 2719.280
## 576 58 female 27.170 0 no northwest 12222.898
## 107 19 female 28.400 1 no southwest 2331.519
## 40 60 male 39.900 0 yes southwest 48173.361
## 967 51 male 24.795 2 yes northwest 23967.383
## 98 55 male 38.280 0 no southeast 10226.284
## 452 30 male 24.130 1 no northwest 4032.241
## 199 51 female 18.050 0 no northwest 9644.253
## 383 55 male 33.000 0 no southeast 20781.489
## 16 19 male 24.600 1 no southwest 1837.237
## 333 61 female 31.160 0 no northwest 13429.035
## 1013 61 female 33.330 4 no southeast 36580.282
## 629 58 male 38.000 0 no southwest 11365.952
## 90 55 female 26.980 0 no northwest 11082.577
## 1077 47 female 32.000 1 no southwest 8551.347
## 198 45 female 28.600 2 no southeast 8516.829
## 345 49 female 41.470 4 no southeast 10977.206
## 269 45 male 30.200 1 no southwest 7441.053
## 71 27 female 24.750 0 yes southeast 16577.780
## 1207 59 female 34.800 2 no southwest 36910.608
## 203 60 female 24.035 0 no northwest 13012.209
## 2 18 male 33.770 1 no southeast 1725.552
## 73 53 female 28.100 3 no southwest 11741.726
## 717 49 female 22.610 1 no northwest 9566.991
## 982 34 male 21.375 0 no northeast 4500.339
## 719 51 female 36.670 2 no northwest 10848.134
## 211 20 male 33.000 1 no southwest 1980.070
## 633 29 female 35.530 0 no southeast 3366.670
## 838 56 female 28.310 0 no northeast 11657.719
## 676 45 male 21.375 0 no northwest 7222.786
## 155 40 female 25.460 1 no northeast 7077.189
## 573 30 female 43.120 2 no southeast 4753.637
## 116 60 male 28.595 0 no northeast 30259.996
## 261 58 female 25.200 0 no southwest 11837.160
## 554 52 female 31.730 2 no northwest 11187.657
## 1250 32 male 33.630 1 yes northeast 37607.528
## 884 51 female 37.050 3 yes northeast 46255.113
## 274 50 male 27.455 1 no northeast 9617.662
## 1326 61 male 33.535 0 no northeast 13143.337
## 622 37 male 34.100 4 yes southwest 40182.246
## 859 25 female 32.230 1 no southeast 18218.161
## 135 20 female 28.785 0 no northeast 2457.211
## 1286 47 female 24.320 0 no northeast 8534.672
## 711 18 male 35.200 1 no southeast 1727.540
## 646 48 male 30.780 3 no northeast 10141.136
## 696 26 female 40.185 0 no northwest 3201.245
## 926 50 male 32.110 2 no northeast 25333.333
## 1306 24 female 27.720 0 no southeast 2464.619
## 1334 50 male 30.970 3 no northwest 10600.548
## 1315 30 female 23.655 3 yes northwest 18765.875
## 44 37 female 30.800 2 no southeast 6313.759
## 1065 29 female 25.600 4 no southwest 5708.867
## 707 51 female 38.060 0 yes southeast 44400.406
## 94 35 male 34.770 2 no northwest 5729.005
## 621 30 male 31.400 1 no southwest 3659.346
## 585 19 male 20.700 0 no southwest 1242.816
## 378 24 male 40.150 0 yes southeast 38126.247
## 970 39 female 34.320 5 no southeast 8596.828
## 1050 49 male 30.900 0 yes southwest 39727.614
## 417 52 male 34.100 0 no southeast 9140.951
## 1313 34 male 42.900 1 no southwest 4536.259
## 710 36 female 27.740 0 no northeast 5469.007
## 32 18 female 26.315 0 no northeast 2198.190
## 201 19 female 32.110 0 no northwest 2130.676
## 745 50 male 26.410 0 no northwest 8827.210
## 1011 48 female 22.800 0 no southwest 8269.044
## 512 27 male 33.660 0 no southeast 2498.414
## 99 56 male 19.950 0 yes northeast 22412.648
## 207 59 male 26.400 0 no southeast 11743.299
## 927 19 female 23.400 2 no southwest 2913.569
## 362 35 male 30.500 1 no southwest 4751.070
## 789 29 male 22.515 3 no northeast 5209.579
## 451 39 male 29.600 4 no southwest 7512.267
## 528 51 female 25.800 1 no southwest 9861.025
## 881 22 male 34.800 3 no southwest 3443.064
## 464 56 male 25.935 0 no northeast 11165.418
## 47 18 female 38.665 2 no northeast 3393.356
## 742 27 male 29.150 0 yes southeast 18246.496
## 434 60 female 30.500 0 no southwest 12638.195
## 721 51 female 40.660 0 no northeast 9875.680
## 447 60 male 29.640 0 no northeast 12731.000
## 1035 61 male 38.380 0 no northwest 12950.071
## 127 19 female 28.300 0 yes southwest 17081.080
## 403 64 female 32.965 0 no northwest 14692.669
## 171 63 male 41.470 0 no southeast 13405.390
## 834 58 male 34.390 0 no northwest 11743.934
## 277 19 male 20.615 2 no northwest 2803.698
## 1037 22 male 37.070 2 yes southeast 37484.449
## 939 18 male 26.180 2 no southeast 2304.002
## 217 53 female 26.600 0 no northwest 10355.641
## 147 46 male 30.495 3 yes northwest 40720.551
## 206 28 female 28.880 1 no northeast 4337.735
## 553 62 male 21.400 0 no southwest 12957.118
## 1104 58 male 36.080 0 no southeast 11363.283
## 119 49 female 27.170 0 no southeast 8601.329
## 560 19 male 35.530 0 no northwest 1646.430
## 1323 62 male 38.830 0 no southeast 12981.346
## 516 58 male 35.700 0 no southwest 11362.755
## 1057 48 female 28.900 0 no southwest 8277.523
## 930 41 male 34.210 1 no southeast 6289.755
## 869 61 male 23.655 0 no northeast 13129.603
## 520 31 male 30.875 0 no northeast 3857.759
## 231 42 female 36.195 1 no northwest 7443.643
## 1170 37 female 34.105 1 no northwest 6112.353
## 332 52 male 27.360 0 yes northwest 24393.622
## 712 50 female 23.540 2 no southeast 10107.221
## 476 61 male 28.310 1 yes northwest 28868.664
## 68 40 male 26.315 1 no northwest 6389.378
## 1055 27 female 21.470 0 no northwest 3353.470
## 166 47 male 28.215 4 no northeast 10407.086
## 1160 32 female 41.100 0 no southwest 3989.841
## 889 22 male 39.500 0 no southwest 1682.597
## 1241 52 male 41.800 2 yes southeast 47269.854
## 1004 48 male 29.600 0 no southwest 21232.182
## 531 57 male 42.130 1 yes southeast 48675.518
## 118 29 female 27.940 1 yes southeast 19107.780
## 983 31 male 25.900 3 yes southwest 19199.944
## 958 24 male 26.790 1 no northwest 12609.887
## 1179 23 female 34.865 0 no northeast 2899.489
## 265 53 female 38.060 3 no southeast 20462.998
## 1239 37 male 22.705 3 no northeast 6985.507
## 1000 36 female 26.885 0 no northwest 5267.818
## 866 40 male 29.900 2 no southwest 6600.361
## 55 40 female 28.690 3 no northwest 8059.679
## 854 53 female 23.750 2 no northeast 11729.680
## 771 61 male 36.100 3 no southwest 27941.288
## 368 42 female 24.985 2 no northwest 8017.061
## 965 52 male 36.765 2 no northwest 26467.097
## 233 19 female 17.800 0 no southwest 1727.785
## 563 27 male 30.500 0 no southwest 2494.022
## 1297 18 male 26.125 0 no northeast 1708.926
## 52 21 female 33.630 2 no northwest 3579.829
## 1257 51 female 36.385 3 no northwest 11436.738
## 84 48 female 41.230 4 no northwest 11033.662
## 20 30 male 35.300 0 yes southwest 36837.467
## 449 40 female 29.600 0 no southwest 5910.944
## 1202 46 male 40.375 2 no northwest 8733.229
## 694 24 male 23.655 0 no northwest 2352.968
## 1294 46 male 25.745 3 no northwest 9301.894
## 1173 56 female 41.910 0 no southeast 11093.623
## 304 28 female 33.000 2 no southeast 4349.462
## 76 57 male 34.010 0 no northwest 11356.661
## 1081 18 male 21.780 2 no southeast 11884.049
## 997 39 female 34.100 3 no southwest 7418.522
## 393 48 male 31.445 1 no northeast 8964.061
## 802 64 female 35.970 0 no southeast 14313.846
## 809 18 male 30.140 0 no southeast 1131.507
## 1 19 female 27.900 0 yes southwest 16884.924
## 1319 35 male 39.710 4 no northeast 19496.719
## 636 64 male 38.190 0 no northeast 14410.932
## 739 23 male 31.730 3 yes northeast 36189.102
## 595 41 male 40.260 0 no southeast 5709.164
## 321 34 male 25.270 1 no northwest 4894.753
## 768 42 female 29.000 1 no southwest 7050.642
## 506 37 male 30.875 3 no northwest 6796.863
## 193 25 male 25.740 0 no southeast 2137.654
## 1097 51 female 34.960 2 yes northeast 44641.197
## 140 22 female 36.000 0 no southwest 2166.732
## 590 38 female 30.690 1 no southeast 5976.831
## 1235 45 female 27.830 2 no southeast 8515.759
## 483 18 female 31.350 0 no southeast 1622.188
## 365 21 female 21.890 2 no southeast 3180.510
## 423 40 male 32.775 1 yes northeast 39125.332
## 260 19 male 31.920 0 yes northwest 33750.292
## 215 45 female 30.900 2 no southwest 8520.026
## 618 49 male 25.600 2 yes southwest 23306.547
## 1196 19 female 27.930 3 no northwest 18838.704
## 882 23 male 27.360 1 no northwest 2789.057
## 1189 43 female 25.270 1 yes northeast 21771.342
## 1325 31 male 25.935 1 no northwest 4239.893
## 437 22 male 31.730 0 no northeast 2254.797
## 1301 45 male 30.360 0 yes southeast 62592.873
## 1111 54 female 32.300 1 no northeast 11512.405
## 741 45 male 24.035 2 no northeast 8604.484
## 1021 51 male 37.000 0 no southwest 8798.593
## 190 29 female 32.110 2 no northwest 4922.916
## 315 27 female 31.400 0 yes southwest 34838.873
## 1007 28 male 29.260 2 no northeast 4438.263
## 499 44 female 23.980 2 no southeast 8211.100
## 454 20 male 29.735 0 no northwest 1769.532
## 153 32 female 37.145 3 no northeast 6334.344
## 1305 42 male 24.605 2 yes northeast 21259.378
## 25 37 male 28.025 2 no northwest 6203.902
## 1329 23 female 24.225 2 no northeast 22395.744
## 254 27 male 30.300 3 no southwest 4260.744
## 623 49 female 21.300 1 no southwest 9182.170
## 136 22 female 28.050 0 no southeast 2155.682
## 446 45 female 33.100 0 no southwest 7345.084
## 960 48 male 36.670 1 no northwest 28468.919
## 45 38 male 37.050 1 no northeast 6079.672
## 984 27 female 30.590 1 no northeast 16796.412
## 278 22 female 24.300 0 no southwest 2150.469
## 352 50 female 25.600 0 no southwest 8932.084
## 1056 55 male 27.645 0 no northwest 10594.502
## 1316 18 male 28.310 1 no northeast 11272.331
## 490 53 male 31.160 1 no northwest 10461.979
## 34 63 male 28.310 0 no northwest 13770.098
## 603 56 female 25.300 0 no southwest 11070.535
## 72 31 male 28.500 5 no northeast 6799.458
## 1268 24 male 31.065 0 yes northeast 34254.053
## 722 53 male 36.600 3 no southwest 11264.541
## 179 46 female 28.900 2 no southwest 8823.279
## 735 59 female 32.100 3 no southwest 14007.222
## 398 21 male 31.020 0 no southeast 16586.498
## 853 46 female 35.530 0 yes northeast 42111.665
## 1156 36 female 22.135 3 no northeast 7228.216
## 322 26 female 29.640 4 no northeast 24671.663
## 491 19 female 32.900 0 no southwest 1748.774
## 346 34 female 29.260 3 no southeast 6184.299
## 122 18 male 23.750 0 no northeast 1705.624
## 463 62 female 38.095 2 no northeast 15230.324
## 597 42 female 29.480 2 no southeast 7640.309
## 973 22 female 20.235 0 no northwest 2527.819
## 566 19 female 30.495 0 no northwest 2128.431
## 879 41 male 28.800 1 no southwest 6282.235
## 1242 64 male 36.960 2 yes southeast 49577.662
## 1001 30 male 22.990 2 yes northwest 17361.766
## 401 51 female 20.600 0 no southwest 9264.797
## 298 47 male 25.410 1 yes southeast 21978.677
## 175 24 female 33.345 0 no northwest 2855.438
## 1062 57 male 27.940 1 no southeast 11554.224
## 650 58 female 32.965 0 no northeast 12430.953
## 324 57 male 40.945 0 no northeast 11566.301
## 679 56 male 36.100 3 no southwest 12363.547
## 614 34 female 19.000 3 no northeast 6753.038
## 949 42 male 31.255 0 no northwest 6358.776
## 688 40 male 41.690 0 no southeast 5438.749
## 310 41 female 33.060 2 no northwest 7749.156
## 648 40 female 23.370 3 no northeast 8252.284
## 592 47 male 19.570 1 no northwest 8428.069
## 1076 32 female 29.590 1 no southeast 4562.842
## 785 31 female 29.260 1 no southeast 4350.514
## 384 35 female 43.340 2 no southeast 5846.918
## 226 55 male 33.880 3 no southeast 11987.168
## 1336 18 female 36.850 0 no southeast 1629.833
## 698 41 male 35.750 1 yes southeast 40273.645
## 361 48 female 32.300 2 no northeast 10043.249
## 167 20 female 37.000 5 no southwest 4830.630
## 404 49 male 32.300 3 no northwest 10269.460
## 1091 47 male 36.190 0 yes southeast 41676.081
## 112 55 female 29.700 2 no southwest 11881.358
## 439 52 female 46.750 5 no southeast 12592.534
## 234 59 male 27.500 1 no southwest 12333.828
## 395 46 female 32.300 2 no northeast 9411.005
## 431 19 male 33.100 0 no southwest 23082.955
## 784 50 female 27.600 1 yes southwest 24520.264
## 1150 42 male 34.100 0 no southwest 5979.731
## 489 44 female 38.060 0 yes southeast 48885.136
## 1222 40 male 24.970 2 no southeast 6593.508
## 264 19 male 36.955 0 yes northwest 36219.405
## 411 19 male 17.480 0 no northwest 1621.340
## 359 23 male 41.910 0 no southeast 1837.282
## 83 22 male 37.620 1 yes southeast 37165.164
## 232 59 female 27.830 3 no southeast 14001.287
## 418 36 female 22.600 2 yes southwest 18608.262
## 824 44 female 29.810 2 no southeast 8219.204
## 916 24 female 33.990 0 no southeast 2473.334
## 929 62 female 39.160 0 no southeast 13470.804
## 640 56 male 33.660 4 no southeast 12949.155
## 137 19 male 34.100 0 no southwest 1261.442
## 350 19 male 27.835 0 no northwest 1635.734
## 105 34 female 27.500 1 no southwest 5003.853
## 337 60 male 25.740 0 no southeast 12142.579
## 444 59 female 36.520 1 no southeast 28287.898
## 1096 18 female 31.350 4 no northeast 4561.189
## 307 28 female 27.500 2 no southwest 20177.671
## 561 46 female 19.950 2 no northwest 9193.838
## 194 56 female 26.600 1 no northwest 12044.342
## 796 27 male 28.500 0 yes northwest 18310.742
## 1214 52 female 33.300 2 no southwest 10806.839
## 1262 28 male 37.100 1 no southwest 3277.161
## 875 44 male 21.850 3 no northeast 8891.139
## 239 19 male 29.070 0 yes northwest 17352.680
## 195 18 male 34.430 0 no southeast 1137.470
## 210 40 male 41.230 1 no northeast 6610.110
## 781 30 male 24.400 3 yes southwest 18259.216
## 1314 19 female 34.700 2 yes southwest 36397.576
## 841 21 male 31.100 0 no southwest 1526.312
## 309 58 male 34.865 0 no northeast 11944.594
## 102 30 male 25.460 0 no northeast 3645.089
## 1066 42 female 25.300 1 no southwest 7045.499
## 748 19 male 21.755 0 no northwest 1627.282
## 30 31 male 36.300 2 yes southwest 38711.000
## 999 33 female 36.290 3 no northeast 6551.750
## 408 47 female 23.600 1 no southwest 8539.671
## 168 32 female 33.155 3 no northwest 6128.797
## 1126 63 female 25.080 0 no northwest 14254.608
## 1093 23 male 32.700 3 no southwest 3591.480
## 54 36 male 34.430 0 yes southeast 37742.576
## 699 56 male 33.725 0 no northwest 10976.246
## 174 35 female 34.800 1 no southwest 5246.047
## 497 31 female 23.600 2 no southwest 4931.647
## 413 26 female 17.195 2 yes northeast 14455.644
## 364 21 female 26.400 1 no southwest 2597.779
## 562 54 female 32.680 0 no northeast 10923.933
## 1162 34 male 42.130 2 no southeast 5124.189
## 1312 33 female 26.695 0 no northwest 4571.413
## 1103 29 male 38.940 1 no southeast 3471.410
## 1087 55 male 28.975 0 no northeast 10796.350
## 126 26 female 28.785 0 no northeast 3385.399
## 1283 18 female 21.660 0 yes northeast 14283.459
## 1245 18 male 33.330 0 no southeast 1135.941
## 946 56 female 35.800 1 no southwest 11674.130
## 830 39 male 21.850 1 no northwest 6117.494
## 602 51 male 31.635 0 no northwest 9174.136
## 991 26 female 19.800 1 no southwest 3378.910
## 550 43 female 46.200 0 yes southeast 45863.205
## 777 40 male 32.300 2 no northwest 6986.697
## 445 56 male 26.695 1 yes northwest 26109.329
## 259 51 male 24.415 4 no northwest 11520.100
## 813 54 male 21.010 2 no southeast 11013.712
## 436 60 male 33.110 3 no southeast 13919.823
## 1136 50 female 28.120 3 no northwest 11085.587
## 977 48 male 40.150 0 no southeast 7804.160
## 513 51 male 22.420 0 no northeast 9361.327
## 564 50 male 44.770 1 no southeast 9058.730
## 914 44 female 27.500 1 no southwest 7626.993
## 893 54 male 24.035 0 no northeast 10422.917
## 778 45 male 39.805 0 no northeast 7448.404
## 38 26 male 20.800 0 no southwest 2302.300
## 1149 55 male 21.500 1 no southwest 10791.960
## 123 20 female 28.975 0 no northwest 2257.475
## 1317 19 female 20.600 0 no southwest 1731.677
## 1024 18 male 23.320 1 no southeast 1711.027
## 534 37 male 36.190 0 no southeast 19214.706
## 526 18 female 33.880 0 no southeast 11482.635
## 934 45 female 35.300 0 no southwest 7348.142
## 804 18 female 42.240 0 yes southeast 38792.686
## 415 19 female 35.150 0 no northwest 2134.901
## 27 63 female 23.085 0 no northeast 14451.835
## 108 26 male 30.875 2 no northwest 3877.304
## 1051 44 female 36.955 1 no northwest 8023.135
## 792 19 male 27.600 0 no southwest 1252.407
## 776 51 male 33.330 3 no southeast 10560.492
## 1254 40 female 29.300 4 no southwest 15828.822
## 1240 25 female 42.130 1 no southeast 3238.436
## 1209 37 female 25.555 1 yes northeast 20296.863
## 1320 39 female 26.315 2 no northwest 7201.701
## 375 20 male 33.330 0 no southeast 1391.529
## 577 22 male 26.840 0 no southeast 1665.000
## 865 51 male 25.400 0 no southwest 8782.469
## 816 20 female 31.460 0 no southeast 1877.929
## 1121 23 female 31.400 0 yes southwest 34166.273
## 730 41 female 36.080 1 no southeast 6781.354
## 903 26 male 27.265 3 no northeast 4661.286
## 568 41 male 30.590 2 no northwest 7256.723
## 723 62 male 37.400 0 no southwest 12979.358
## 1246 28 male 24.300 5 no southwest 5615.369
## 634 40 male 22.705 2 no northeast 7173.360
## 106 20 male 28.025 1 yes northwest 17560.380
## 895 62 male 32.110 0 no northeast 13555.005
## 1048 22 male 52.580 1 yes southeast 44501.398
## 376 23 female 28.310 0 yes northwest 18033.968
## 19 56 male 40.300 0 no southwest 10602.385
## 703 53 male 41.470 0 no southeast 9504.310
## 567 38 female 40.565 1 no northwest 6373.557
## 230 47 male 25.460 2 no northeast 9225.256
## 961 19 female 39.615 1 no northwest 2730.108
## 848 23 male 50.380 1 no southeast 2438.055
## 760 18 male 38.170 0 yes southeast 36307.798
## 849 27 female 24.100 0 no southwest 2974.126
## 548 54 female 46.700 2 no southwest 11538.421
## 342 62 male 30.020 0 no northwest 13352.100
## 478 25 male 35.625 0 no northwest 2534.394
## 1152 58 female 36.480 0 no northwest 12235.839
## 749 47 female 36.000 1 no southwest 8556.907
## 1071 37 male 37.070 1 yes southeast 39871.704
## 357 46 male 43.890 3 no southeast 8944.115
## 420 63 female 26.980 0 yes northwest 28950.469
## 1310 41 male 32.200 2 no southwest 6875.961
## 821 45 male 33.700 1 no southwest 7445.918
## 1064 36 male 28.595 3 no northwest 6548.195
## 638 35 female 38.095 2 no northeast 24915.046
## 953 30 female 28.405 1 no northwest 4527.183
## 716 60 male 28.900 0 no southwest 12146.971
## 299 31 male 34.390 3 yes northwest 38746.355
## 1227 38 male 16.815 2 no northeast 6640.545
## 1085 62 female 30.495 2 no northwest 15019.760
## 673 36 male 29.700 0 no southeast 4399.731
## 492 61 female 25.080 0 no southeast 24513.091
## 871 50 male 36.200 0 no southwest 8457.818
## 453 24 male 23.400 0 no southwest 1969.614
## 180 41 female 33.155 3 no northeast 8538.288
## 541 34 female 38.000 3 no southwest 6196.448
## 1255 34 female 27.720 0 no southeast 4415.159
## 546 49 male 25.840 2 yes northwest 23807.241
## 1078 21 male 26.030 0 no northeast 2102.265
## 814 28 male 22.515 2 no northeast 4428.888
## 594 21 female 21.850 1 yes northeast 15359.104
## 556 28 male 23.800 2 no southwest 3847.674
## 1161 43 female 34.580 1 no northwest 7727.253
## 1042 18 male 23.085 0 no northeast 1704.700
## 862 38 female 28.000 3 no southwest 7151.092
## 508 21 male 23.750 2 no northwest 3077.095
## 535 64 male 40.480 0 no southeast 13831.115
## 1006 29 male 31.730 2 no northwest 4433.388
## 886 32 male 28.930 1 yes southeast 19719.695
## 842 59 male 24.700 0 no northeast 12323.936
## 385 44 male 22.135 2 no northeast 8302.536
## 693 20 male 32.395 1 no northwest 2362.229
## 88 56 female 27.200 0 no southwest 11073.176
## 547 28 male 35.435 0 no northeast 3268.847
## 1015 38 female 27.600 0 no southwest 5383.536
## 78 21 male 35.530 0 no southeast 1532.470
## 966 35 male 27.100 1 no southwest 4746.344
## 1020 21 female 32.680 2 no northwest 26018.951
## 255 50 male 31.825 0 yes northeast 41097.162
## 880 37 female 29.500 2 no southwest 6311.952
## 165 37 male 29.640 0 no northwest 5028.147
## 1100 25 female 33.990 1 no southeast 3227.121
## 775 41 male 34.200 2 no northwest 7261.741
## 246 54 male 30.020 0 no northwest 24476.479
## 795 39 female 31.920 2 no northwest 7209.492
## 987 43 male 30.115 3 no northwest 8410.047
## 822 26 male 17.670 0 no northwest 2680.949
## 87 57 female 31.160 0 yes northwest 43578.939
## 1174 38 male 29.260 2 no northwest 6457.843
## 1036 54 female 23.000 3 no southwest 12094.478
## 601 18 female 39.160 0 no southeast 1633.044
## 1284 18 male 30.030 1 no southeast 1720.354
## 1142 41 female 32.600 3 no southwest 7954.517
## 572 18 female 37.290 1 no southeast 2219.445
## 139 54 female 31.900 3 no southeast 27322.734
## 343 60 female 27.550 0 no northeast 13217.094
## 569 49 female 31.900 5 no southwest 11552.904
## 1164 18 female 28.215 0 no northeast 2200.831
## 303 56 female 37.510 2 no southeast 12265.507
## 459 56 male 39.600 0 no southwest 10601.412
## 766 57 female 31.825 0 no northwest 11842.624
## 704 34 female 26.410 1 no northwest 5385.338
## 954 44 male 30.200 2 yes southwest 38998.546
## 1264 43 female 29.900 1 no southwest 7337.748
## 400 18 female 38.170 0 no southeast 1631.668
## 1092 55 female 29.830 0 no northeast 11286.539
## 355 18 female 38.280 0 no southeast 14133.038
## 473 19 female 29.800 0 no southwest 1744.465
## 1233 54 female 24.605 3 no northwest 12479.709
## 70 28 male 23.980 3 yes southeast 17663.144
## 759 30 male 37.430 3 no northeast 5428.728
## 839 35 female 23.465 2 no northeast 6402.291
## 1195 31 female 21.755 0 no northwest 4134.082
## 330 52 male 36.700 0 no southwest 9144.565
## 942 50 female 46.090 1 no southeast 9549.565
## 325 29 male 27.200 0 no southwest 2866.091
## 1094 22 female 30.400 0 yes northwest 33907.548
## 867 18 male 37.290 0 no southeast 1141.445
## 1208 36 male 33.400 2 yes southwest 38415.474
## 1259 55 male 37.715 3 no northwest 30063.581
## 158 18 male 25.175 0 yes northeast 15518.180
## 925 43 male 23.200 0 no southwest 6250.435
## 120 37 female 23.370 2 no northwest 6686.431
## 479 21 male 36.850 0 no southeast 1534.304
## 661 37 male 46.530 3 no southeast 6435.624
## 1157 19 male 44.880 0 yes southeast 39722.746
## 815 36 male 34.430 2 no southeast 5584.306
## 756 31 male 27.645 2 no northeast 5031.270
## 276 47 female 26.600 2 no northeast 9715.841
## 845 53 male 30.495 0 no northeast 10072.055
## 1238 58 female 28.215 0 no northwest 12224.351
## 1003 24 male 25.800 0 no southwest 1972.950
## 134 19 male 25.555 0 no northwest 1632.564
## 481 63 male 41.325 3 no northwest 15555.189
## 651 49 female 42.680 2 no southeast 9800.888
## 353 30 female 27.700 0 no southwest 3554.203
## 832 36 female 25.840 0 no northwest 5266.366
## 1225 41 male 23.940 1 no northeast 6858.480
## 100 38 male 19.300 0 yes southwest 15820.699
## 1019 54 female 35.815 3 no northwest 12495.291
## 370 18 male 30.400 3 no northeast 3481.868
## 558 34 male 34.210 0 no southeast 3935.180
## 1034 18 male 21.565 0 yes northeast 13747.872
## 1291 38 female 19.950 2 no northeast 7133.903
## 145 30 male 28.690 3 yes northwest 20745.989
## 827 56 male 31.790 2 yes southeast 43813.866
## 852 61 male 32.300 2 no northwest 14119.620
## 915 33 male 24.605 2 no northwest 5257.508
## 1321 31 male 31.065 3 no northwest 5425.023
## 1270 45 male 27.500 3 no southwest 8615.300
## 1127 55 male 29.900 0 no southwest 10214.636
## 607 27 female 25.175 0 no northeast 3558.620
## 537 33 female 38.900 3 no southwest 5972.378
## 951 57 male 18.335 0 no northeast 11534.873
## 769 64 female 39.700 0 no southwest 14319.031
## 146 29 female 38.830 3 no southeast 5138.257
## 555 25 female 41.325 0 no northeast 17878.901
## 580 25 female 23.465 0 no northeast 3206.491
## 655 59 female 35.200 0 no southeast 12244.531
## 860 57 male 28.100 0 no southwest 10965.446
## 826 64 female 31.825 2 no northeast 16069.085
## 1009 25 male 24.985 2 no northeast 23241.475
## 667 49 male 28.700 1 no southwest 8703.456
## 1298 28 female 26.510 2 no southeast 4340.441
## 1086 39 female 18.300 5 yes southwest 19023.260
## 1232 20 female 21.800 0 yes southwest 20167.336
## 412 44 female 20.235 1 yes northeast 19594.810
## 181 58 male 28.595 0 no northwest 11735.879
## 773 44 female 36.480 0 no northeast 12797.210
## 596 46 female 33.725 1 no northeast 8823.986
## 13 23 male 34.400 0 no southwest 1826.843
## 379 64 female 30.115 3 no northwest 16455.708
## 851 37 female 30.780 0 yes northeast 37270.151
## 289 59 female 36.765 1 yes northeast 47896.791
## 287 46 female 48.070 2 no northeast 9432.925
## 899 18 female 40.260 0 no southeast 1634.573
## 1025 47 female 45.320 1 no southeast 8569.862
## 220 24 female 23.210 0 no southeast 25081.768
## 1147 60 male 32.800 0 yes southwest 52590.829
## 1090 56 male 22.100 0 no southwest 10577.087
## 1153 43 female 32.560 3 yes southeast 40941.285
## 962 29 female 25.900 0 no southwest 3353.284
## 300 48 female 28.880 1 no northwest 9249.495
## 746 50 female 30.115 1 no northwest 9910.360
## 894 47 male 38.940 2 yes southeast 44202.654
## 818 23 male 37.100 3 no southwest 3597.596
## 367 56 female 32.300 3 no northeast 13430.265
## 258 38 female 40.150 0 no southeast 5400.980
## 305 57 female 38.000 2 no southwest 12646.207
## 1289 20 male 39.400 2 yes southwest 38344.566
## 77 29 female 29.590 1 no southeast 3947.413
## 975 26 male 35.420 0 no southeast 2322.622
## 1252 19 male 19.800 0 no southwest 1241.565
## 509 24 female 25.270 0 no northeast 3044.213
## 613 18 female 33.155 0 no northeast 2207.697
## 632 24 male 29.300 0 no southwest 1977.815
## 1318 18 male 53.130 0 no southeast 1163.463
## 762 23 male 35.200 1 no southwest 2416.955
## 786 35 female 27.700 3 no southwest 6414.178
## 678 60 male 31.350 3 yes northwest 46130.526
## 1256 42 female 37.900 0 no southwest 6474.013
## 382 55 male 30.685 0 yes northeast 42303.692
## 731 35 male 24.420 3 yes southeast 19361.999
## 1129 34 male 32.800 1 no southwest 14358.364
## 164 32 female 29.800 2 no southwest 5152.134
## 1143 52 female 24.860 0 no southeast 27117.994
## 1145 50 male 32.300 2 no southwest 9630.397
## 1327 42 female 32.870 0 no northeast 7050.021
## 817 24 female 24.225 0 no northwest 2842.761
## 615 20 female 33.000 0 no southeast 1880.070
## 494 61 male 43.400 0 no southwest 12574.049
## 11 25 male 26.220 0 no northeast 2721.321
## 754 58 female 22.770 0 no southeast 11833.782
## 496 20 male 27.930 0 no northeast 1967.023
## 587 21 male 20.235 3 no northeast 3861.210
## 783 51 male 35.970 1 no southeast 9386.161
## 224 19 male 34.800 0 yes southwest 34779.615
## 1083 38 male 19.950 1 no northwest 5855.903
## 669 62 male 32.015 0 yes northeast 45710.208
## 391 48 male 35.625 4 no northeast 10736.871
## 1115 23 male 24.510 0 no northeast 2396.096
## 480 23 male 32.560 0 no southeast 1824.285
## 890 57 male 33.630 1 no northwest 11945.133
## 825 60 male 24.320 0 no northwest 12523.605
## 31 22 male 35.600 0 yes southwest 35585.576
## 238 31 male 38.390 2 no southeast 4463.205
## 1039 22 male 28.880 0 no northeast 2250.835
## 1277 22 female 30.400 0 no northeast 2741.948
## 729 18 female 40.280 0 no northeast 2217.601
## 372 57 female 22.230 0 no northeast 12029.287
## 668 40 female 32.775 2 yes northwest 40003.332
## 645 43 male 35.310 2 no southeast 18806.145
## 347 33 male 35.750 2 no southeast 4889.999
## 1199 40 male 29.355 1 no northwest 6393.603
## 617 56 female 28.595 0 no northeast 11658.115
## 1296 20 male 22.000 1 no southwest 1964.780
## 770 38 female 19.475 2 no northwest 6933.242
## 1146 52 male 32.775 3 no northwest 11289.109
## 1063 59 male 41.140 1 yes southeast 48970.248
## 3 28 male 33.000 3 no southeast 4449.462
## 189 41 female 32.200 1 no southwest 6775.961
## 1155 48 female 27.930 4 no northwest 11015.175
## 708 49 male 28.690 3 no northwest 10264.442
## 1192 41 female 21.755 1 no northeast 13725.472
## 1185 23 female 28.490 1 yes southeast 18328.238
## 458 57 female 30.495 0 no northwest 11840.775
## 1213 18 male 21.470 0 no northeast 1702.455
## 519 35 female 31.000 1 no southwest 5240.765
## 968 44 male 25.365 1 no northwest 7518.025
## 1022 22 female 31.020 3 yes southeast 35595.590
## 131 59 female 26.505 0 no northeast 12815.445
## 161 42 female 26.600 0 yes northwest 21348.706
## 249 19 male 20.900 1 no southwest 1832.094
## 186 36 male 41.895 3 yes northeast 43753.337
## 900 19 female 22.515 0 no northwest 2117.339
## 578 31 female 38.095 1 yes northeast 58571.074
## 36 19 male 20.425 0 no northwest 1625.434
## 349 36 female 29.920 1 no southeast 5478.037
## 957 54 male 30.800 1 yes southeast 41999.520
## 624 18 male 33.535 0 yes northeast 34617.841
## 1141 50 male 37.070 1 no southeast 9048.027
## 1276 57 male 23.700 0 no southwest 10959.330
## 475 54 male 25.100 3 yes southwest 25382.297
## 1338 61 female 29.070 0 yes northwest 29141.360
## 306 29 male 33.345 2 no northwest 19442.354
## 111 54 male 33.630 1 no northwest 10825.254
## 421 64 male 33.880 0 yes southeast 46889.261
## 753 64 male 37.905 0 no northwest 14210.536
## 1304 43 male 27.800 0 yes southwest 37829.724
## 467 60 female 28.700 1 no southwest 13224.693
## 225 42 male 24.640 0 yes southeast 19515.542
## 662 57 female 23.980 1 no southeast 22192.437
## 1028 23 male 18.715 0 no northwest 21595.382
## 369 44 male 32.015 2 no northwest 8116.269
## 485 48 male 34.300 3 no southwest 9563.029
## 482 49 male 37.510 2 no southeast 9304.702
## 1075 60 female 18.335 0 no northeast 13204.286
## 1226 33 female 39.820 1 no southeast 4795.657
## 338 62 male 27.550 1 no northwest 13937.666
## 1303 25 female 20.800 1 no southwest 3208.787
## 689 47 female 24.100 1 no southwest 26236.580
## 293 25 male 45.540 2 yes southeast 42112.236
## 138 22 male 25.175 0 no northwest 2045.685
## 323 34 male 30.800 0 yes southwest 35491.640
## 923 38 male 31.000 1 no southwest 5488.262
## 589 61 female 35.910 0 no northeast 13635.638
## 788 21 male 36.860 0 no northwest 1917.318
## 978 26 male 29.150 1 no southeast 2902.907
## 979 45 female 39.995 3 no northeast 9704.668
## 628 33 male 42.460 1 no southeast 11326.715
## 8 37 female 27.740 3 no northwest 7281.506
## 1330 52 male 38.600 2 no southwest 10325.206
## 1026 21 female 34.600 0 no southwest 2020.177
## 518 45 male 30.495 2 no northwest 8413.463
## 216 41 female 37.100 2 no southwest 7371.772
## 91 21 female 39.490 0 no southeast 2026.974
## 837 36 male 31.500 0 no southwest 4402.233
## 60 34 female 37.335 2 no northwest 5989.524
## 237 18 female 26.730 0 no southeast 1615.767
## 913 59 female 26.695 3 no northwest 14382.709
## 1120 30 female 19.950 3 no northwest 5693.431
## 1138 26 female 22.230 0 no northwest 3176.288
## 297 19 male 27.700 0 yes southwest 16297.846
## 823 18 female 31.130 0 no southeast 1621.883
## 641 33 male 42.400 5 no southwest 6666.243
## 1221 30 female 21.945 1 no northeast 4718.204
## 1263 41 female 28.050 1 no southeast 6770.193
## 767 47 male 32.300 1 no southwest 8062.764
## 177 38 male 27.835 2 no northwest 6455.863
## 887 57 male 28.975 0 yes northeast 27218.437
## 425 48 male 30.200 2 no southwest 8968.330
## 993 50 female 31.600 2 no southwest 10118.424
## 918 45 male 22.895 0 yes northeast 35069.375
## 1135 28 male 33.820 0 no northwest 19673.336
## 263 52 male 24.320 3 yes northeast 24869.837
## 738 26 male 23.700 2 no southwest 3484.331
## 744 31 female 26.620 0 no southeast 3757.845
## 976 29 male 22.895 0 yes northeast 16138.762
## 95 64 female 31.300 2 yes southwest 47291.055
## 819 47 female 26.125 1 yes northeast 23401.306
## 861 37 female 47.600 2 yes southwest 46113.511
## 266 46 male 42.350 3 yes southeast 46151.124
## 1107 49 female 29.925 0 no northwest 8988.159
## 1215 27 female 31.255 1 no northwest 3956.071
## 1197 19 female 30.020 0 yes northwest 33307.551
## 1099 52 female 30.875 0 no northeast 23045.566
## 1322 62 male 26.695 0 yes northeast 28101.333
## 282 54 male 40.565 3 yes northeast 48549.178
## 1302 62 male 30.875 3 yes northwest 46718.163
## 1080 63 male 33.660 3 no southeast 15161.534
## 1069 63 male 21.660 1 no northwest 14349.854
## 992 38 female 27.835 2 no northeast 7144.863
## 1191 31 female 32.775 2 no northwest 5327.400
## 448 56 female 25.650 0 no northwest 11454.022
## 660 57 female 28.785 4 no northeast 14394.398
## 995 27 female 20.045 3 yes northwest 16420.495
## 1279 39 male 29.925 1 yes northeast 22462.044
## 674 41 female 31.020 0 no southeast 6185.321
## 319 44 female 27.645 0 no northwest 7421.195
## 1184 48 female 27.360 1 no northeast 9447.382
## 192 36 female 26.200 0 no southwest 4883.866
## 941 18 male 23.210 0 no southeast 1121.874
## 579 52 male 30.200 1 no southwest 9724.530
## 917 43 female 26.885 0 yes northwest 21774.322
## 457 55 female 30.140 2 no southeast 11881.970
## 515 39 male 28.300 1 yes southwest 21082.160
## 312 19 female 24.700 0 no southwest 1737.376
## 883 21 female 22.135 0 no northeast 2585.851
## 1010 51 male 27.740 1 no northeast 9957.722
## 525 42 male 26.070 1 yes southeast 38245.593
## 426 45 male 24.310 5 no southeast 9788.866
## 1044 28 female 25.800 0 no southwest 3161.454
## 1324 42 female 40.370 2 yes southeast 43896.376
## 406 52 female 38.380 2 no northeast 11396.900
## 727 41 male 28.405 1 no northwest 6664.686
## 1260 52 female 23.180 0 no northeast 10197.772
## 272 50 male 34.200 2 yes southwest 42856.838
## 162 18 female 36.850 0 yes southeast 36149.484
## 1190 23 female 28.000 0 no southwest 13126.677
## 912 18 male 31.730 0 yes northeast 33732.687
## 250 29 male 28.975 1 no northeast 4040.558
## 1101 33 female 19.095 2 yes northeast 16776.304
## 229 41 female 31.635 1 no northeast 7358.176
## 495 21 male 25.700 4 yes southwest 17942.106
## 1176 22 female 27.100 0 no southwest 2154.361
## 682 19 male 20.300 0 no southwest 1242.260
## 971 50 female 28.160 3 no southeast 10702.642
## 1181 42 female 41.325 1 no northeast 7650.774
## 178 54 male 29.200 1 no southwest 10436.096
## 1175 29 male 32.110 2 no northwest 4433.916
## 619 19 female 33.110 0 yes southeast 34439.856
## 1198 41 male 33.550 0 no southeast 5699.837
## 360 18 female 20.790 0 no southeast 1607.510
## 472 18 female 30.115 0 no northeast 2203.472
## 58 18 male 31.680 2 yes southeast 34303.167
## 484 51 female 39.500 1 no southwest 9880.068
## 67 61 female 39.100 2 no southwest 14235.072
## 82 45 female 38.285 0 no northeast 7935.291
## 129 32 female 17.765 2 yes northwest 32734.186
## 780 53 male 28.880 0 no northwest 9869.810
## 820 33 female 35.530 0 yes northwest 55135.402
## 63 64 male 24.700 1 no northwest 30166.618
## 736 49 female 34.770 1 no northwest 9583.893
## 582 19 male 30.590 0 no northwest 1639.563
## 511 56 male 32.110 1 no northeast 11763.001
## 1248 33 male 29.400 4 no southwest 6059.173
## 1095 50 female 33.700 4 no southwest 11299.343
## 1132 27 male 45.900 2 no southwest 3693.428
## 1133 57 male 40.280 0 no northeast 20709.020
## 718 60 male 24.320 1 no northwest 13112.605
## 86 45 male 22.895 2 yes northwest 21098.554
## 649 18 male 28.500 0 no northeast 1712.227
## 963 63 female 35.200 1 no southeast 14474.675
## 1292 19 male 34.900 0 yes southwest 34828.654
## 441 31 female 32.680 1 no northwest 4738.268
## 130 38 male 34.700 2 no southwest 6082.405
## 794 53 male 20.900 0 yes southeast 21195.818
## 245 63 female 27.740 0 yes northeast 29523.166
## 1166 35 female 26.125 0 no northeast 5227.989
## 700 23 female 39.270 2 no southeast 3500.612
## 874 43 male 30.100 1 no southwest 6849.026
## 885 25 male 26.695 4 no northwest 4877.981
## 1172 43 female 26.700 2 yes southwest 22478.600
## 1017 19 female 24.605 1 no northwest 2709.244
## 351 57 female 23.180 0 no northwest 11830.607
## 901 49 male 22.515 0 no northeast 8688.859
## 374 26 male 32.900 2 yes southwest 36085.219
## 811 46 female 30.800 3 no southwest 9414.920
## 414 25 male 23.900 5 no southwest 5080.096
## 1299 33 male 27.455 2 no northwest 5261.469
## 26 59 female 27.720 3 no southeast 14001.134
## 734 48 female 27.265 1 no northeast 9447.250
## 574 62 female 36.860 1 no northeast 31620.001
## 334 56 female 28.785 0 no northeast 11658.379
## 1216 18 male 39.140 0 no northeast 12890.058
## 675 44 female 43.890 2 yes southeast 46200.985
## 1054 47 male 29.800 3 yes southwest 25309.489
## 150 19 male 28.400 1 no southwest 1842.519
## 833 28 female 23.845 2 no northwest 4719.737
## 182 18 female 38.280 0 no southeast 1631.821
## 294 22 female 28.820 0 no southeast 2156.752
## 487 54 female 21.470 3 no northwest 12475.351
## 402 47 male 47.520 1 no southeast 8083.920
## 1023 47 male 36.080 1 yes southeast 42211.138
## 341 24 female 27.600 0 no southwest 18955.220
## 92 53 female 24.795 1 no northwest 10942.132
## 1108 50 female 26.220 2 no northwest 10493.946
## 23 18 male 34.100 0 no southeast 1137.011
## 335 43 female 35.720 2 no northeast 19144.577
## 1151 18 female 30.305 0 no northeast 2203.736
## 523 51 female 33.915 0 no northeast 9866.305
## 931 26 male 46.530 1 no southeast 2927.065
## 685 33 female 18.500 1 no southwest 4766.022
## 317 50 male 32.205 0 no northwest 8835.265
## 505 38 female 28.930 1 no southeast 5974.385
## 221 34 female 33.700 1 no southwest 5012.471
## 1187 20 male 35.625 3 yes northwest 37465.344
## 141 34 male 22.420 2 no northeast 27375.905
## 1125 23 female 42.750 1 yes northeast 40904.200
## 450 35 male 38.600 1 no southwest 4762.329
## 870 25 female 24.300 3 no southwest 4391.652
## 455 32 male 46.530 2 no southeast 4686.389
## 5 32 male 28.880 0 no northwest 3866.855insurance_test## age sex bmi children smoker region charges
## 4 33 male 22.705 0 no northwest 21984.471
## 6 31 female 25.740 0 no southeast 3756.622
## 7 46 female 33.440 1 no southeast 8240.590
## 9 37 male 29.830 2 no northeast 6406.411
## 12 62 female 26.290 0 yes southeast 27808.725
## 14 56 female 39.820 0 no southeast 11090.718
## 17 52 female 30.780 1 no northeast 10797.336
## 21 60 female 36.005 0 no northeast 13228.847
## 22 30 female 32.400 1 no southwest 4149.736
## 24 34 female 31.920 1 yes northeast 37701.877
## 28 55 female 32.775 2 no northwest 12268.632
## 29 23 male 17.385 1 no northwest 2775.192
## 33 19 female 28.600 5 no southwest 4687.797
## 35 28 male 36.400 1 yes southwest 51194.559
## 39 35 male 36.670 1 yes northeast 39774.276
## 42 31 female 36.630 2 no southeast 4949.759
## 43 41 male 21.780 1 no southeast 6272.477
## 46 55 male 37.300 0 no southwest 20630.284
## 48 28 female 34.770 0 no northwest 3556.922
## 50 36 male 35.200 1 yes southeast 38709.176
## 51 18 female 35.625 0 no northeast 2211.131
## 56 58 male 36.955 2 yes northwest 47496.494
## 57 58 female 31.825 2 no northeast 13607.369
## 61 43 male 27.360 3 no northeast 8606.217
## 62 25 male 33.660 4 no southeast 4504.662
## 64 28 female 25.935 1 no northwest 4133.642
## 65 20 female 22.420 0 yes northwest 14711.744
## 66 19 female 28.900 0 no southwest 1743.214
## 69 40 female 36.190 0 no southeast 5920.104
## 74 58 male 32.010 1 no southeast 11946.626
## 75 44 male 27.400 2 no southwest 7726.854
## 79 22 female 39.805 0 no northeast 2755.021
## 80 41 female 32.965 0 no northwest 6571.024
## 81 31 male 26.885 1 no northeast 4441.213
## 85 37 female 34.800 2 yes southwest 39836.519
## 89 46 female 27.740 0 no northwest 8026.667
## 93 59 male 29.830 3 yes northeast 30184.937
## 96 28 female 37.620 1 no southeast 3766.884
## 97 54 female 30.800 3 no southwest 12105.320
## 101 41 female 31.600 0 no southwest 6186.127
## 103 18 female 30.115 0 no northeast 21344.847
## 104 61 female 29.920 3 yes southeast 30942.192
## 109 29 male 27.940 0 no southeast 2867.120
## 113 37 male 30.800 0 no southwest 4646.759
## 114 21 female 35.720 0 no northwest 2404.734
## 115 52 male 32.205 3 no northeast 11488.317
## 124 44 male 31.350 1 yes northeast 39556.495
## 125 47 female 33.915 3 no northwest 10115.009
## 128 52 female 37.400 0 no southwest 9634.538
## 132 61 female 22.040 0 no northeast 13616.359
## 133 53 female 35.900 2 no southwest 11163.568
## 143 34 male 25.300 2 yes southeast 18972.495
## 149 53 female 37.430 1 no northwest 10959.695
## 151 35 male 24.130 1 no northwest 5125.216
## 154 42 female 23.370 0 yes northeast 19964.746
## 156 44 male 39.520 0 no northwest 6948.701
## 157 48 male 24.420 0 yes southeast 21223.676
## 160 50 female 27.830 3 no southeast 19749.383
## 170 27 male 18.905 3 no northeast 4827.905
## 172 49 male 30.300 0 no southwest 8116.680
## 173 18 male 15.960 0 no northeast 1694.796
## 176 63 female 37.700 0 yes southwest 48824.450
## 183 22 male 19.950 3 no northeast 4005.423
## 188 30 female 30.900 3 no southwest 5325.651
## 191 61 male 31.570 0 no southeast 12557.605
## 196 19 male 30.590 0 no northwest 1639.563
## 197 39 female 32.800 0 no southwest 5649.715
## 200 64 female 39.330 0 no northeast 14901.517
## 202 48 female 32.230 1 no southeast 8871.152
## 204 27 female 36.080 0 yes southeast 37133.898
## 205 46 male 22.300 0 no southwest 7147.105
## 208 35 male 27.740 2 yes northeast 20984.094
## 212 40 male 30.875 4 no northwest 8162.716
## 213 24 male 28.500 2 no northwest 3537.703
## 219 26 female 29.920 1 no southeast 3392.977
## 223 32 male 30.800 3 no southwest 5253.524
## 227 28 male 38.060 0 no southeast 2689.495
## 235 39 male 24.510 2 no northwest 6710.192
## 236 40 female 22.220 2 yes southeast 19444.266
## 241 23 female 36.670 2 yes northeast 38511.628
## 242 33 female 22.135 1 no northeast 5354.075
## 243 55 female 26.800 1 no southwest 35160.135
## 244 40 male 35.300 3 no southwest 7196.867
## 247 60 female 38.060 0 no southeast 12648.703
## 248 24 male 35.860 0 no southeast 1986.933
## 251 18 male 17.290 2 yes northeast 12829.455
## 252 63 female 32.200 2 yes southwest 47305.305
## 253 54 male 34.210 2 yes southeast 44260.750
## 256 55 female 25.365 3 no northeast 13047.332
## 257 56 male 33.630 0 yes northwest 43921.184
## 262 20 female 26.840 1 yes southeast 17085.268
## 267 40 male 19.800 1 yes southeast 17179.522
## 270 49 male 25.840 1 no northeast 9282.481
## 271 18 male 29.370 1 no southeast 1719.436
## 273 41 male 37.050 2 no northwest 7265.703
## 275 25 male 27.550 0 no northwest 2523.169
## 281 40 female 28.120 1 yes northeast 22331.567
## 283 30 male 27.645 1 no northeast 4237.127
## 286 46 male 26.620 1 no southeast 7742.110
## 288 63 female 26.220 0 no northwest 14256.193
## 290 52 male 26.400 3 no southeast 25992.821
## 291 28 female 33.400 0 no southwest 3172.018
## 292 29 male 29.640 1 no northeast 20277.808
## 296 18 male 22.990 0 no northeast 1704.568
## 302 53 female 22.610 3 yes northeast 24873.385
## 311 50 male 26.600 0 no southwest 8444.474
## 313 43 male 35.970 3 yes southeast 42124.515
## 318 54 male 32.775 0 no northeast 10435.065
## 326 40 male 34.105 1 no northeast 6600.206
## 327 27 female 23.210 1 no southeast 3561.889
## 328 45 male 36.480 2 yes northwest 42760.502
## 329 64 female 33.800 1 yes southwest 47928.030
## 339 50 male 32.300 1 yes northeast 41919.097
## 344 63 male 36.765 0 no northeast 13981.850
## 354 33 male 35.245 0 no northeast 12404.879
## 356 46 male 27.600 0 no southwest 24603.048
## 358 47 male 29.830 3 no northwest 9620.331
## 366 49 female 30.780 1 no northeast 9778.347
## 373 42 female 33.155 1 no northeast 7639.417
## 377 39 female 24.890 3 yes northeast 21659.930
## 380 62 male 31.460 1 no southeast 27000.985
## 381 27 female 17.955 2 yes northeast 15006.579
## 386 19 male 34.400 0 no southwest 1261.859
## 388 50 male 25.365 2 no northwest 30284.643
## 389 26 female 22.610 0 no northwest 3176.816
## 390 24 female 30.210 3 no northwest 4618.080
## 392 19 female 37.430 0 no northwest 2138.071
## 394 49 male 31.350 1 no northeast 9290.139
## 396 46 male 19.855 0 no northwest 7526.706
## 397 43 female 34.400 3 no southwest 8522.003
## 407 33 female 24.310 0 no southeast 4185.098
## 409 38 male 21.120 3 no southeast 6652.529
## 410 32 male 30.030 1 no southeast 4074.454
## 419 64 male 39.160 1 no southeast 14418.280
## 422 61 male 35.860 0 yes southeast 46599.108
## 424 25 male 30.590 0 no northeast 2727.395
## 430 27 female 30.400 3 no northwest 18804.752
## 435 31 male 28.595 1 no northwest 4243.590
## 442 33 female 33.500 0 yes southwest 37079.372
## 443 18 male 43.010 0 no southeast 1149.396
## 456 59 male 37.400 0 no southwest 21797.000
## 462 42 male 30.000 0 yes southwest 22144.032
## 465 19 male 25.175 0 no northwest 1632.036
## 466 30 female 28.380 1 yes southeast 19521.968
## 469 28 female 24.320 1 no northeast 23288.928
## 470 18 female 24.090 1 no southeast 2201.097
## 471 27 male 32.670 0 no southeast 2497.038
## 477 24 male 28.500 0 yes northeast 35147.528
## 486 31 female 31.065 0 no northeast 4347.023
## 488 19 male 28.700 0 no southwest 1253.936
## 493 18 female 25.080 0 no northeast 2196.473
## 498 45 male 28.700 2 no southwest 8027.968
## 501 29 male 34.400 0 yes southwest 36197.699
## 502 43 male 26.030 0 no northeast 6837.369
## 503 51 male 23.210 1 yes southeast 22218.115
## 507 22 male 31.350 1 no northwest 2643.269
## 514 19 male 30.400 0 no southwest 1256.299
## 517 20 male 35.310 1 no southeast 27724.289
## 521 50 female 27.360 0 no northeast 25656.575
## 522 32 female 44.220 0 no southeast 3994.178
## 527 19 female 30.590 2 no northwest 24059.680
## 529 46 male 39.425 1 no northeast 8342.909
## 530 18 male 25.460 0 no northeast 1708.001
## 532 62 female 31.730 0 no northeast 14043.477
## 538 46 female 30.200 2 no southwest 8825.086
## 540 53 male 31.350 0 no southeast 27346.042
## 542 20 female 31.790 2 no southeast 3056.388
## 543 63 female 36.300 0 no southeast 13887.204
## 544 54 female 47.410 0 yes southeast 63770.428
## 545 54 male 30.210 0 no northwest 10231.500
## 552 32 female 28.930 0 no southeast 3972.925
## 557 46 male 33.440 1 no northeast 8334.590
## 565 18 female 32.120 2 no southeast 2801.259
## 570 48 male 40.565 2 yes northwest 45702.022
## 575 57 female 34.295 2 no northeast 13224.057
## 581 59 male 25.460 1 no northeast 12913.992
## 584 32 female 23.650 1 no southeast 17626.240
## 588 34 female 30.210 1 yes northwest 43943.876
## 591 58 female 29.000 0 no southwest 11842.442
## 598 34 female 33.250 1 no northeast 5594.846
## 600 52 female 37.525 2 no northwest 33471.972
## 604 64 female 39.050 3 no southeast 16085.128
## 605 19 female 28.310 0 yes northwest 17468.984
## 606 51 female 34.100 0 no southeast 9283.562
## 609 28 male 26.980 2 no northeast 4435.094
## 610 30 male 37.800 2 yes southwest 39241.442
## 611 47 female 29.370 1 no southeast 8547.691
## 616 47 female 36.630 1 yes southeast 42969.853
## 620 55 female 37.100 0 no southwest 10713.644
## 625 59 male 28.785 0 no northwest 12129.614
## 627 36 male 28.880 3 no northeast 6748.591
## 631 53 male 36.100 1 no southwest 10085.846
## 635 51 male 39.700 1 no southwest 9391.346
## 637 19 female 24.510 1 no northwest 2709.112
## 642 42 male 28.310 3 yes northwest 32787.459
## 647 39 male 26.220 1 no northwest 6123.569
## 653 48 female 31.130 0 no southeast 8280.623
## 654 45 female 36.300 2 no southeast 8527.532
## 657 26 female 42.400 1 no southwest 3410.324
## 658 27 male 33.155 2 no northwest 4058.712
## 659 48 female 35.910 1 no northeast 26392.260
## 663 32 female 31.540 1 no northeast 5148.553
## 664 18 male 33.660 0 no southeast 1136.399
## 665 64 female 22.990 0 yes southeast 27037.914
## 666 43 male 38.060 2 yes southeast 42560.430
## 670 40 female 29.810 1 no southeast 6500.236
## 677 55 female 40.810 3 no southeast 12485.801
## 681 21 female 17.400 1 no southwest 2585.269
## 683 39 male 35.300 2 yes southwest 40103.890
## 684 53 male 24.320 0 no northwest 9863.472
## 687 42 male 26.125 2 no northeast 7729.646
## 690 27 male 31.130 1 yes southeast 34806.468
## 695 27 female 34.800 1 no southwest 3577.999
## 697 53 female 32.300 2 no northeast 29186.482
## 701 21 female 34.870 0 no southeast 2020.552
## 702 50 female 44.745 0 no northeast 9541.696
## 705 47 female 29.545 1 no northwest 8930.935
## 706 33 female 32.900 2 no southwest 5375.038
## 709 31 female 30.495 3 no northeast 6113.231
## 714 20 male 40.470 0 no northeast 1984.453
## 715 24 female 22.600 0 no southwest 2457.502
## 720 58 female 33.440 0 no northwest 12231.614
## 724 19 male 35.400 0 no southwest 1263.249
## 726 30 female 39.050 3 yes southeast 40932.429
## 728 29 female 21.755 1 yes northeast 16657.717
## 732 53 male 21.400 1 no southwest 10065.413
## 733 24 female 30.100 3 no southwest 4234.927
## 737 37 female 38.390 0 yes southeast 40419.019
## 740 29 male 35.500 2 yes southwest 44585.456
## 747 34 male 27.000 2 no southwest 11737.849
## 750 28 male 30.875 0 no northwest 3062.508
## 751 37 female 26.400 0 yes southeast 19539.243
## 752 21 male 28.975 0 no northwest 1906.358
## 755 24 male 33.630 4 no northeast 17128.426
## 757 39 female 22.800 3 no northeast 7985.815
## 761 22 female 34.580 2 no northeast 3925.758
## 763 33 male 27.100 1 yes southwest 19040.876
## 765 45 female 25.175 2 no northeast 9095.068
## 779 35 male 34.320 3 no southeast 5934.380
## 782 18 male 41.140 0 no southeast 1146.797
## 787 60 male 36.955 0 no northeast 12741.167
## 790 62 female 29.920 0 no southeast 13457.961
## 793 22 female 23.180 0 no northeast 2731.912
## 798 30 female 22.895 1 no northeast 4719.524
## 800 33 male 24.795 0 yes northeast 17904.527
## 801 42 female 26.180 1 no southeast 7046.722
## 803 21 male 22.300 1 no southwest 2103.080
## 805 23 male 26.510 0 no southeast 1815.876
## 806 45 female 35.815 0 no northwest 7731.858
## 807 40 female 41.420 1 no northwest 28476.735
## 810 25 male 25.840 1 no northeast 3309.793
## 812 33 female 42.940 3 no northwest 6360.994
## 829 41 male 30.780 3 yes northeast 39597.407
## 836 42 male 35.970 2 no southeast 7160.330
## 840 59 female 31.350 0 no northwest 12622.180
## 843 23 female 32.780 2 yes southeast 36021.011
## 844 57 female 29.810 0 yes southeast 27533.913
## 847 51 female 34.200 1 no southwest 9872.701
## 855 49 female 23.845 3 yes northeast 24106.913
## 856 20 female 29.600 0 no southwest 1875.344
## 858 25 male 24.130 0 yes northwest 15817.986
## 863 55 female 33.535 2 no northwest 12269.689
## 864 36 female 19.855 0 no northeast 5458.046
## 868 57 male 43.700 1 no southwest 11576.130
## 876 23 female 28.120 0 no northwest 2690.114
## 877 49 female 27.100 1 no southwest 26140.360
## 888 36 female 30.020 0 no northwest 5272.176
## 892 36 female 29.040 4 no southeast 7243.814
## 896 61 female 44.000 0 no southwest 13063.883
## 897 43 female 20.045 2 yes northeast 19798.055
## 898 19 male 25.555 1 no northwest 2221.564
## 902 60 male 40.920 0 yes southeast 48673.559
## 904 49 male 36.850 0 no southeast 8125.784
## 906 26 female 29.355 2 no northeast 4564.191
## 908 44 female 32.340 1 no southeast 7633.721
## 910 32 female 24.600 0 yes southwest 17496.306
## 919 61 female 28.200 0 no southwest 13041.921
## 920 35 female 34.210 1 no southeast 5245.227
## 921 62 female 25.000 0 no southwest 13451.122
## 924 34 male 35.815 0 no northwest 4320.411
## 928 57 female 20.100 1 no southwest 12032.326
## 933 46 male 25.800 5 no southwest 10096.970
## 935 32 male 37.180 2 no southeast 4673.392
## 936 59 female 27.500 0 no southwest 12233.828
## 938 39 female 24.225 5 no northwest 8965.796
## 943 18 female 40.185 0 no northeast 2217.469
## 944 19 male 22.610 0 no northwest 1628.471
## 945 62 male 39.930 0 no southeast 12982.875
## 947 42 male 35.800 2 no southwest 7160.094
## 948 37 male 34.200 1 yes northeast 39047.285
## 950 25 male 29.700 3 yes southwest 19933.458
## 952 51 male 42.900 2 yes southeast 47462.894
## 956 31 male 39.490 1 no southeast 3875.734
## 969 21 male 25.745 2 no northeast 3279.869
## 974 19 female 40.500 0 no southwest 1759.338
## 980 36 female 29.920 0 no southeast 4889.037
## 985 20 male 30.115 5 no northeast 4915.060
## 988 45 female 27.645 1 no northwest 28340.189
## 989 34 male 34.675 0 no northeast 4518.826
## 990 24 female 20.520 0 yes northeast 14571.891
## 994 38 male 28.270 1 no southeast 5484.467
## 996 39 female 23.275 3 no northeast 7986.475
## 998 63 female 36.850 0 no southeast 13887.969
## 1008 47 male 28.215 3 yes northwest 24915.221
## 1012 43 male 20.130 2 yes southeast 18767.738
## 1016 59 male 25.460 0 no northwest 12124.992
## 1018 26 female 34.200 2 no southwest 3987.926
## 1027 19 male 26.030 1 yes northwest 16450.895
## 1031 46 female 23.655 1 yes northwest 21677.283
## 1033 30 female 27.930 0 no northeast 4137.523
## 1038 45 female 30.495 1 yes northwest 39725.518
## 1040 19 male 27.265 2 no northwest 22493.660
## 1041 35 female 28.025 0 yes northwest 20234.855
## 1043 20 male 30.685 0 yes northeast 33475.817
## 1045 55 male 35.245 1 no northeast 11394.066
## 1046 43 female 24.700 2 yes northwest 21880.820
## 1053 49 male 29.830 1 no northeast 9288.027
## 1058 45 female 31.790 0 no southeast 17929.303
## 1059 24 female 39.490 0 no southeast 2480.979
## 1060 32 male 33.820 1 no northwest 4462.722
## 1061 24 male 32.010 0 no southeast 1981.582
## 1067 48 male 37.290 2 no southeast 8978.185
## 1068 39 male 42.655 0 no northeast 5757.413
## 1070 54 female 31.900 1 no southeast 10928.849
## 1072 63 male 31.445 0 no northeast 13974.456
## 1079 28 male 31.680 0 yes southeast 34672.147
## 1084 32 male 31.500 1 no southwest 4076.497
## 1088 57 male 31.540 0 no northwest 11353.228
## 1089 52 male 47.740 1 no southeast 9748.911
## 1098 22 male 33.770 0 no southeast 1674.632
## 1102 53 male 28.600 3 no southwest 11253.421
## 1106 54 female 31.240 0 no southeast 10338.932
## 1109 26 male 30.000 1 no southwest 2904.088
## 1110 45 male 20.350 3 no southeast 8605.362
## 1113 48 female 25.850 3 yes southeast 24180.933
## 1116 55 male 32.670 1 no southeast 10807.486
## 1117 41 male 29.640 5 no northeast 9222.403
## 1118 25 male 33.330 2 yes southeast 36124.574
## 1119 33 male 35.750 1 yes southeast 38282.749
## 1122 46 male 38.170 2 no southeast 8347.164
## 1123 53 female 36.860 3 yes northwest 46661.442
## 1124 27 female 32.395 1 no northeast 18903.491
## 1130 19 female 18.600 0 no southwest 1728.897
## 1134 52 female 18.335 0 no northwest 9991.038
## 1137 44 female 25.000 1 no southwest 7623.518
## 1139 33 male 30.250 0 no southeast 3704.354
## 1140 19 female 32.490 0 yes northwest 36898.733
## 1144 39 male 32.340 2 no southeast 6338.076
## 1148 20 female 31.920 0 no northwest 2261.569
## 1158 23 female 23.180 2 no northwest 14426.074
## 1159 20 female 30.590 0 no northeast 2459.720
## 1163 30 male 38.830 1 no southeast 18963.172
## 1165 41 female 28.310 1 no northwest 7153.554
## 1167 57 male 40.370 0 no southeast 10982.501
## 1180 31 male 29.810 0 yes southeast 19350.369
## 1183 25 female 30.300 0 no southwest 2632.992
## 1186 45 male 23.560 2 no northeast 8603.823
## 1193 58 female 32.395 1 no northeast 13019.161
## 1200 31 female 25.800 2 no southwest 4934.705
## 1203 22 male 32.110 0 no northwest 2055.325
## 1204 51 male 32.300 1 no northeast 9964.060
## 1205 18 female 27.280 3 yes southeast 18223.451
## 1211 36 male 30.875 1 no northwest 5373.364
## 1212 39 male 34.100 2 no southeast 23563.016
## 1217 40 male 25.080 0 no southeast 5415.661
## 1218 29 male 37.290 2 no southeast 4058.116
## 1220 38 female 30.210 3 no northwest 7537.164
## 1223 50 male 25.300 0 no southeast 8442.667
## 1224 20 female 24.420 0 yes southeast 26125.675
## 1228 42 male 37.180 2 no southeast 7162.012
## 1229 56 male 34.430 0 no southeast 10594.226
## 1230 58 male 30.305 0 no northeast 11938.256
## 1231 52 male 34.485 3 yes northwest 60021.399
## 1236 26 male 31.065 0 no northwest 2699.568
## 1237 63 female 21.660 0 no northeast 14449.854
## 1244 28 female 33.110 0 no southeast 3171.615
## 1247 45 female 25.700 3 no southwest 9101.798
## 1249 18 female 39.820 0 no southeast 1633.962
## 1251 24 male 29.830 0 yes northeast 18648.422
## 1253 20 male 27.300 0 yes southwest 16232.847
## 1266 64 male 23.760 0 yes southeast 26926.514
## 1269 20 female 33.300 0 no southwest 1880.487
## 1271 26 male 33.915 1 no northwest 3292.530
## 1272 25 female 34.485 0 no northwest 3021.809
## 1273 43 male 25.520 5 no southeast 14478.330
## 1275 26 male 27.060 0 yes southeast 17043.341
## 1278 32 female 29.735 0 no northwest 4357.044
## 1280 25 female 26.790 2 no northwest 4189.113
## 1281 48 female 33.330 0 no southeast 8283.681
## 1282 47 female 27.645 2 yes northwest 24535.699
## 1285 61 male 36.300 1 yes southwest 47403.880
## 1293 21 male 23.210 0 no southeast 1515.345
## 1300 19 female 25.745 1 no northwest 2710.829
## 1307 29 female 21.850 0 yes northeast 16115.305
## 1308 32 male 28.120 4 yes northwest 21472.479
## 1309 25 female 30.200 0 yes southwest 33900.653
## 1311 42 male 26.315 1 no northwest 6940.910
## 1328 51 male 30.030 1 no southeast 9377.905
## 1331 57 female 25.740 2 no southeast 12629.166
## 1333 52 female 44.700 3 no southwest 11411.685
## 1335 18 female 31.920 0 no northeast 2205.9812. Regression Tree (4 points)
- Fit a regression tree based on the training data,
using the
chargesas response variable, and all other variables as predictors. Then visualize the tree usingrpart.plot.
# Your code here
library(rpart)
library(rpart.plot)## Warning: package 'rpart.plot' was built under R version 4.5.2insurance_rpart <- rpart(charges ~ ., data = insurance_train, method = "anova")
rpart.plot(insurance_rpart)
- Pruning: Fit a large regression tree with
cp = 0.001, and then useplotcp()function to view the complexity parameter plot. Based on this plot, what value of cp you would you choose to prune the tree, and why?
# Your code here
insurance_pruned_tree <- rpart(charges ~. , data = insurance_train, method = "anova", cp = 0.001)
plotcp(insurance_pruned_tree)
Comments:
The tree/cplot decreases down to the zeroes. However I’d choose 1.0/0.095 because that’s the higest the plot goes.
- Refit the regression tree using the cp selected in question (b). Then obtain the predictions on the testing data.
# Your code here
insurance_pruned_tree_2 <- rpart(charges ~. , data = insurance_test, method = "anova", cp = 0.001)
plotcp(insurance_pruned_tree_2)
- Obtain the out-of-sample MSE (Mean Squared Error) for both the initial tree model in (a) and the pruned tree model in (c). Which model is preferred for this data, and why?
# Your code here
pred_insurance_full <- predict(insurance_rpart, newdata = insurance_test)
pred_insurance_pruned <- predict(insurance_pruned_tree_2, newdata = insurance_test)
mean( (insurance_test$charge - pred_insurance_full)^2) ## [1] 30205107mean( (insurance_test$charge - pred_insurance_pruned)^2)## [1] 20683373Comments:
For pred_insurance_full, we get 24,738,968. For pred_insurance_prunned, we get 15,232,707. Our best pick is model A aka pred_insurance_full.
End of Exam. Please double-check that your RMD file knits successfully. Submit both the RMD and the generated HTML report.
Reminder: If a specific chunk causes an error, comment it out to allow the file to knit. Failure to submit an HTML report may result in a point deduction.