install.packages("AER", repos = "http://cran.us.r-project.org")##
## The downloaded binary packages are in
## /var/folders/xw/gzd_szgs3nvfyhc2s98_d7sr0000gn/T//RtmpctEOtQ/downloaded_packageslibrary("AER")## Loading required package: car## Loading required package: carData## Loading required package: lmtest## Loading required package: zoo##
## Attaching package: 'zoo'## The following objects are masked from 'package:base':
##
## as.Date, as.Date.numeric## Loading required package: sandwich## Loading required package: survivaldata("PSID7682")
earnings <- PSID7682
earnings <- earnings[, c("id", "year", setdiff(names(earnings), c("id", "year")))]Panel data on earnings of 595 individuals for the years 1976--1982, originating from the Panel Study of Income Dynamics. (Provided by RDocumentation)
Variables:
id: factor indicating individual subject ID
year: factor indicating year
experience: years of full-time work experience
weeks: weeks worked
occupation: factor. Is the individual a
white-collar ("white") or blue-collar
("blue") worker?
industry: factor. Does the individual work in a manufacturing industry?
south: factor. Does the individual reside in the South?
smsa: factor. Does the individual reside in a SMSA (standard metropolitan statistical area)?
married: factor. Is the individual married?
gender: factor indicating gender.
union: factor. Is the individual’s wage set by a union contract?
education: years of education
ethnicity: factor indicating ethnicity. Is the
individual African-American ("afam") or
not ("other")?
wage: wage (income)
earnings## id year experience weeks occupation industry south smsa married gender
## 1 1 1976 3 32 white no yes no yes male
## 2 1 1977 4 43 white no yes no yes male
## 3 1 1978 5 40 white no yes no yes male
## 4 1 1979 6 39 white no yes no yes male
## 5 1 1980 7 42 white yes yes no yes male
## 6 1 1981 8 35 white yes yes no yes male
## 7 1 1982 9 32 white yes yes no yes male
## 8 2 1976 30 34 blue no no no yes male
## 9 2 1977 31 27 blue no no no yes male
## 10 2 1978 32 33 blue yes no no yes male
## 11 2 1979 33 30 blue yes no no yes male
## 12 2 1980 34 30 blue yes no no yes male
## 13 2 1981 35 37 blue yes no no yes male
## 14 2 1982 36 30 blue yes no no yes male
## 15 3 1976 6 50 blue yes no no yes male
## 16 3 1977 7 51 blue yes no no yes male
## 17 3 1978 8 50 blue yes no no yes male
## 18 3 1979 9 52 blue yes no no yes male
## 19 3 1980 10 52 blue yes no no yes male
## 20 3 1981 11 52 blue yes no no no male
## 21 3 1982 12 46 blue yes no no no male
## 22 4 1976 31 52 blue no no yes no female
## 23 4 1977 32 46 blue no no yes no female
## 24 4 1978 33 46 blue no no yes no female
## 25 4 1979 34 49 blue no no yes no female
## 26 4 1980 35 44 blue no no yes no female
## 27 4 1981 36 52 blue no no yes no female
## 28 4 1982 37 46 blue no no yes no female
## 29 5 1976 10 50 blue no no no yes male
## 30 5 1977 11 46 blue no no no yes male
## 31 5 1978 12 40 blue no no no yes male
## 32 5 1979 13 50 white no no no yes male
## 33 5 1980 14 47 blue no no yes yes male
## 34 5 1981 15 47 white no no no yes male
## 35 5 1982 16 49 white no no no yes male
## 36 6 1976 26 44 blue yes no yes yes male
## 37 6 1977 27 47 blue yes no yes yes male
## 38 6 1978 28 47 blue yes no yes yes male
## 39 6 1979 29 47 blue yes no yes yes male
## 40 6 1980 30 44 blue yes no yes yes male
## 41 6 1981 31 45 blue yes no yes yes male
## 42 6 1982 32 47 blue yes no yes yes male
## 43 7 1976 15 46 blue no no no yes male
## 44 7 1977 16 48 blue no no no yes male
## 45 7 1978 17 49 blue no no no yes male
## 46 7 1979 18 46 blue no no no yes male
## 47 7 1980 19 47 blue no no no yes male
## 48 7 1981 20 47 blue no no no yes male
## 49 7 1982 21 48 blue no no no yes male
## 50 8 1976 23 51 blue yes yes no yes male
## 51 8 1977 24 50 blue yes yes no yes male
## 52 8 1978 25 50 blue yes yes no yes male
## 53 8 1979 26 50 blue yes yes no yes male
## 54 8 1980 27 44 blue yes no yes yes male
## 55 8 1981 28 51 blue yes no yes yes male
## 56 8 1982 29 51 blue yes no yes yes male
## 57 9 1976 3 50 white no yes yes yes male
## 58 9 1977 4 48 white no yes yes yes male
## 59 9 1978 5 50 white no yes yes yes male
## 60 9 1979 6 48 white no yes yes yes male
## 61 9 1980 7 48 white no yes yes yes male
## 62 9 1981 8 44 white no yes yes yes male
## 63 9 1982 9 48 white no yes yes yes male
## 64 10 1976 3 49 white no yes yes yes male
## 65 10 1977 4 47 white no yes yes yes male
## 66 10 1978 5 46 white no yes yes yes male
## 67 10 1979 6 44 white no yes yes yes male
## 68 10 1980 7 43 white no yes yes yes male
## 69 10 1981 8 34 white no yes yes yes male
## 70 10 1982 9 40 white no yes yes yes male
## 71 11 1976 24 47 blue no no yes no male
## 72 11 1977 25 48 blue no no yes no male
## 73 11 1978 26 45 blue no no yes no male
## 74 11 1979 27 45 blue no no yes yes male
## 75 11 1980 28 47 blue no no yes yes male
## 76 11 1981 29 17 blue no no yes yes male
## 77 11 1982 30 47 blue no no yes yes male
## 78 12 1976 21 47 blue no yes yes yes male
## 79 12 1977 22 46 blue no yes yes yes male
## 80 12 1978 23 47 blue no yes yes yes male
## 81 12 1979 24 47 blue no yes yes yes male
## 82 12 1980 25 47 blue no yes yes yes male
## 83 12 1981 26 47 blue no yes yes yes male
## 84 12 1982 27 46 blue no yes yes yes male
## 85 13 1976 26 48 blue no yes yes yes male
## 86 13 1977 27 48 blue no yes yes yes male
## 87 13 1978 28 50 blue no yes yes yes male
## 88 13 1979 29 48 blue no yes yes yes male
## 89 13 1980 30 48 blue no yes yes yes male
## 90 13 1981 31 46 white no yes yes yes male
## 91 13 1982 32 46 blue no yes yes yes male
## 92 14 1976 15 45 white no yes yes yes male
## 93 14 1977 16 45 white no yes yes yes male
## 94 14 1978 17 45 white no yes yes yes male
## 95 14 1979 18 44 white no yes yes yes male
## 96 14 1980 19 44 white no yes yes yes male
## 97 14 1981 20 44 white no yes yes yes male
## 98 14 1982 21 44 white no yes yes yes male
## 99 15 1976 9 50 white no no no no female
## 100 15 1977 10 46 white no no no no female
## 101 15 1978 11 48 white no no no no female
## 102 15 1979 12 46 white no no no no female
## 103 15 1980 13 48 white no no no no female
## 104 15 1981 14 41 white no no no no female
## 105 15 1982 15 48 white no no no no female
## 106 16 1976 16 50 blue no yes yes no female
## 107 16 1977 17 50 blue no yes yes no female
## 108 16 1978 18 48 blue no yes yes no female
## 109 16 1979 19 48 blue no yes yes no female
## 110 16 1980 20 50 blue no yes yes no female
## 111 16 1981 21 50 blue no yes yes no female
## 112 16 1982 22 49 blue no yes yes no female
## 113 17 1976 16 49 white yes no no yes male
## 114 17 1977 17 48 white yes no no yes male
## 115 17 1978 18 49 white yes no no yes male
## 116 17 1979 19 50 white yes no no yes male
## 117 17 1980 20 51 white yes no no yes male
## 118 17 1981 21 46 white yes no no yes male
## 119 17 1982 22 47 white yes no no yes male
## 120 18 1976 25 47 white yes yes yes yes male
## 121 18 1977 26 46 white yes yes yes yes male
## 122 18 1978 27 47 white yes yes yes yes male
## 123 18 1979 28 47 white yes yes yes yes male
## 124 18 1980 29 47 white yes yes yes yes male
## 125 18 1981 30 48 white yes yes yes yes male
## 126 18 1982 31 47 white yes yes yes yes male
## 127 19 1976 40 37 blue yes no yes yes male
## 128 19 1977 41 49 blue yes no yes yes male
## 129 19 1978 42 50 blue yes no yes yes male
## 130 19 1979 43 47 blue yes no yes yes male
## 131 19 1980 44 47 blue yes no yes yes male
## 132 19 1981 45 25 blue yes no yes yes male
## 133 19 1982 46 40 blue yes no yes yes male
## 134 20 1976 25 50 white no no no yes male
## 135 20 1977 26 49 white yes no no yes male
## 136 20 1978 27 49 white yes no no yes male
## 137 20 1979 28 48 white yes no no yes male
## 138 20 1980 29 48 white yes no no yes male
## 139 20 1981 30 49 white yes no no yes male
## 140 20 1982 31 48 white yes no no yes male
## 141 21 1976 28 42 blue yes yes no yes male
## 142 21 1977 29 46 blue yes yes no yes male
## 143 21 1978 30 49 blue yes yes no yes male
## 144 21 1979 31 49 blue yes yes no yes male
## 145 21 1980 32 48 blue no yes no yes male
## 146 21 1981 33 45 blue no yes no yes male
## 147 21 1982 34 42 blue yes yes no yes male
## 148 22 1976 20 46 white no no no yes male
## 149 22 1977 21 45 white no no no yes male
## 150 22 1978 22 44 white no no no yes male
## 151 22 1979 23 46 white no no no yes male
## 152 22 1980 24 47 white no no no yes male
## 153 22 1981 25 51 white yes no no yes male
## 154 22 1982 26 47 white no no no yes male
## 155 23 1976 11 50 white no no yes yes male
## 156 23 1977 12 50 white no no yes yes male
## 157 23 1978 13 51 white no no yes yes male
## 158 23 1979 14 50 white no no yes yes male
## 159 23 1980 15 48 white no no yes yes male
## 160 23 1981 16 47 white no no yes yes male
## 161 23 1982 17 50 white no no yes yes male
## 162 24 1976 5 30 white no no no no female
## 163 24 1977 6 51 white no no no no female
## 164 24 1978 7 51 blue no no no no female
## 165 24 1979 8 52 blue no no no no female
## 166 24 1980 9 49 blue no no no no female
## 167 24 1981 10 51 blue no no no no female
## 168 24 1982 11 50 blue no no no no female
## 169 25 1976 8 37 white no no yes yes male
## 170 25 1977 9 39 white no no yes yes male
## 171 25 1978 10 40 white no no yes yes male
## 172 25 1979 11 38 white no no yes yes male
## 173 25 1980 12 38 white no no yes yes male
## 174 25 1981 13 39 white no no yes yes male
## 175 25 1982 14 41 white no no yes yes male
## 176 26 1976 14 48 white yes yes yes yes male
## 177 26 1977 15 47 blue yes yes yes yes male
## 178 26 1978 16 49 white yes yes yes yes male
## 179 26 1979 17 48 white yes yes yes yes male
## 180 26 1980 18 47 white yes yes yes yes male
## 181 26 1981 19 47 white yes yes yes yes male
## 182 26 1982 20 48 white yes yes yes yes male
## 183 27 1976 8 50 white no no yes no male
## 184 27 1977 9 52 white no no yes no male
## 185 27 1978 10 48 white no no no no male
## 186 27 1979 11 50 white no no no no male
## 187 27 1980 12 50 white no no no no male
## 188 27 1981 13 45 white no no no no male
## 189 27 1982 14 23 white no no no no male
## 190 28 1976 26 50 blue no no yes yes male
## 191 28 1977 27 50 blue no no yes yes male
## 192 28 1978 28 50 blue no no yes yes male
## 193 28 1979 29 50 blue no no yes yes male
## 194 28 1980 30 50 blue no no yes yes male
## 195 28 1981 31 49 blue no no yes yes male
## 196 28 1982 32 49 blue no no yes yes male
## 197 29 1976 31 49 white no no yes yes male
## 198 29 1977 32 49 white no no yes yes male
## 199 29 1978 33 49 white no no yes yes male
## 200 29 1979 34 49 white no no yes yes male
## 201 29 1980 35 50 white no no yes yes male
## 202 29 1981 36 49 white no no yes yes male
## 203 29 1982 37 49 white no no yes yes male
## 204 30 1976 17 47 white no yes yes no female
## 205 30 1977 18 47 white no yes yes no female
## 206 30 1978 19 48 white no yes yes no female
## 207 30 1979 20 49 white no yes yes no female
## 208 30 1980 21 49 white no yes yes no female
## 209 30 1981 22 45 white no yes yes no female
## 210 30 1982 23 49 white no yes yes no female
## 211 31 1976 22 48 white yes no yes yes male
## 212 31 1977 23 48 white yes no yes yes male
## 213 31 1978 24 48 white yes no yes yes male
## 214 31 1979 25 47 white yes no yes yes male
## 215 31 1980 26 43 white yes no yes yes male
## 216 31 1981 27 47 white no no yes yes male
## 217 31 1982 28 45 white yes no yes yes male
## 218 32 1976 30 50 white yes no yes yes male
## 219 32 1977 31 49 white yes no yes yes male
## 220 32 1978 32 49 white yes no yes yes male
## 221 32 1979 33 48 white yes no yes yes male
## 222 32 1980 34 49 white yes no yes yes male
## 223 32 1981 35 47 white yes no yes yes male
## 224 32 1982 36 47 white yes no yes yes male
## 225 33 1976 14 51 white no no yes yes male
## 226 33 1977 15 47 white no no yes yes male
## 227 33 1978 16 51 white no no yes yes male
## 228 33 1979 17 47 white no no yes yes male
## 229 33 1980 18 48 white no no yes yes male
## 230 33 1981 19 50 white no no yes yes male
## 231 33 1982 20 49 white no no yes yes male
## 232 34 1976 45 48 blue no yes no yes male
## 233 34 1977 46 48 blue no yes no yes male
## 234 34 1978 47 48 blue no yes no yes male
## 235 34 1979 48 49 blue no yes no yes male
## 236 34 1980 49 50 blue no yes no yes male
## 237 34 1981 50 48 blue no yes no yes male
## 238 34 1982 51 46 blue no yes no yes male
## 239 35 1976 8 30 blue no no yes yes male
## 240 35 1977 9 49 blue yes no yes yes male
## 241 35 1978 10 48 blue yes no yes yes male
## 242 35 1979 11 49 blue yes no yes yes male
## 243 35 1980 12 34 blue yes no yes yes male
## 244 35 1981 13 48 blue yes no yes yes male
## 245 35 1982 14 45 blue yes no yes yes male
## 246 36 1976 15 52 blue no yes yes yes male
## 247 36 1977 16 47 white no yes yes yes male
## 248 36 1978 17 50 white no yes no yes male
## 249 36 1979 18 50 white no yes no yes male
## 250 36 1980 19 48 white no yes yes yes male
## 251 36 1981 20 50 white no yes yes yes male
## 252 36 1982 21 41 white no yes yes yes male
## 253 37 1976 12 52 white no no yes yes male
## 254 37 1977 13 47 white no no yes yes male
## 255 37 1978 14 50 white no no yes yes male
## 256 37 1979 15 49 white no no yes yes male
## 257 37 1980 16 50 white no no yes yes male
## 258 37 1981 17 48 white no no yes yes male
## 259 37 1982 18 49 white no no yes no male
## 260 38 1976 10 48 blue yes no no yes male
## 261 38 1977 11 49 blue yes no no yes male
## 262 38 1978 12 48 blue yes no no yes male
## 263 38 1979 13 48 blue yes no no yes male
## 264 38 1980 14 49 blue yes no no yes male
## 265 38 1981 15 48 white yes no no yes male
## 266 38 1982 16 49 blue yes no no yes male
## 267 39 1976 6 47 white no no yes yes male
## 268 39 1977 7 51 white no no yes no male
## 269 39 1978 8 48 white no no yes no male
## 270 39 1979 9 50 white no no yes no male
## 271 39 1980 10 50 white no no yes no male
## 272 39 1981 11 52 white no no yes no male
## 273 39 1982 12 51 white no no yes yes male
## 274 40 1976 30 47 white no yes no yes male
## 275 40 1977 31 39 white no yes no yes male
## 276 40 1978 32 32 white no yes no yes male
## 277 40 1979 33 35 white no yes no yes male
## 278 40 1980 34 47 white no yes no yes male
## 279 40 1981 35 45 white no yes no yes male
## 280 40 1982 36 47 white no yes no yes male
## 281 41 1976 20 50 white no yes yes yes male
## 282 41 1977 21 50 white no yes yes yes male
## 283 41 1978 22 50 white no yes yes yes male
## 284 41 1979 23 50 white no yes yes yes male
## 285 41 1980 24 50 white no yes yes yes male
## 286 41 1981 25 48 white no yes yes yes male
## 287 41 1982 26 47 white no yes yes yes male
## 288 42 1976 30 38 blue yes no yes no female
## 289 42 1977 31 41 blue no no yes no female
## 290 42 1978 32 51 blue no no yes no female
## 291 42 1979 33 50 blue yes no yes no female
## 292 42 1980 34 42 blue yes no yes no female
## 293 42 1981 35 50 blue yes no yes no female
## 294 42 1982 36 49 blue yes no yes no female
## 295 43 1976 5 49 white no no yes yes male
## 296 43 1977 6 47 white no no yes yes male
## 297 43 1978 7 48 white no no yes yes male
## 298 43 1979 8 49 white no no yes yes male
## 299 43 1980 9 46 white no no yes yes male
## 300 43 1981 10 45 white no no yes yes male
## 301 43 1982 11 49 white no no yes yes male
## 302 44 1976 7 48 white yes no yes yes male
## 303 44 1977 8 48 white yes no yes yes male
## 304 44 1978 9 48 white yes no yes yes male
## 305 44 1979 10 47 white yes no yes yes male
## 306 44 1980 11 46 white yes no yes yes male
## 307 44 1981 12 46 white yes no yes yes male
## 308 44 1982 13 46 white yes no yes yes male
## 309 45 1976 13 49 white no no yes no female
## 310 45 1977 14 50 white no no yes no female
## 311 45 1978 15 50 white no no yes no female
## 312 45 1979 16 50 white no no yes no female
## 313 45 1980 17 50 white no no yes no female
## 314 45 1981 18 50 white no no yes no female
## 315 45 1982 19 49 white no no yes no female
## 316 46 1976 6 42 blue no no no yes male
## 317 46 1977 7 44 blue no no no yes male
## 318 46 1978 8 48 blue no no no yes male
## 319 46 1979 9 47 blue no no no yes male
## 320 46 1980 10 48 blue no no no yes male
## 321 46 1981 11 47 white no no no yes male
## 322 46 1982 12 47 blue no no no yes male
## 323 47 1976 26 48 white no no yes yes male
## 324 47 1977 27 49 white no no yes yes male
## 325 47 1978 28 48 white no no yes yes male
## 326 47 1979 29 48 white no no yes yes male
## 327 47 1980 30 48 white no no yes yes male
## 328 47 1981 31 47 white no no yes yes male
## 329 47 1982 32 48 white no no yes yes male
## 330 48 1976 26 50 white yes no yes no male
## 331 48 1977 27 50 white yes no yes no male
## 332 48 1978 28 50 white yes no yes no male
## 333 48 1979 29 50 white yes no yes no male
## 334 48 1980 30 48 white yes no yes yes male
## 335 48 1981 31 41 white yes no yes yes male
## 336 48 1982 32 49 white yes no yes no male
## 337 49 1976 31 47 white yes no no yes male
## 338 49 1977 32 46 white yes no no yes male
## 339 49 1978 33 47 white yes no no yes male
## 340 49 1979 34 48 white yes no no yes male
## 341 49 1980 35 47 white yes no no yes male
## 342 49 1981 36 49 white yes no no yes male
## 343 49 1982 37 48 white yes no no yes male
## 344 50 1976 31 50 white no no yes no female
## 345 50 1977 32 45 white no no yes no female
## 346 50 1978 33 43 white no no yes no female
## 347 50 1979 34 48 white no no yes no female
## 348 50 1980 35 46 white no no yes no female
## 349 50 1981 36 32 white no no yes no female
## 350 50 1982 37 28 white no no yes no female
## 351 51 1976 31 45 white yes no yes yes male
## 352 51 1977 32 48 white yes no yes yes male
## 353 51 1978 33 48 white yes no yes yes male
## 354 51 1979 34 47 white no no yes yes male
## 355 51 1980 35 48 white yes no yes yes male
## 356 51 1981 36 47 white yes no yes yes male
## 357 51 1982 37 44 white yes no yes yes male
## 358 52 1976 25 46 white no no yes yes male
## 359 52 1977 26 49 white no no yes yes male
## 360 52 1978 27 49 white no no yes yes male
## 361 52 1979 28 48 white no no yes yes male
## 362 52 1980 29 48 white no no yes yes male
## 363 52 1981 30 48 white no no yes yes male
## 364 52 1982 31 49 white no no yes yes male
## 365 53 1976 13 47 white no yes no yes male
## 366 53 1977 14 49 white no yes no yes male
## 367 53 1978 15 48 blue no no no yes male
## 368 53 1979 16 49 blue no no no yes male
## 369 53 1980 17 48 white no no no yes male
## 370 53 1981 18 47 blue no no no yes male
## 371 53 1982 19 48 white no no no yes male
## 372 54 1976 13 47 blue yes no no yes male
## 373 54 1977 14 52 blue yes no no yes male
## 374 54 1978 15 51 blue yes no no yes male
## 375 54 1979 16 51 blue yes no no yes male
## 376 54 1980 17 49 blue yes no no yes male
## 377 54 1981 18 49 blue yes no no yes male
## 378 54 1982 19 50 blue yes no no yes male
## 379 55 1976 32 49 blue yes no yes yes male
## 380 55 1977 33 49 blue yes no yes yes male
## 381 55 1978 34 49 blue yes no yes yes male
## 382 55 1979 35 47 blue yes no yes yes male
## 383 55 1980 36 48 blue yes no yes yes male
## 384 55 1981 37 47 blue yes no yes yes male
## 385 55 1982 38 46 blue yes no yes yes male
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## 389 56 1979 26 52 blue yes yes no yes male
## 390 56 1980 27 48 blue yes yes no yes male
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## 393 57 1976 21 47 blue no yes yes yes male
## 394 57 1977 22 49 blue no yes yes yes male
## 395 57 1978 23 49 blue no yes yes yes male
## 396 57 1979 24 49 white no yes yes yes male
## 397 57 1980 25 47 white no yes yes yes male
## 398 57 1981 26 48 white no yes yes yes male
## 399 57 1982 27 48 white no yes yes yes male
## 400 58 1976 37 49 blue yes no yes yes male
## 401 58 1977 38 48 blue yes no yes yes male
## 402 58 1978 39 40 blue yes no yes yes male
## 403 58 1979 40 48 blue yes no yes yes male
## 404 58 1980 41 48 blue yes no yes yes male
## 405 58 1981 42 48 blue yes no yes yes male
## 406 58 1982 43 48 blue yes no yes yes male
## 407 59 1976 26 48 white yes no yes yes male
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## 419 60 1981 23 47 blue no no yes no female
## 420 60 1982 24 43 blue no no yes no female
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## 454 65 1981 35 45 blue yes no yes yes male
## 455 65 1982 36 45 blue yes no yes yes male
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## 457 66 1977 21 49 blue yes yes no yes male
## 458 66 1978 22 47 blue yes yes no yes male
## 459 66 1979 23 49 blue yes yes no yes male
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## 4072 582 1980 6 49 blue no no yes no male
## 4073 582 1981 7 50 blue no no yes no male
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## 4107 587 1980 16 48 blue no no yes yes male
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## 4109 587 1982 18 48 blue no no yes yes male
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## 4123 589 1982 37 46 blue no no yes yes male
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## 4163 595 1980 5 50 white no no yes no female
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## 4165 595 1982 7 50 white no no yes no female
## union education ethnicity wage
## 1 no 9 other 260
## 2 no 9 other 305
## 3 no 9 other 402
## 4 no 9 other 402
## 5 no 9 other 429
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## 9 no 11 other 500
## 10 yes 11 other 525
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## 12 no 11 other 810
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## 15 yes 12 other 285
## 16 yes 12 other 624
## 17 yes 12 other 698
## 18 yes 12 other 737
## 19 yes 12 other 809
## 20 yes 12 other 879
## 21 yes 12 other 954
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## 23 no 10 afam 512
## 24 no 10 afam 545
## 25 no 10 afam 578
## 26 no 10 afam 645
## 27 no 10 afam 708
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## 29 yes 16 other 625
## 30 yes 16 other 750
## 31 yes 16 other 760
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## 42 no 12 other 1539
## 43 yes 12 other 461
## 44 yes 12 other 480
## 45 yes 12 other 499
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## 48 yes 12 other 630
## 49 yes 12 other 680
## 50 yes 10 other 562
## 51 yes 10 other 604
## 52 yes 10 other 695
## 53 yes 10 other 708
## 54 yes 10 other 729
## 55 yes 10 other 914
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## 77 yes 12 other 1400
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## 146 yes 4 other 628
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## 276 yes 8 other 722
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## 289 yes 12 afam 661
## 290 yes 12 afam 721
## 291 yes 12 afam 804
## 292 yes 12 afam 892
## 293 yes 12 afam 1017
## 294 yes 12 afam 1125
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## 317 yes 12 other 509
## 318 yes 12 other 559
## 319 yes 12 other 558
## 320 yes 12 other 644
## 321 yes 12 other 740
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## 347 yes 12 other 704
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## 350 yes 12 other 943
## 351 no 17 other 998
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## 354 no 17 other 2100
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## 365 no 13 other 624
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## 368 no 13 other 1050
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## 370 no 13 other 1350
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## 373 yes 11 other 728
## 374 yes 11 other 800
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## 380 yes 8 other 944
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## 383 yes 8 other 1143
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## 393 no 11 other 420
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## 397 no 11 other 700
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## 401 yes 14 other 800
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## 405 yes 14 other 1290
## 406 no 14 other 1250
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## 409 no 17 other 1550
## 410 no 17 other 1700
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## 412 no 17 other 2000
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## 415 yes 11 afam 420
## 416 yes 11 afam 420
## 417 yes 11 afam 420
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## 419 yes 11 afam 502
## 420 yes 11 afam 479
## 421 yes 17 other 885
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## 429 no 16 other 930
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## 431 no 16 other 1052
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## 437 no 17 other 1800
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## 449 yes 8 other 703
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## 451 yes 8 other 831
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## 453 yes 8 other 1031
## 454 yes 8 other 1135
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## 471 yes 12 other 670
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## 482 no 13 other 930
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## 484 no 16 other 650
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## 494 no 16 other 1050
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## 497 no 16 other 1639
## 498 yes 17 other 650
## 499 yes 17 other 750
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## 501 yes 17 other 800
## 502 yes 17 other 950
## 503 yes 17 other 1000
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## 505 yes 16 other 640
## 506 yes 16 other 777
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## 511 yes 16 other 1228
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## 522 no 8 afam 480
## 523 no 8 afam 521
## 524 no 8 afam 625
## 525 no 8 afam 630
## 526 no 13 other 175
## 527 no 13 other 278
## 528 no 13 other 345
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## 530 yes 13 other 415
## 531 yes 13 other 470
## 532 no 13 other 516
## 533 no 10 other 250
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## 536 no 10 other 428
## 537 no 10 other 492
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## 540 no 12 other 300
## 541 no 12 other 325
## 542 no 12 other 325
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## 545 no 12 other 500
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## 547 no 8 other 228
## 548 no 8 other 238
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## 555 no 17 other 913
## 556 no 17 other 780
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## 558 no 17 other 1187
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## 564 yes 16 other 600
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## 566 no 16 other 1570
## 567 no 16 other 1304
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## 571 yes 12 other 981
## 572 yes 12 other 1051
## 573 yes 12 other 1026
## 574 yes 12 other 1171
## 575 yes 12 other 456
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## 584 no 17 afam 750
## 585 no 17 afam 603
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## 587 no 17 afam 1018
## 588 no 17 afam 813
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## 591 yes 7 other 556
## 592 yes 7 other 636
## 593 yes 7 other 675
## 594 yes 7 other 750
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## 602 no 12 other 775
## 603 yes 14 other 694
## 604 yes 14 other 737
## 605 yes 14 other 851
## 606 yes 14 other 958
## 607 yes 14 other 1052
## 608 yes 14 other 1112
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## 621 no 12 afam 780
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## 632 yes 7 other 610
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## 634 yes 7 other 867
## 635 yes 7 other 950
## 636 yes 7 other 1100
## 637 yes 7 other 1300
## 638 yes 14 other 650
## 639 yes 14 other 725
## 640 yes 14 other 840
## 641 yes 14 other 910
## 642 yes 14 other 1055
## 643 no 14 other 667
## 644 yes 14 other 814
## 645 yes 7 other 400
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## 651 yes 7 other 1000
## 652 yes 17 other 890
## 653 yes 17 other 940
## 654 yes 17 other 965
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## 656 yes 17 other 1208
## 657 yes 17 other 1288
## 658 yes 17 other 1288
## 659 yes 8 other 536
## 660 yes 8 other 560
## 661 yes 8 other 650
## 662 yes 8 other 668
## 663 yes 8 other 726
## 664 yes 8 other 867
## 665 yes 8 other 907
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## 704 no 14 other 1063
## 705 no 14 other 1018
## 706 no 14 other 1313
## 707 no 14 other 1303
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## 709 no 17 other 900
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## 712 no 17 other 1150
## 713 no 17 other 1500
## 714 no 17 other 1700
## 715 no 16 other 550
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## 717 no 16 other 750
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## 721 no 16 other 1050
## 722 no 7 other 310
## 723 no 7 other 335
## 724 no 7 other 365
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## 731 no 14 other 935
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## 754 yes 12 other 746
## 755 yes 12 other 850
## 756 yes 12 other 1250
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## 807 yes 14 other 925
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## 809 yes 14 other 1040
## 810 yes 14 other 1108
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## 818 yes 17 other 1028
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## 826 yes 9 other 1096
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## 851 yes 12 other 1071
## 852 yes 12 other 1019
## 853 yes 12 other 1100
## 854 yes 12 other 1100
## 855 yes 8 other 550
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## 860 yes 8 other 1050
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## 885 yes 14 other 1190
## 886 yes 14 other 1210
## 887 yes 14 other 1600
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## 889 yes 14 other 1560
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## 928 yes 12 afam 800
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## 930 yes 12 afam 1034
## 931 yes 12 afam 1150
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## 1048 yes 12 other 933
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## 1167 no 10 other 310
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## 1192 no 12 afam 375
## 1193 no 12 afam 437
## 1194 no 12 afam 437
## 1195 no 12 afam 525
## 1196 no 12 afam 625
## 1197 no 12 afam 700
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## 1215 yes 12 other 812
## 1216 yes 12 other 894
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## 1233 no 15 other 875
## 1234 no 15 other 921
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## 1237 no 15 other 500
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## 1239 no 15 other 730
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## 1242 no 9 other 514
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## 1257 no 12 other 838
## 1258 no 12 other 1796
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## 1286 no 12 other 1050
## 1287 yes 12 other 889
## 1288 yes 12 other 1200
## 1289 yes 12 other 700
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## 1291 yes 12 other 817
## 1292 yes 12 other 885
## 1293 yes 12 other 981
## 1294 yes 12 other 1105
## 1295 yes 12 other 1227
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## 1301 no 12 other 1722
## 1302 yes 12 other 1770
## 1303 yes 12 other 998
## 1304 yes 12 other 998
## 1305 yes 12 other 1232
## 1306 yes 12 other 1181
## 1307 yes 12 other 1162
## 1308 yes 12 other 1126
## 1309 yes 12 other 1426
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## 1312 no 12 other 928
## 1313 no 12 other 1018
## 1314 no 12 other 1123
## 1315 no 12 other 1168
## 1316 no 12 other 1317
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## 1323 no 17 other 1113
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## 1325 no 9 other 540
## 1326 no 9 other 605
## 1327 no 9 other 750
## 1328 no 9 other 828
## 1329 no 9 other 921
## 1330 no 9 other 1048
## 1331 yes 6 other 446
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## 1334 yes 6 other 585
## 1335 yes 6 other 648
## 1336 yes 6 other 697
## 1337 yes 6 other 728
## 1338 yes 12 other 537
## 1339 yes 12 other 639
## 1340 yes 12 other 699
## 1341 yes 12 other 770
## 1342 yes 12 other 870
## 1343 yes 12 other 936
## 1344 yes 12 other 1041
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## 1353 yes 12 other 930
## 1354 yes 12 other 896
## 1355 yes 12 other 899
## 1356 yes 12 other 1003
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## 1364 no 16 other 831
## 1365 no 16 other 829
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## 1368 no 9 other 625
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## 1370 no 9 other 800
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## 1372 no 9 other 1000
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## 1374 no 7 other 337
## 1375 no 7 other 365
## 1376 no 7 other 394
## 1377 no 7 other 425
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## 1382 no 12 other 875
## 1383 no 12 other 940
## 1384 no 12 other 1125
## 1385 no 12 other 1198
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## 1388 no 13 other 678
## 1389 no 13 other 738
## 1390 no 13 other 844
## 1391 no 13 other 937
## 1392 no 13 other 1000
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## 1395 no 17 other 565
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## 1403 yes 11 other 582
## 1404 yes 11 other 628
## 1405 yes 11 other 672
## 1406 yes 11 other 753
## 1407 yes 11 other 825
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## 1420 no 9 other 390
## 1421 no 9 other 410
## 1422 yes 9 other 650
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## 1424 no 9 other 725
## 1425 yes 9 other 790
## 1426 yes 9 other 900
## 1427 yes 9 other 1030
## 1428 yes 9 other 1150
## 1429 yes 12 other 697
## 1430 yes 12 other 800
## 1431 yes 12 other 1000
## 1432 yes 12 other 808
## 1433 yes 12 other 1000
## 1434 yes 12 other 1031
## 1435 yes 12 other 1151
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## 1437 no 13 other 998
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## 1439 no 13 other 1765
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## 1448 no 17 other 1750
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## 1453 yes 11 afam 315
## 1454 yes 11 afam 335
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## 1483 no 17 other 1341
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## 1497 no 12 other 700
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## 1500 no 16 afam 480
## 1501 no 16 afam 450
## 1502 no 16 afam 450
## 1503 no 16 afam 550
## 1504 no 16 afam 500
## 1505 no 16 afam 600
## 1506 no 17 other 950
## 1507 no 17 other 998
## 1508 no 17 other 1150
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## 1522 yes 12 other 603
## 1523 yes 12 other 693
## 1524 yes 12 other 697
## 1525 yes 12 other 773
## 1526 yes 12 other 803
## 1527 no 12 other 910
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## 1529 yes 12 other 1050
## 1530 no 12 other 1198
## 1531 yes 12 other 1579
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## 1533 yes 12 other 1354
## 1534 yes 12 other 651
## 1535 yes 12 other 702
## 1536 yes 12 other 756
## 1537 yes 12 other 850
## 1538 yes 12 other 925
## 1539 yes 12 other 1200
## 1540 yes 12 other 1154
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## 1543 yes 17 other 1350
## 1544 yes 17 other 1470
## 1545 yes 17 other 1600
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## 1554 no 11 other 575
## 1555 no 14 other 450
## 1556 no 14 other 515
## 1557 no 14 other 535
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## 1560 no 14 other 704
## 1561 no 14 other 875
## 1562 yes 5 other 998
## 1563 yes 5 other 998
## 1564 yes 5 other 1140
## 1565 yes 5 other 1240
## 1566 yes 5 other 1240
## 1567 yes 5 other 1300
## 1568 yes 5 other 1490
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## 1574 no 12 other 937
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## 1578 no 12 other 339
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## 1580 no 12 other 365
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## 1591 no 16 other 700
## 1592 no 16 other 900
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## 1609 yes 12 other 900
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## 1626 yes 10 other 825
## 1627 yes 10 other 925
## 1628 yes 10 other 1000
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## 1630 yes 10 other 1191
## 1631 yes 10 other 1250
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## 1634 yes 12 other 570
## 1635 yes 12 other 647
## 1636 yes 12 other 657
## 1637 yes 12 other 825
## 1638 yes 12 other 850
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## 1640 no 7 other 385
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## 1642 no 7 other 465
## 1643 no 7 other 480
## 1644 no 7 other 480
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## 1650 no 17 other 1600
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## 1674 yes 12 other 998
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## 1676 yes 12 other 1241
## 1677 yes 12 other 1393
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## 1679 yes 12 other 1750
## 1680 yes 12 other 1915
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## 1695 yes 12 other 998
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## 1699 yes 12 other 1530
## 1700 yes 12 other 1650
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## 1747 yes 10 other 536
## 1748 yes 10 other 600
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## 1763 no 17 afam 2000
## 1764 no 17 afam 2200
## 1765 yes 12 afam 512
## 1766 yes 12 afam 660
## 1767 yes 12 afam 680
## 1768 yes 12 afam 725
## 1769 yes 12 afam 900
## 1770 yes 12 afam 950
## 1771 yes 12 afam 1050
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## 1776 no 12 other 744
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## 1778 no 12 other 834
## 1779 no 12 other 425
## 1780 yes 12 other 410
## 1781 yes 12 other 533
## 1782 yes 12 other 583
## 1783 yes 12 other 638
## 1784 yes 12 other 708
## 1785 yes 12 other 758
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## 1787 yes 16 other 575
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## 1789 yes 16 other 800
## 1790 yes 16 other 1075
## 1791 yes 16 other 1100
## 1792 yes 16 other 1200
## 1793 yes 12 other 768
## 1794 yes 12 other 849
## 1795 yes 12 other 897
## 1796 yes 12 other 986
## 1797 yes 12 other 1127
## 1798 yes 12 other 1170
## 1799 yes 12 other 1340
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## 1802 no 17 other 763
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## 1813 no 10 other 477
## 1814 no 12 other 700
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## 1816 no 12 other 850
## 1817 no 12 other 1050
## 1818 no 12 other 1125
## 1819 no 12 other 1275
## 1820 no 12 other 1500
## 1821 yes 10 other 554
## 1822 yes 10 other 579
## 1823 yes 10 other 620
## 1824 yes 10 other 838
## 1825 yes 10 other 907
## 1826 yes 10 other 1045
## 1827 yes 10 other 1018
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## 1829 no 16 other 946
## 1830 no 16 other 1004
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## 1833 no 16 other 1325
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## 1836 no 12 afam 495
## 1837 no 12 afam 585
## 1838 no 12 afam 600
## 1839 no 12 afam 700
## 1840 no 12 afam 737
## 1841 no 12 afam 750
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## 1843 no 16 other 540
## 1844 no 16 other 550
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## 1846 no 16 other 750
## 1847 no 16 other 715
## 1848 no 16 other 1150
## 1849 yes 12 other 795
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## 1851 yes 12 other 936
## 1852 yes 12 other 1050
## 1853 yes 12 other 1100
## 1854 yes 12 other 1280
## 1855 yes 12 other 1360
## 1856 yes 17 other 998
## 1857 yes 17 other 998
## 1858 yes 17 other 1130
## 1859 yes 17 other 1200
## 1860 yes 17 other 1350
## 1861 yes 17 other 1425
## 1862 yes 17 other 1450
## 1863 yes 12 other 706
## 1864 yes 12 other 736
## 1865 yes 12 other 839
## 1866 yes 12 other 890
## 1867 yes 12 other 1000
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## 1869 yes 12 other 1200
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## 1876 no 14 other 725
## 1877 yes 9 other 630
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## 1879 yes 9 other 915
## 1880 yes 9 other 950
## 1881 yes 9 other 1100
## 1882 yes 9 other 1200
## 1883 yes 9 other 1350
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## 1888 no 16 other 3050
## 1889 no 16 other 2766
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## 1892 no 16 other 705
## 1893 no 16 other 719
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## 1895 no 16 other 600
## 1896 no 16 other 1200
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## 1898 no 16 other 575
## 1899 no 16 other 630
## 1900 no 16 other 900
## 1901 no 16 other 900
## 1902 no 16 other 1000
## 1903 no 16 other 1060
## 1904 no 16 other 1200
## 1905 yes 12 afam 551
## 1906 yes 12 afam 696
## 1907 yes 12 afam 709
## 1908 yes 12 afam 759
## 1909 yes 12 afam 900
## 1910 yes 12 afam 936
## 1911 yes 12 afam 990
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## 1913 no 17 other 857
## 1914 no 17 other 914
## 1915 no 17 other 1007
## 1916 no 17 other 1050
## 1917 no 17 other 1114
## 1918 no 17 other 1205
## 1919 no 17 other 500
## 1920 no 17 other 480
## 1921 no 17 other 575
## 1922 no 17 other 700
## 1923 no 17 other 635
## 1924 no 17 other 500
## 1925 no 17 other 2500
## 1926 yes 12 other 701
## 1927 yes 12 other 750
## 1928 yes 12 other 800
## 1929 yes 12 other 832
## 1930 yes 12 other 920
## 1931 yes 12 other 1050
## 1932 yes 12 other 1100
## 1933 no 8 other 615
## 1934 no 8 other 658
## 1935 no 8 other 829
## 1936 no 8 other 871
## 1937 no 8 other 900
## 1938 no 8 other 970
## 1939 no 8 other 1092
## 1940 no 15 other 998
## 1941 no 15 other 998
## 1942 no 15 other 1300
## 1943 no 15 other 1455
## 1944 no 15 other 1575
## 1945 no 15 other 1533
## 1946 no 15 other 1764
## 1947 yes 12 other 716
## 1948 yes 12 other 796
## 1949 yes 12 other 952
## 1950 yes 12 other 937
## 1951 yes 12 other 1062
## 1952 yes 12 other 1250
## 1953 yes 12 other 1326
## 1954 yes 13 other 425
## 1955 yes 13 other 425
## 1956 yes 13 other 450
## 1957 yes 13 other 500
## 1958 yes 13 other 525
## 1959 yes 13 other 525
## 1960 yes 13 other 550
## 1961 yes 12 other 686
## 1962 yes 12 other 706
## 1963 yes 12 other 721
## 1964 yes 12 other 832
## 1965 yes 12 other 969
## 1966 yes 12 other 1070
## 1967 yes 12 other 1100
## 1968 no 17 other 850
## 1969 no 17 other 850
## 1970 no 17 other 910
## 1971 no 17 other 945
## 1972 no 17 other 1125
## 1973 no 17 other 1200
## 1974 no 17 other 1450
## 1975 yes 9 other 998
## 1976 yes 9 other 500
## 1977 yes 9 other 1250
## 1978 yes 9 other 1000
## 1979 yes 9 other 1500
## 1980 yes 9 other 1750
## 1981 yes 9 other 1500
## 1982 yes 12 other 629
## 1983 yes 12 other 635
## 1984 yes 12 other 679
## 1985 yes 12 other 835
## 1986 yes 12 other 729
## 1987 yes 12 other 844
## 1988 yes 12 other 875
## 1989 no 12 other 654
## 1990 no 12 other 687
## 1991 no 12 other 856
## 1992 no 12 other 898
## 1993 no 12 other 862
## 1994 no 12 other 1063
## 1995 no 12 other 1002
## 1996 yes 10 other 400
## 1997 yes 10 other 590
## 1998 yes 10 other 710
## 1999 yes 10 other 840
## 2000 no 10 other 850
## 2001 yes 10 other 940
## 2002 yes 10 other 850
## 2003 yes 10 other 668
## 2004 yes 10 other 648
## 2005 yes 10 other 709
## 2006 yes 10 other 855
## 2007 yes 10 other 980
## 2008 yes 10 other 1091
## 2009 yes 10 other 1193
## 2010 no 12 other 958
## 2011 no 12 other 998
## 2012 no 12 other 1125
## 2013 no 12 other 1275
## 2014 no 12 other 1400
## 2015 no 12 other 1053
## 2016 no 12 other 1705
## 2017 no 16 other 998
## 2018 no 16 other 998
## 2019 no 16 other 1750
## 2020 no 16 other 2200
## 2021 no 16 other 2000
## 2022 no 16 other 2750
## 2023 no 16 other 2750
## 2024 no 13 other 538
## 2025 no 13 other 495
## 2026 no 13 other 515
## 2027 no 13 other 560
## 2028 no 13 other 690
## 2029 no 13 other 700
## 2030 no 13 other 750
## 2031 no 12 other 900
## 2032 no 12 other 925
## 2033 no 12 other 1080
## 2034 no 12 other 1100
## 2035 no 12 other 819
## 2036 no 12 other 1055
## 2037 no 12 other 1054
## 2038 no 12 other 747
## 2039 no 12 other 718
## 2040 no 12 other 800
## 2041 no 12 other 848
## 2042 no 12 other 1137
## 2043 no 12 other 1124
## 2044 no 12 other 1375
## 2045 yes 12 other 431
## 2046 yes 12 other 487
## 2047 yes 12 other 551
## 2048 yes 12 other 704
## 2049 yes 12 other 702
## 2050 yes 12 other 856
## 2051 yes 12 other 1014
## 2052 yes 12 other 491
## 2053 yes 12 other 526
## 2054 yes 12 other 581
## 2055 yes 12 other 626
## 2056 yes 12 other 695
## 2057 yes 12 other 746
## 2058 yes 12 other 826
## 2059 yes 12 other 563
## 2060 yes 12 other 746
## 2061 yes 12 other 841
## 2062 yes 12 other 875
## 2063 yes 12 other 958
## 2064 yes 12 other 1065
## 2065 yes 12 other 1150
## 2066 yes 8 other 630
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## 2068 no 8 other 600
## 2069 yes 8 other 653
## 2070 yes 8 other 729
## 2071 yes 8 other 730
## 2072 yes 8 other 879
## 2073 no 12 other 620
## 2074 no 12 other 621
## 2075 yes 12 other 731
## 2076 yes 12 other 822
## 2077 yes 12 other 850
## 2078 yes 12 other 970
## 2079 yes 12 other 900
## 2080 no 12 afam 660
## 2081 no 12 afam 500
## 2082 no 12 afam 835
## 2083 no 12 afam 785
## 2084 no 12 afam 550
## 2085 no 12 afam 500
## 2086 no 12 afam 500
## 2087 no 16 other 550
## 2088 no 16 other 550
## 2089 no 16 other 550
## 2090 no 16 other 550
## 2091 no 16 other 700
## 2092 no 16 other 750
## 2093 no 16 other 850
## 2094 no 12 other 467
## 2095 no 12 other 520
## 2096 no 12 other 550
## 2097 no 12 other 573
## 2098 no 12 other 640
## 2099 no 12 other 667
## 2100 no 12 other 733
## 2101 no 14 other 690
## 2102 no 14 other 700
## 2103 no 14 other 780
## 2104 no 14 other 925
## 2105 no 14 other 950
## 2106 no 14 other 1050
## 2107 no 14 other 1250
## 2108 yes 17 other 505
## 2109 yes 17 other 550
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## 2111 yes 17 other 795
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## 2113 yes 17 other 902
## 2114 yes 17 other 950
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## 2116 no 13 other 350
## 2117 no 13 other 435
## 2118 no 13 other 5000
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## 2120 no 13 other 725
## 2121 no 13 other 815
## 2122 yes 9 other 475
## 2123 yes 9 other 525
## 2124 yes 9 other 575
## 2125 yes 9 other 625
## 2126 yes 9 other 650
## 2127 yes 9 other 700
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## 2132 no 16 other 1410
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## 2135 no 16 other 1440
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## 2137 no 12 other 738
## 2138 no 12 other 813
## 2139 no 12 other 725
## 2140 no 12 other 613
## 2141 no 12 other 500
## 2142 no 12 other 750
## 2143 yes 8 other 633
## 2144 yes 8 other 790
## 2145 yes 8 other 709
## 2146 yes 8 other 740
## 2147 yes 8 other 930
## 2148 yes 8 other 955
## 2149 yes 8 other 1176
## 2150 yes 11 other 653
## 2151 yes 11 other 702
## 2152 yes 11 other 749
## 2153 yes 11 other 860
## 2154 yes 11 other 969
## 2155 yes 11 other 1086
## 2156 yes 11 other 1182
## 2157 yes 9 other 405
## 2158 yes 9 other 450
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## 2160 no 9 other 418
## 2161 no 9 other 453
## 2162 no 9 other 490
## 2163 no 9 other 529
## 2164 yes 12 other 562
## 2165 yes 12 other 598
## 2166 yes 12 other 655
## 2167 yes 12 other 713
## 2168 yes 12 other 815
## 2169 yes 12 other 889
## 2170 yes 12 other 969
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## 2172 no 12 other 710
## 2173 yes 12 other 735
## 2174 yes 12 other 805
## 2175 yes 12 other 935
## 2176 yes 12 other 1030
## 2177 yes 12 other 1137
## 2178 yes 14 other 717
## 2179 yes 14 other 774
## 2180 yes 14 other 859
## 2181 yes 14 other 935
## 2182 yes 14 other 999
## 2183 yes 14 other 799
## 2184 yes 14 other 1166
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## 2186 no 16 other 570
## 2187 no 16 other 620
## 2188 no 16 other 660
## 2189 no 16 other 762
## 2190 no 16 other 780
## 2191 no 16 other 1250
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## 2193 yes 12 other 576
## 2194 yes 12 other 611
## 2195 yes 12 other 660
## 2196 yes 12 other 753
## 2197 yes 12 other 894
## 2198 yes 12 other 1070
## 2199 no 17 other 301
## 2200 no 17 other 600
## 2201 no 17 other 600
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## 2203 no 17 other 750
## 2204 no 17 other 800
## 2205 no 17 other 925
## 2206 no 17 other 998
## 2207 no 17 other 998
## 2208 no 17 other 2150
## 2209 no 17 other 2325
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## 2223 yes 15 other 700
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## 2225 no 15 other 720
## 2226 no 15 other 1000
## 2227 yes 12 other 666
## 2228 yes 12 other 716
## 2229 yes 12 other 777
## 2230 yes 12 other 857
## 2231 yes 12 other 942
## 2232 yes 12 other 1036
## 2233 yes 12 other 1136
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## 2235 no 6 afam 511
## 2236 no 6 afam 529
## 2237 no 6 afam 650
## 2238 no 6 afam 732
## 2239 no 6 afam 630
## 2240 no 6 afam 880
## 2241 yes 12 other 420
## 2242 yes 12 other 496
## 2243 yes 12 other 530
## 2244 yes 12 other 600
## 2245 yes 12 other 646
## 2246 yes 12 other 696
## 2247 yes 12 other 798
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## 2249 no 12 other 850
## 2250 no 12 other 950
## 2251 no 12 other 1050
## 2252 no 12 other 1150
## 2253 no 12 other 1204
## 2254 no 12 other 1250
## 2255 no 16 other 700
## 2256 no 16 other 700
## 2257 no 16 other 900
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## 2259 no 16 other 960
## 2260 no 16 other 1100
## 2261 no 16 other 1250
## 2262 yes 14 other 487
## 2263 yes 14 other 740
## 2264 yes 14 other 800
## 2265 yes 14 other 870
## 2266 yes 14 other 954
## 2267 yes 14 other 1060
## 2268 yes 14 other 1100
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## 2270 no 15 other 540
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## 2274 no 15 other 750
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## 2276 no 12 other 700
## 2277 no 12 other 800
## 2278 no 12 other 700
## 2279 no 12 other 924
## 2280 no 12 other 900
## 2281 no 12 other 1257
## 2282 no 12 other 1317
## 2283 no 12 afam 377
## 2284 no 12 afam 491
## 2285 no 12 afam 511
## 2286 no 12 afam 550
## 2287 yes 12 afam 628
## 2288 no 12 afam 450
## 2289 no 12 afam 500
## 2290 no 10 other 750
## 2291 no 10 other 800
## 2292 yes 10 other 840
## 2293 yes 10 other 915
## 2294 no 10 other 965
## 2295 no 10 other 1060
## 2296 no 10 other 1145
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## 2298 no 15 other 650
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## 2305 no 17 other 910
## 2306 no 17 other 960
## 2307 no 17 other 945
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## 2314 yes 11 other 1100
## 2315 yes 11 other 1250
## 2316 yes 11 other 1222
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## 2326 yes 12 other 750
## 2327 yes 12 other 735
## 2328 yes 12 other 760
## 2329 yes 12 other 930
## 2330 yes 12 other 1096
## 2331 yes 12 other 1000
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## 2333 no 5 other 350
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## 2335 no 5 other 450
## 2336 no 5 other 450
## 2337 no 5 other 450
## 2338 no 5 other 600
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## 2341 no 16 other 660
## 2342 no 16 other 838
## 2343 no 16 other 850
## 2344 no 16 other 1144
## 2345 no 16 other 1200
## 2346 no 14 other 550
## 2347 no 14 other 690
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## 2354 no 12 other 875
## 2355 no 12 other 1000
## 2356 no 12 other 1063
## 2357 no 12 other 1056
## 2358 no 12 other 1222
## 2359 no 12 other 1625
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## 2362 yes 12 other 485
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## 2368 no 12 other 360
## 2369 no 12 other 378
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## 2371 no 12 other 437
## 2372 no 12 other 438
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## 2376 yes 12 other 843
## 2377 yes 12 other 905
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## 2379 yes 12 other 1010
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## 2397 yes 12 other 1320
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## 2409 yes 11 afam 475
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## 2414 yes 11 afam 700
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## 2422 yes 17 other 1500
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## 2447 yes 11 other 910
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## 2672 yes 12 afam 598
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## 2952 yes 12 other 714
## 2953 yes 12 other 794
## 2954 yes 12 other 873
## 2955 yes 10 other 770
## 2956 yes 10 other 805
## 2957 yes 10 other 805
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## 3019 yes 12 other 998
## 3020 yes 12 other 1140
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## 3033 yes 12 other 720
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## 3036 yes 12 other 946
## 3037 yes 12 other 1050
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## 3058 yes 12 other 597
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## 3112 yes 17 other 1200
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## 3131 yes 10 afam 720
## 3132 yes 10 afam 820
## 3133 yes 10 afam 840
## 3134 yes 10 afam 980
## 3135 yes 10 afam 1050
## 3136 yes 10 afam 1150
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## 3141 yes 12 other 718
## 3142 yes 12 other 1224
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## 3145 yes 11 other 725
## 3146 yes 11 other 781
## 3147 yes 11 other 871
## 3148 yes 11 other 980
## 3149 yes 11 other 1068
## 3150 yes 11 other 1192
## 3151 yes 11 other 568
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## 3153 yes 11 other 785
## 3154 yes 11 other 858
## 3155 yes 11 other 928
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## 3167 yes 12 other 986
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## 3269 yes 12 other 907
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## 3830 no 16 afam 950
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## 3942 yes 14 other 720
## 3943 yes 14 other 875
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## 3970 yes 14 other 617
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## 3973 yes 14 other 800
## 3974 yes 14 other 905
## 3975 yes 14 other 1016
## 3976 yes 14 other 1079
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## 3995 yes 12 other 1065
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## 4054 yes 12 other 540
## 4055 yes 12 other 595
## 4056 yes 12 other 640
## 4057 yes 12 other 720
## 4058 yes 12 other 740
## 4059 yes 12 other 825
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## 4062 yes 17 other 875
## 4063 yes 17 other 985
## 4064 yes 17 other 1050
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## 4066 yes 17 other 1325
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## 4072 no 12 other 887
## 4073 no 12 other 1010
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## 4104 yes 12 afam 815
## 4105 yes 12 afam 888
## 4106 yes 12 afam 977
## 4107 yes 12 afam 1186
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## 4109 yes 12 afam 1312
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## 4118 yes 12 other 843
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## 4123 yes 12 other 1300
## 4124 yes 12 other 565
## 4125 yes 12 other 688
## 4126 yes 12 other 750
## 4127 yes 12 other 730
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## 4136 yes 8 other 950
## 4137 yes 8 other 950
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## 4144 yes 13 other 1166
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## 4151 no 8 afam 292
## 4152 yes 12 other 617
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## 4154 yes 12 other 716
## 4155 yes 12 other 805
## 4156 yes 12 other 886
## 4157 yes 12 other 1012
## 4158 yes 12 other 1150
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## 4161 no 12 other 385
## 4162 no 12 other 430
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## 4164 no 12 other 540
## 4165 no 12 other 585I would like to keep things simple for this discussion and run a simple linear regression. We will regress the dependent variable (wage) on two arguments (experience and education) along with a dummy variable (union).
\[ wage = \beta_0 +\beta_1 (experience_i) +\beta_2(education_i)+\beta_3(union_i)+u_i \]
Dependent (y) variable: wage
Independent (x) variables: experience, education
regression <- lm(wage ~ education + experience + union, data = earnings)
regression##
## Call:
## lm(formula = wage ~ education + experience + union, data = earnings)
##
## Coefficients:
## (Intercept) education experience unionyes
## -278.13 71.16 11.92 28.46\[ \beta=(X'X)^{-1}X'Y \]
Now construct the X and Y matrices using the same variables from the regression.
#Construct the X matrix
B0 <-as.vector(rep(1,4165))
education <- as.vector(earnings$education)
experience <- as.vector(earnings$experience)
union <- ifelse(earnings$union == "yes", 1, 0)
X <- cbind(B0,education,experience,union)
#Call to wage for the Y axis
Y <- earnings$wage
#Now solve
beta_matrix <- solve(t(X) %*% X) %*% t(X) %*% Y
#make more presentable by saving to 2 decimals
bm <- round(x = beta_matrix, digits = 2)
bm## [,1]
## B0 -278.13
## education 71.16
## experience 11.92
## union 28.46Calculate residuals
\[ u_i =y_i-\hat{y}_i \]
residuals <- Y - X %*% beta_matrixCalculate RSS
\[ RSS=\sum_{i=1}^n u_i^2 \]
RSS <- sum(residuals^2)
RSS## [1] 633013075Calculate variance
\[ \hat{\sigma}^2=\displaystyle \frac{RSS}{n-k} \]
n <- nrow(X) #number of observations
k <- ncol(X) - 1 #number of parameters
variance <- RSS / (n - k)
variance## [1] 152093.5Calculate variance-covariance matrix
\[ Var(\hat{\beta})=\hat{\sigma^2}*(X^tX)^{-1} \]
var_cov_matrix <- variance * solve(t(X) %*% X)
var_cov_matrix## B0 education experience union
## B0 1273.057233 -76.4154056 -9.844745297 -1.634680e+02
## education -76.415406 5.3018760 0.273582175 7.910102e+00
## experience -9.844745 0.2735822 0.318903844 -2.660648e-03
## union -163.467971 7.9101018 -0.002660648 1.700961e+02Extract diagonal element to find standard error
\[ SE(\hat{\beta_i})=\sqrt Var(\hat{\beta_{ii}}) \]
se <- sqrt(diag(var_cov_matrix))
se## B0 education experience union
## 35.6799276 2.3025803 0.5647157 13.0420913Check for match
summary(regression)##
## Call:
## lm(formula = wage ~ education + experience + union, data = earnings)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1185.8 -238.4 -62.6 169.7 4293.4
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -278.1262 35.6842 -7.794 8.14e-15 ***
## education 71.1647 2.3029 30.903 < 2e-16 ***
## experience 11.9151 0.5648 21.097 < 2e-16 ***
## unionyes 28.4602 13.0437 2.182 0.0292 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 390 on 4161 degrees of freedom
## Multiple R-squared: 0.2247, Adjusted R-squared: 0.2241
## F-statistic: 402 on 3 and 4161 DF, p-value: < 2.2e-16Unfortunately, it appears that the standard errors do not match. Therefore, there must be an error in the formula above. I would appreciate any input or feedback to correct the mistake.