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weredwarf

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weredwarf
Sep 3rd, 2015
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  1. dput(data)
  2. structure(list(State = structure(c(46L, 1L, 2L, 3L, 4L, 5L, 6L,
  3. 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L,
  4. 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L,
  5. 33L, 34L, 35L, 36L, 37L, 38L, 39L, 41L, 42L, 43L, 44L, 45L, 47L,
  6. 48L, 49L, 50L, 51L, 52L, 53L, 40L, 46L, 1L, 2L, 3L, 4L, 5L, 6L,
  7. 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L,
  8. 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L,
  9. 33L, 34L, 35L, 36L, 37L, 38L, 39L, 41L, 42L, 43L, 44L, 45L, 47L,
  10. 48L, 49L, 50L, 51L, 52L, 53L, 40L, 46L, 1L, 2L, 3L, 4L, 5L, 6L,
  11. 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L,
  12. 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L,
  13. 33L, 34L, 35L, 36L, 37L, 38L, 39L, 41L, 42L, 43L, 44L, 45L, 47L,
  14. 48L, 49L, 50L, 51L, 52L, 53L, 40L, 46L, 1L, 2L, 3L, 4L, 5L, 6L,
  15. 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L,
  16. 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L,
  17. 33L, 34L, 35L, 36L, 37L, 38L, 39L, 41L, 42L, 43L, 44L, 45L, 47L,
  18. 48L, 49L, 50L, 51L, 52L, 53L, 40L, 46L, 1L, 2L, 3L, 4L, 5L, 6L,
  19. 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L,
  20. 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L,
  21. 33L, 34L, 35L, 36L, 37L, 38L, 39L, 41L, 42L, 43L, 44L, 45L, 47L,
  22. 48L, 49L, 50L, 51L, 52L, 53L, 40L, 46L, 1L, 2L, 3L, 4L, 5L, 6L,
  23. 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L,
  24. 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L,
  25. 33L, 34L, 35L, 36L, 37L, 38L, 39L, 41L, 42L, 43L, 44L, 45L, 47L,
  26. 48L, 49L, 50L, 51L, 52L, 53L, 40L), .Label = c("Alabama", "Alaska",
  27. "Arizona", "Arkansas", "California", "Colorado", "Connecticut",
  28. "Delaware", "District of Columbia", "Florida", "Georgia", "Hawaii",
  29. "Idaho", "Illinois", "Indiana", "Iowa", "Kansas", "Kentucky",
  30. "Louisiana", "Maine", "Maryland", "Massachusetts", "Michigan",
  31. "Minnesota", "Mississippi", "Missouri", "Montana", "Nebraska",
  32. "Nevada", "New Hampshire", "New Jersey", "New Mexico", "New York",
  33. "North Carolina", "North Dakota", "Ohio", "Oklahoma", "Oregon",
  34. "Pennsylvania", "Puerto Rico", "Rhode Island", "South Carolina",
  35. "South Dakota", "Tennessee", "Texas", "United States", "Utah",
  36. "Vermont", "Virginia", "Washington", "West Virginia", "Wisconsin",
  37. "Wyoming"), class = "factor"), Population = c(308.745538, 4.779736,
  38. 0.710231, 6.392017, 2.915918, 37.253956, 5.029196, 3.574097,
  39. 0.897934, 0.601723, 18.80131, 9.687653, 1.360301, 1.567582, 12.830632,
  40. 6.483802, 3.046355, 2.853118, 4.339367, 4.533372, 1.328361, 5.773552,
  41. 6.547629, 9.88364, 5.303925, 2.967297, 5.988927, 0.989415, 1.826341,
  42. 2.700551, 1.31647, 8.791894, 2.059179, 19.378102, 9.535483, 0.672591,
  43. 11.536504, 3.751351, 3.831074, 12.702379, 1.052567, 4.625364,
  44. 0.81418, 6.346105, 25.145561, 2.763885, 0.625741, 8.001024, 6.72454,
  45. 1.852994, 5.686986, 0.563626, 3.725789, 309.347057, 4.785822,
  46. 0.713856, 6.411999, 2.922297, 37.336011, 5.048575, 3.579345,
  47. 0.899731, 0.60521, 18.85222, 9.714464, 1.36395, 1.570639, 12.840097,
  48. 6.490308, 3.050295, 2.858949, 4.349838, 4.545581, 1.327361, 5.788101,
  49. 6.564073, 9.876498, 5.310418, 2.970811, 5.996085, 0.990575, 1.829865,
  50. 2.703493, 1.316517, 8.80358, 2.06495, 19.400867, 9.559488, 0.674345,
  51. 11.54007, 3.759481, 3.837083, 12.711077, 1.053078, 4.63629, 0.816192,
  52. 6.356628, 25.245717, 2.774346, 0.625792, 8.025376, 6.741911,
  53. 1.854176, 5.689268, 0.564358, 3.721527, 311.721632, 4.801695,
  54. 0.722572, 6.472867, 2.93843, 37.701901, 5.119661, 3.590537, 0.907829,
  55. 0.620427, 19.1079, 9.813201, 1.378251, 1.58378, 12.858725, 6.51656,
  56. 3.064904, 2.869965, 4.370038, 4.575972, 1.32793, 5.843833, 6.61227,
  57. 9.875736, 5.348036, 2.978464, 6.010544, 0.997661, 1.842232, 2.718586,
  58. 1.318109, 8.842614, 2.078407, 19.521745, 9.651502, 0.685242,
  59. 11.544757, 3.786527, 3.867644, 12.743995, 1.05202, 4.673054,
  60. 0.824171, 6.398389, 25.657477, 2.815324, 0.62645, 8.110188, 6.822112,
  61. 1.854982, 5.708785, 0.567631, 3.686771, 314.112078, 4.817484,
  62. 0.731081, 6.556236, 2.9493, 38.06278, 5.191709, 3.594362, 0.916881,
  63. 0.63504, 19.355257, 9.919, 1.392766, 1.59559, 12.873763, 6.537632,
  64. 3.075935, 2.885966, 4.383465, 4.604744, 1.328592, 5.891819, 6.655829,
  65. 9.884781, 5.380615, 2.986137, 6.025281, 1.005163, 1.855487, 2.755245,
  66. 1.321297, 8.876, 2.084594, 19.60714, 9.748181, 0.701705, 11.550901,
  67. 3.817059, 3.898684, 12.770043, 1.052637, 4.722621, 0.834504,
  68. 6.455177, 26.094422, 2.855194, 0.626138, 8.193422, 6.896325,
  69. 1.856313, 5.724888, 0.576893, 3.642281, 316.497531, 4.833996,
  70. 0.737259, 6.634997, 2.958765, 38.431393, 5.272086, 3.599341,
  71. 0.92524, 0.649111, 19.600311, 9.994759, 1.408987, 1.612843, 12.890552,
  72. 6.570713, 3.092341, 2.895801, 4.399583, 4.629284, 1.328702, 5.938737,
  73. 6.708874, 9.898193, 5.42206, 2.992206, 6.044917, 1.014864, 1.868969,
  74. 2.791494, 1.322616, 8.911502, 2.086895, 19.69568, 9.848917, 0.723857,
  75. 11.572005, 3.853118, 3.928068, 12.781296, 1.053354, 4.771929,
  76. 0.84551, 6.497269, 26.505637, 2.902787, 0.626855, 8.270345, 6.973742,
  77. 1.853595, 5.742953, 0.583223, 3.595839, 318.857056, 4.849377,
  78. 0.736732, 6.731484, 2.966369, 38.8025, 5.355866, 3.596677, 0.935614,
  79. 0.658893, 19.893297, 10.097343, 1.419561, 1.634464, 12.88058,
  80. 6.596855, 3.107126, 2.904021, 4.413457, 4.649676, 1.330089, 5.976407,
  81. 6.745408, 9.909877, 5.457173, 2.994079, 6.063589, 1.023579, 1.881503,
  82. 2.839099, 1.326813, 8.938175, 2.085572, 19.746227, 9.943964,
  83. 0.739482, 11.594163, 3.878051, 3.970239, 12.787209, 1.055173,
  84. 4.832482, 0.853175, 6.549352, 26.956958, 2.942902, 0.626562,
  85. 8.326289, 7.06153, 1.850326, 5.757564, 0.584153, 3.548397), Year = structure(c(6L,
  86. 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
  87. 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
  88. 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
  89. 6L, 6L, 6L, 6L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
  90. 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
  91. 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
  92. 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
  93. 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
  94. 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
  95. 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L,
  96. 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
  97. 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
  98. 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
  99. 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
  100. 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
  101. 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
  102. 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
  103. 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
  104. 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
  105. 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L), .Label = c("2,010",
  106. "2,011", "2,012", "2,013", "2,014", "Census"), class = "factor")), .Names = c("State",
  107. "Population", "Year"), row.names = c(NA, -318L), class = "data.frame")
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