###Ablos### Kuend<-c(0.65,1.04,1.33,1.47,1.60, 1.79,1.83,2.16,2.26,2.44,2.48,2.62,2.89,3.07) Ablos<-c(5.1,4.7,4.3,5.1,4.5,4.4,4.8,5.2,4.7,7.7,9.5,6.3,9.5,9.2) Land<-c("USA","Großbritannien","Irland","Australien","Schweiz","Japan","Dänemark","Österreich", "Niederlande","Italien","Deutschland","Schweden","Frankreich","Spanien") ABLOS<-cbind(Kuend,Ablos) dimnames(ABLOS)[1]<-list(Land) ### Approx.fun : Zeichnet ein Säulendiagramm einer Hyperg. Vertlng und deren Approximation durch die Binomialverteilung ### Approx.fun<-function(x,Ne,Nm,n) { barplot(rbind(dhyper(x,Ne,Nm,n),dbinom(x,n,Ne/(Ne+Nm))),col = c(1,2), legend=c("Hyper", "Binom"),beside=T,names=x,xlab="x", ylab="Wahrscheinlichkeit P(x)") abline(h = 0) } ### daten1 und daten2 daten1<-c(0.498,2.409,0.577,5.579,2.507,1.695,2.396,1.528,0.365,0.388,3.971,0.984,1.157,12.283,0.052,3.939,9.631,3.727,2.684,0.513,2.540,1.509,1.542,4.771,1.478,4.784,3.266,6.677,3.034,2.426,2.595,0.472,4.074,4.530,2.192,0.418,1.237,1.929,0.729,0.127,6.429,2.072,7.844,0.584,1.769,0.838,1.590,1.554,5.853,4.342) daten2<-c(3.418, 4.167, 3.037, 6.598, 4.69, 4.01, 6.052, 5.14, 1.525, 9.011, 7.932, 5.363, 8.409, 4.775, 3.952, 5.299, 1.766, 4.099, 3.234, 2.797, 2.662, 5.718, 3.777, 5.963, 3.828, 4.733, 7.303, 5.928, 3.04, 6.357, 5.92, 5.084, 4.451, -1.038, 2.591, 3.543, 3.656, 6.036, 3.555, 4.595, 7.356, 8.116, 3.669, 8.032, 6.007, 6.278, 4.109, 6.909, 4.224, 5.844, 7.123, 7.427, 5.263, 5.432, 3.253, 2.117, 3.642, 4.934, 2.987, 6.527, 6.019, 4.162, 6.368, 2.793, 5.054, 6.245, 9.5, 3.385, 3.411, 3.025, 5.825, 3.297, 4.706, 2.228, 8.75, 4.067, 4.932, 4.669, 1.941, 5.834, 5.31, 8.885, 4.193, 1.874, 7.99, 6.175, 3.395, 8.719, 6.676, 3.083, 1.406, 4.531, 4.433, 2.921, 4.451, 4.449, 1.789, 7.379, 7.383, 3.453, 8.957, 2.986, 6.042, 3.903, 6.515, 4.1, 6.42, 5.201, 3.826, 2.661, 3.823, 3.737, 3.886, 5.596, 1.929, 8.83, 3.02, 5.167, 4.274, 7.763, 8.243, 7.211, 6.311, 3.728, 5.204, 2.955, 4.254, 9.477, 3.541, 8.101, 6.447, 3.935, 6.131, 3.38, 0.632, 3.941, 2.292, 4.436, 6.116, 4.449, 5.007, 7.909, 7.296, 5.404, 3.079, 7.434, 5.963, 2.7, 3.431, 6.145, 7.47, 4.166, 2.948, 9.339, 2.716, 6.336, 8.151, 5.886, 4.453, 5.592, 7.066, 8.396, 7.082, 8.577, 6.767, 4.993, 5.737, 5.677, 2.428, 4.428, 5.417, 5.04, 1.862, 4.311, 3.459, 3.339, 3.027, 3.449, 3.403, 6.197, 4.687, 6.356, 3.86, 4.925, 6.187, 8.745, 5.567, 5.236, 7.065, 4.515, 6.208, 6.113, 10.753, 3.705, 4.444, 10.475, 7.848, 5.402, 4.989, 7.303, 7.863, 5.335, 4.859, 7.37, 6.863, 5.37, 1.538, 5.764, 6.007, 1.409, 3.601, 6.22, 4.469, 5.924, 3.106, 6.024, 4.366, 5.678, 4.103, 4.536, 6.926, 6.906, -0.227, 5.274, 4.145, 5.581, 3.927, 2.474, 4.435, 2.75, 5.739, 3.486, 3.785, 6.176, 3.221, 6.038, 7.939, 4.544, 3.902, 6.269, 6.121, 3.597, 5.155, 6.313, 5.634, 6.053, 9.115, 2.437, 6.306, 5.044, 7.093, 5.762, 5.761, 2.994, 3.657, 7.987, 6.724, 6.748, 4.349, 8.533, 4.146, 7.395, 2.227, 5.527, 3.63, 2.455, 5.388, 2.898, 6.425, 3.728, 4.74, 5.548, 1.627, 4.897, 7.49, 4.225, 4.638, 2.003, 4.67, 6.574, 7.341, 5.423, 6.417, 3.53, 3.496, 8.263, 4.39, 3.942, 5.622, 3.566, 7.297, 3.077, 3.832, 6.225, 4.575, 3.349, 5.431, 7.48, 5.257, 6.166, 5.669, 2.663, 7.357, 3.256, 2.829, 2.875, 3.289, 5.37, 3.254, 5.837, 5.34, 6.008, 1.657, 3.16, 5.374, 5.246, 1.551, 2.113, 3.618, 3.162, 3.913, 2.747, 3.016, 6.544, 4.985, 6.853, 6.654, 2.757, 5.845, 7.608, 3.696, 2.297, 8.477, 3.507, 6.882, 11.837, 6.761, 2.54, 7.571, 6.492, 4.183, 7.883, 6.731, 5.437, 7.618, 5.282, 4.586, 4.555, 3.951, 3.386, 4.179, 3.758, 3.633, 5.394, 0.871, 8.867, 4.662, 4.29, 3.194, 6.149, 6.644, 2.376, 4.62, 5.386, 3.453, 7.737, 4.108, 4.428, 5.457, 7.97, 7, 6.06, 2.655, 3.204, 5.282, 5.489, 5.307, 4.154, 6.881, 6.167, 5.77, 5.547, 8.673, 2.605, 3.605, 5.986, 5.044, 7.081, 7.382, 5.009, 3.98, 3.903, 7.729, 4.339, 4.264, 7.213, 3.266, 5.198, 5.348, 10.606, 1.362, 5.569, 3.688, 7.126, 4.846, 7.664, 6.014, 6.509, 3.274, 6.471, 8.074, 5.015, 4.024, 4.276, 7.187, 6.453, 6.449, 8.099, 3.32, 6.115, 6.159, 4.917, 3.61, 4.704, 6.249, 4.699, 5.012, 4.233, 3.296, 4.044, 5.788, 3.697, 7.93, 7.289, 1.8, 3.754, 8.518, 4.641, 2.882, 7.153, 5.628, 1.541, 3.782, 6.396, 5.464, 5.708, 6.376, 3.951, 2.973, 2.221, 3.28, 6.314, 5.545, 3.294, 2.994, 5.191, 4.242, 4.891, 7.958, 4.461, 4.426, 6.621, 4.511, 4.059, 3.931, 9.553, 2.174, -1.712, 5.854, 3.398, 4.896, 5.851, 4.476, 7.021, 6.181, 3.538, 4.958, 4.318, 5.238, 8.394, 6.386, 5.6, 6.912, 7.018, 4.337, 9.577, 5.367, 6.746, 6.899, 5.436, 7.123, 5.456, 4.332, 4.978, 7.749, 4.403, 5.55, 6.442, 5.859, 6.659, 2.307, 4.732, 7.387, 9.8, 5.667, 4.583, 4.249, 9.015, 6.55, 2.994, 4.848, 6.356, 4.08, 6.237, 9.016, 8.576, 6.419, 9.306, 5.591, 3.138, 9.481, 6.482, 6.546, 7.344, 4.681, 2.874, 4.375, 7.33, 5.327, 6.149, 9.436, 6.978, 5.442, 5.495, 1.328, 8.778, 5.494, 2.827, 7.495, 3.799, 6.637, 7.187, 2.721, 4.194, 5.037, -0.257, 2.946, 2.181, 6.323, 3.269, 4.644, 2.796, 6.587, 6.266, 5.675, 3.322, 8.733, 3.823, 5.351, 5.971, 1.914, 4.823, 6.863, 4.822, 2.714, 2.705, 6.536, 3.647, 2.91, 5.213, 6.309, 6.411, 3.522, 7.864, 5.005, 3.624, 3.51, 6.914, 5.414, 4.568, 6.074, 7.595, 7.066, 6.8, 4.7, 3.551, 1.614, 5.797, 8.266, 1.75, 4.618, 7.363, 5.298, 5.183, 9.014, 6.799, 6.795, 5.342, 1.467, 3.576, 3.442, 7.103, 6.243, 3.579, 6.366, 7.401, 4.48, 4.944, 8.785, 4.677, 6.086, 5.297, 6.804, 6.401, 4.757, 3.734, 4.603, 9.304, 6.498, 7.428, 3.075, 3.285, 4.886, 1.041, 6.045, 2.982, 3.305, 5.733, 3.717, 5.25, 4.348, 0.734, 4.332, 6.314, 2.5, 2.754, 2.41, 9.089, 5.507, 1.754, 4.09, 4.985, 3.946, 1.471, 6.595, 5.524, 7.4, 9.031, 2.155, 3.827, 5.291, 4.45, 5.077, 2.508, 2.725, 2.969, 5.219, 2.758, 4.115, 5.268, 4.497, 5.694, 2.618, 5.27, 4.276, 7.716, 3.279, 4.968, 5.551, 5.652, 4.248, 4.869, 3.08, 4.759, 2.819, 6.653, 6.223, 2.562, 5.086, 7.068, 4.557, 5.608, 5.76, 3.525, 7.61, 2.224, 6.909, 2.938, 6.434, 2.913, 5.673, 4.232, 7.964, 6.235, 5.979, 6.927, 2.766, 5.64, 8.258, 4.869, 5.713, 4.193, 4.659, 1.967, 4.788, 4.083, 4.632, 7.106, 4.361, 2.111, 5.333, 5.127, 3.492, 5.296, 5.666, 2.536, 5.079, 5.607, 4.792, 2.24, 4.979, 7.421, 0.955, 4.181, 10.313, 5.477, 1.443, 6.494, 4.044, 6.043, 5.777, 6.437, 2.906, 3.806, 4.518, 5.734, 5.345, 4.902, 1.108, 6.723, 6.41, 6.792, 4.896, 5.482, 3.964, 3.679, 5.036, 6.624, 1.659, 6.624, 6.321, 3.631, 5.621, 6.316, -0.753, 9.157, 5.258, 6.457, 2.315, 6.803, 2.724, 5.221, 4.348, 1.163, 0.775, 1.851, 4.547, 3.057, 5.629, 3.651, 4.574, 3.379, 3.644, 3.655, 5.324, 4.015, 7.064, 5.641, 6.062, 6.603, 5.169, 6.212, 5.891, 8.238, 4.872, 5.819, -1.84, 1.225, 2.275, 3.124, 5.512, 6.412, 3.672, 8.36, 2.33, 5.465, 4.498, 5.983, 5.795, 4.263, 8.085, 5.742, 7.375, 1.703, 4.585, 4.398, 5.097, 4.762, 4.578, 3.249, 2.579, 4.786, 4.112, 6.613, 7.452, 5.675, 4.113, 3.787, 5.472, 5.473, 4.809, 6.032, 3.34, 5.026, 5.795, 4.389, 4.579, 1.2, 8.286, 4.121, 6.753, 2.028, 7.602, 3.309, 3.381, 4.829, 3.062, 3.691, 4.299, 6.69, 5.646, 3.673, 5.888, 2.393, 5.509, 2.846, 6.3, 5.447, 4.574, 5.808, 4.687, 5.246, 7.077, 3.605, 2.732, 3.436, 7.604, 3.039, 4.306, 7.466, 3.541, 5.875, 3.442, 2.606, 6.303, 6.043, 4.957, 4.789, 4.299, 4.423, 4.869, 4.669, 3.908, 4.696, 10.753, 1.266, 8.663, 6.891, 3.308, 3.713, 4.362, 2.101, 7.251, 5.258, 4.44, 4.439, 4.79, 5.032, 5.24, 6.115, 4.254, 5.022, 3.883, 2.413, 3.927, 2.457, 7.008, 7.799, 6.47, 2.999, 7.204, 6.426, 4.934, 2.458, 2.5, 6.623, 4.532, 9.323, 7.015, 2.946, 6.695, 5.71, 3.283, 3.481, 4.75, 4.169, 2.33, 8.051, 7.449, 3.283, 4.202, 6.733, 7.435, 5.707, 5.018, 7.721, 4.395, 5.28, 6.286, 3.62, 3.445, 4.298, 3.07, 4.311, 7.606, 8.699, -0.638, 4.513, 7.432, 4.982, 1.982, 4.246, 6.841, 1.367, 7.604, 3.82, 3.993, 6.604, 2.182, 5.809, 2.576, 4.492, 6.275, 6.455, 3.535, 6.32, 5.289, -1.235, 5.858, 8.853, 4.579, 2.819, 1.298, 5.826, 3.094, 5.551, 1.95, 4.572, 4.536, 6.629, 7.687, 5.435, 2.618, 5.048, 2.452, 2.723, 5.158, 7.42, 3.092, 4.309, 7.528, 6.055, 4.172, 3.864, 8.029, 0.857, 7.432, 4.631, 3.463, 6.523, 5.321, 5.203, 6.808, 4.879, 2.824, 7.998, 4.536, 3.099, 7.948, 2.97) ###gluehall und konfi.fun### gluehall<-c(1067, 919,1196,785,1126, 936, 918,1156, 920, 948, 855,1092,1162,1170, 929, 950, 905, 972,1035,1045,1157,1195,1195,1340,1122, 938, 970,1237, 956,1102,1022, 978, 832,1009, 1157,1151,1009, 765, 958, 902, 923,1333, 811,1217,1085, 896, 958,1311,1037, 702, 521, 933, 928,1153, 946, 858,1071,1069, 830,1063, 930, 807, 954,1063,1002, 909,1077,1021,1062,1157, 999, 932,1035, 944,1049, 940,1122,1115, 833,1320, 901,1324, 818,1250,1203,1078, 890,1303, 1011,1102, 996, 780, 900,1106, 704, 621, 854,1178,1138, 951,1187,1067,1118,1037, 958, 760,1101, 949, 992, 966, 824, 653, 980, 935, 878, 934, 910,1058, 730, 980, 844, 814,1103,1000, 788,1143, 935,1069,1170,1067,1037,1151, 863, 990,1035,1112, 931, 970, 932, 904,1026,1147, 883, 867, 990, 1258,1192, 922,1150,1091,1039,1083,1040,1289, 699,1083, 880,1029, 658, 912,1023, 984, 856, 924, 801,1122,1292,1116, 880,1173,1134, 932, 938,1078,1180,1106,1184, 954, 824, 529, 998, 996,1133, 765, 775,1105,1081,1171, 705,1425, 610, 916,1001, 895, 709, 860,1110, 1149, 972,1002, 990,1141,1127,1181, 856, 716,1308, 943,1272, 917,1069, 976,1187,1107, 1230, 836,1034,1248,1061,1550,1240, 932,1165,1303,1085, 813,1340,1137, 773, 787,1438,1009, 1002,1061,1277, 892, 900,1384,1148,1117,1225,1176, 709,1485,1225,1011,1028,1227,1277,1222, 912, 885,1562,1118,1197, 976,1080, 924,1233,1135, 623, 983, 883,1088,1029,1201, 898, 970, 1058,1160, 831,1023,1354,1218,1121,1172,1169,1113,1308,1166,1470,1635,1141, 1555,1054,1461,1057,1228,1187,1016, 744,1197,1122, 666,1022, 964,1085, 612,1003,1235, 942,1055, 893, 1235,1056, 968,1056,1014,1096,1013, 889,1430, 926,1297,1033,1024,1103,1385,1077, 813, 1121, 960,1156,1033,1255, 225, 525, 675,1211, 995, 924, 732, 935,1173,1024, 1254,1014, 798,1080, 862,1220,1024,1170,1120, 898, 918,1086,1028, 1122, 872, 826,1337, 965,1297,1096,1068, 943,1490, 918, 609, 985,1233, 985, 985,1075,1240, 985, 1105,1243,1204,1203,1310,1262,1234,1104,1303,1185, 759, 1404,944,1343, 932,1055,1381, 816,1067,1252,1248,1324,1000, 984,1220, 972,1022, 956,1093,1358,1024, 1240,1157,1415,1385, 824,1690,1302,1233,1331,1109, 827,1209,1202,1229,1079,1176,1173, 769, 905) #### #### konfi.fun<-function (daten,Konfidenzniveau) { # Grenzen des Konfidenzintervalls fuer mue # bei Normalverteilung mit unbekannter Varianz # x: Datensatz n<-length(daten) xquer<-mean(daten) laenge<-qt(1-(1-Konfidenzniveau)/2,n-1)*sd(daten)/sqrt(n) segments(xquer-laenge,Konfidenzniveau/1000,xquer+laenge,Konfidenzniveau/1000) return(c(xquer-laenge,xquer+laenge)) } #### #### konfi1.fun<-function(daten=gluehall.dat,m=30,Konfidenzniveau=0.9){ w0 <- 20/2.54 h0 <- 12/2.54 PNG43D <- TRUE seqlen <- 1000 col1.light <- rgb(199, 209, 229, maxColorValue = 255) col2.light <- rgb(221, 204, 224, maxColorValue = 255) col3.light <- rgb(231, 202, 202, maxColorValue = 255) col4.light <- rgb(220, 208, 177, maxColorValue = 255) col5.light <- rgb(181, 212, 210, maxColorValue = 255) col1.medium <- rgb(124, 134, 201, maxColorValue = 255) col2.medium <- rgb(163, 130, 183, maxColorValue = 255) col3.medium <- rgb(191, 135, 135, maxColorValue = 255) col4.medium <- rgb(157, 138, 115, maxColorValue = 255) col5.medium <- rgb(127, 165, 162, maxColorValue = 255) col1 <- rgb( 45, 58, 189, maxColorValue = 255) col2 <- rgb( 94, 45, 177, maxColorValue = 255) col3 <- rgb(155, 71, 90, maxColorValue = 255) col4 <- rgb(143, 99, 53, maxColorValue = 255) col5 <- rgb( 48, 132, 131, maxColorValue = 255) col.notice <- "#ffff66" col.warning <- "#dd2222" col.warning2 <- "#eeaab1" croptop <- function() par(mai = par()$mai - c(0,0,0.5,0)) xlab <- function(lab, mgp1 = 3, cl = 0.9, ...){ pm <- par()$mgp par(mgp = c(mgp1,pm[2:3])) title(xlab = lab, cex.lab = cl, ...) par(mgp = pm) rm("pm") } ylab <- function(lab, mgp1 = 3, cl = 0.9, ...){ pm <- par()$mgp par(mgp = c(mgp1,pm[2:3])) title(ylab = lab, cex.lab = cl, ...) par(mgp = pm) rm("pm") } modseq <- function(x, val){ for (i in 1: length(val)){ x[(1:length(x))[((x-val[i])^2 == min((x-val[i])^2))][1]] <- val[i] } return(x) } gridw <- function(xlo, xhi, xdels, xdell, ylo, yhi, ydels, ydell, cols = "grey75", coll = "grey50", lwds = 0.5, lwdl = 0.5, ...) { nxs <- ceiling((xhi - xlo)/xdels) nxl <- ceiling((xhi - xlo)/xdell) nys <- ceiling((yhi - ylo)/ydels) nyl <- ceiling((yhi - ylo)/ydell) segments(rep(xlo, nys), seq(ylo, yhi, ydels), rep(xhi, nys), seq(ylo, yhi, ydels), col = cols, lwd = lwds) segments(seq(xlo, xhi, xdels), rep(ylo, nxs), seq(xlo, xhi, xdels), rep(yhi, nxs), col = cols, lwd = lwds) segments(rep(xlo, nyl), seq(ylo, yhi, ydell), rep(xhi, nyl), seq(ylo, yhi, ydell), col = coll, lwd = lwdl) segments(seq(xlo, xhi, xdell), rep(ylo, nxl), seq(xlo, xhi, xdell), rep(yhi, nxl), col = coll, lwd = lwdl) } ### mu <- mean(daten) ki <- matrix(NA, nrow = 20, ncol = 2) kic <- rep(NA, 20) kic2 <- rep(NA, 20) for (i in 1:20){ test <- sample(daten, m, replace = FALSE) ki[i,1] <- mean(test) - qt(1-(1-Konfidenzniveau)/2, m-1)*sd(test)/sqrt(m) ki[i,2] <- mean(test) + qt(1-(1-Konfidenzniveau)/2, m-1)*sd(test)/sqrt(m) kic[i] <- ifelse(mu < ki[i,1] | mu > ki[i,2], col.warning, col3.medium) kic2[i] <- ifelse(mu < ki[i,1] | mu > ki[i,2], 4, 3) } ## par(mfrow = c(1,1), mar = c(3.2,3.7,1.3,1.3), mgp = c(2.5,0.6,0), lab = c(8,20,8), lend = 1, las = 1) plot(0, 0, xlim = c(900,1200), ylim = c(1,20), type = "n", xlab = "Brenndauer\n", ylab = "Stichprobe", axes = FALSE) gridw(xlo = 900, xhi = 1200, xdels = 20, xdell = 100, ylo = 1, yhi = 20, ydels = 1, ydell = 19, lwds = 0.5, lwdl = 1) polygon(c(900,1200,1200,900), c(1,1,20,20)) axis(1, cex.axis = Konfidenzniveau) axis(2, at = 1:20, labels = 1:20, cex.axis = Konfidenzniveau) par(xpd=T) for (i in 1:20){ lines(c(ki[i,1],ki[i,2]), c(i,i),col=kic[i], lwd = kic2[i]) } par(xpd=F) segments(mu, Konfidenzniveau, mu, 20.4, col = col1, lwd = 3) text(mu, 20, expression(paste(mu," = 1045.4")), pos = 3, cex = 1.2, xpd = NA, col = col1)} ############################################################### ###Datensatz senat ############################################################### senat<-c(76.9,7.1,51.3,21.9,63.8,97.3,3.1,7.7,50.3,92.2,57.3,99.1,29.6,33.1,33.5, 79.1,20.9,67.8,40.9,61.2,17.3,89.7,36.4,68.6,2.8,29.7,24.9,99.3,15.1,59.6,38.4,85,8.7, 62.8,28.5,57.3,34.6,60.1,79.9,26,50.1,43.7,76,49.5,85,25.9,55.1,47.2,58.1,39.1,56.9,48, 58.7,35.2,71.9,47.8,78,23.4,66.5,27.4,66.8,25.5,60.7,41.4,70,47.7) senat<-matrix(senat,ncol=2,byrow="T") ############################################################### ###Datensatz ernlbsp ############################################################### ernlbsp<-c(-0.997,-0.888,-0.998,-0.205,-0.889, -0.709,-0.311,-0.746,-0.117,-1.252, 0.414,-0.637,-0.454,-0.89,-0.205, -0.926,-0.999,-0.816,-0.852,0.348, -0.098,-0.746,-0.818,-0.316,-0.889, -0.598,-1.036,-0.926,-1.431,-0.783, 1.797,1.874,1.228,-1.108,-0.286, 0.119,-0.893,-0.385,-0.892,-0.929, -1.036,-0.927,-0.963,-0.927,-0.204, -0.032,-0.42,-0.53,-0.09399999,-0.46, -1.072,-0.109,-0.164,-0.15,-0.365, -0.222,1.04,-0.748,-0.211,-0.182, -0.354,0.117,-0.855,-1.105,-0.888, 0.073,-1.036,-1.035,1.47,0.006, -0.46,-0.818,-0.891,1.067,-1.105, -0.745,1.539,1.279,1.353,1.447, 0.836,1.392,1.32,1.103,1.277, 1.071,1.308,1.55,0.91,1.703, 1.005,1.013,1.107,1.485,1.611, -0.924,2.106,1.728,1.352,1.876, 1.981,1.152,4.727388,5.241747,4.59512, 5.627621,4.584967,6.045005,6.467699,5.402677, 4.812184,6.049733,8.563313,5.241747,4.770685, 5.598422,5.891644,4.736198,5.451038,4.317488, 5.53339,7.17012,6.318968,5.525453,5.273, 6.42972,5.181784,5.768321,5.043425,4.343805, 4.983607,6.434547,8.800265,8.799812,7.594884, 5.831882,6.858565,6.608,6.272877,6.759255, 6.455199,6.331502,6.003887,6.318968,5.087596, 5.799093,7.118826,7.021084,6.568078,7.014814, 6.251904,6.206576,7.899895,7.532624,7.098376, 7.848934,7.26333,6.966024,8.232972,6.008813, 6.920672,8.077137,6.329721,6.645091,5.147494, 5.283204,4.60517,7.396949,4.969813,5.278115, 8.325064,6.216606,6.658011,5.087596,5.874931, 7.74846,5.463832,5.774552,8.606302,8.696845, 8.527935,8.734882,7.680637,7.92081,8.710125, 8.544614,8.133587,8.377241,8.47073,8.671287, 7.36328,8.837246,8.900413,7.657755,7.794823, 8.774931,8.389587,6.297109,7.68708,7.828038, 7.003065,7.953318,7.524561,7.026427) ernlbsp<-matrix(ernlbsp,ncol=2,byrow="F") ########################################################################## ### groegewicht #### ### Datensatz mit koerpergroesse (1.Spalte) und gewicht (2.Spalte) #### ########################################################################## groegewicht<-structure(c(171, 176, 161, 158, 168, 190, 181, 174, 183, 172, 183, 160, 196, 183, 164, 180, 190, 165, 171, 192, 178, 194, 168, 183, 177, 170, 178, 176, 178, 168, 182, 160, 164, 171, 196, 196, 184, 181, 170, 180, 169, 174, 172, 187, 170, 178, 174, 170, 167, 184, 190, 175, 184, 175, 198, 180, 175, 187, 167, 190, 189, 174, 193, 176, 158, 180, 184, 180, 176, 190, 175, 168, 174, 175, 190, 175, 195, 190, 178, 180, 175, 193, 183, 182, 180, 167, 176, 176, 188, 182, 187, 174, 172, 178, 172, 183, 178, 173, 162, 197, 178, 170, 193, 180, 193, 190, 187, 173, 178, 175, 186, 175, 176, 190, 181, 158, 188, 174, 184, 171, 177, 183, 184, 180, 175, 170, 181, 188, 175, 180, 194, 178, 166, 190, 183, 179, 170, 158, 178, 167, 162, 176, 181, 183, 177, 172, 186, 167, 168, 175, 166, 196, 162, 170, 158, 167, 170, 185, 185, 190, 170, 165, 180, 170, 191, 172, 171, 151, 168, 170, 167, 174, 153, 190, 179, 170, 193, 175, 170, 170, 170, 154, 175, 186, 178, 189, 201, 180, 186, 179, 159, 180, 190, 170, 179, 169, 189, 172, 168, 170, 180, 178, 169, 166, 179, 168, 195, 165, 169, 187, 189, 185, 166, 184, 178, 163, 176, 180, 178, 186, 176, 179, 175, 172, 172, 186, 186, 76, 71, 48, 50, 65, 86, 73, 73, 68, 56, 65, 57, 93, 65, 53, 75, 85, 53, 67, 83, 78, 85, 58, 75, 85, 50, 67, 68, 60, 56, 82, 50, 52, 57, 126, 83, 70, 72, 57, 75, 45, 65, 58, 78, 65, 76, 55, 60, 53, 84, 90, 70, 84, 52, 85, 63, 58, 81, 57, 85, 80, 62, 90, 72, 58, 75, 74, 69, 68, 80, 66, 50, 62, 65, 90, 57, 92, 82, 66, 65, 68, 90, 70, 67, 72, 49, 63, 62, 87, 80, 82, 60, 53, 58, 57, 98, 65, 50, 50, 137, 100, 57, 66, 65, 78, 85, 82, 72, 81, 82, 83, 70, 62, 74, 68, 43, 82, 60, 72, 50, 62, 72, 75, 74, 68, 54, 75, 87, 72, 75, 75, 68, 43, 86, 69, 75, 57, 52, 69, 60, 55, 65, 74, 78, 62, 64, 66, 62, 60, 62, 59, 96, 55, 55, 51, 60, 65, 110, 75, 80, 62, 53, 60, 55, 77, 55, 75, 65, 56, 67, 67, 55, 52, 95, 69, 60, 80, 60, 76, 55, 55, 49, 78, 80, 72, 70, 89, 62, 80, 65, 53, 74, 82, 67, 62, 52, 102, 69, 61, 60, 110, 67, 50, 49, 68, 70, 78, 65, 60, 75, 74, 70, 53, 88, 70, 50, 68, 75, 70, 78, 63, 77, 73, 63, 65, 78, 86), .Dim = c(227, 2)) groegewicht<-matrix(groegewicht,ncol=2) dimnames(groegewicht)[2]<-list(c("groesse","gewicht")) ################################################################################################ ### QF #### ### Datensatz mit uniform verteilte Zufallszahlen x (1.Spalte) und deren Quadrate (2.Spalte) #### ################################################################################################# x<-runif(1000,-1,1) y<-x^2 QF<-cbind(x,y) ############################### ### Datensatz SP50 #### ############################### sp50<-c(7,5,8,8,7,7,1,5,1,1) ################################## ###Datensatz lotto #### ################################## lotto<-c(13, 12, 34, 30, 31, 29, 27, 26, 47, 10, 26, 34, 38, 37, 29, 23, 18, 26, 14, 26, 30, 41, 6, 26, 42, 25, 32, 46, 19, 18, 45, 43, 22, 36, 36, 23, 25, 37, 44, 47, 48, 38, 27, 40, 10, 5, 36, 49, 42, 42, 31, 9, 33, 32, 41, 17, 38, 29, 37, 16, 15, 32, 17, 49, 23, 20, 6, 2, 12, 31, 1, 15, 36, 2, 3, 18, 47, 2, 39, 35, 18, 31, 15, 28, 24, 4, 7, 21, 10, 23, 26, 41, 42, 9, 48, 13, 3, 36, 27, 27, 24, 25, 21, 9, 49, 35, 22, 49, 24, 20, 23, 46, 45, 27, 33, 46, 36, 19, 30, 7, 34, 30, 36, 19, 24, 11, 18, 39, 30, 44, 16, 27, 1, 31, 2, 49, 37, 25, 34, 46, 17, 9, 28, 19, 4, 42, 46, 14, 1, 18, 45, 47, 33, 20, 46, 4, 33, 46, 33, 47, 46, 22, 22, 11, 28, 11, 6, 44, 41, 46, 2, 28, 25, 13, 11, 18, 33, 11, 14, 49, 49, 23, 2, 16, 21, 30, 44, 49, 28, 8, 10, 30, 42, 34, 2, 35, 9, 31, 24, 26, 31, 2, 36, 8, 15, 48, 1, 15, 39, 19, 39, 12, 20, 29, 15, 4, 2, 5, 40, 31, 9, 33, 14, 45, 30, 48, 10, 12, 12, 34, 28, 26, 4, 47, 7, 17, 17, 45, 28, 41, 28, 26, 32, 10, 24, 8, 23, 16, 22, 22, 32, 43, 14, 11, 31, 45, 46, 19, 17, 4, 38, 25, 5, 8, 19, 30, 36, 27, 22, 34, 46, 42, 15, 20, 10, 15, 18, 15, 41, 5, 26, 1, 24, 48, 6, 32, 20, 4, 30, 1, 27, 7, 7, 45, 15, 47, 47, 23, 37, 1, 2, 5, 12, 28, 9, 25, 18, 20, 13, 20, 7, 33, 1, 44, 31, 22, 9, 33, 44, 40, 27, 23, 5, 36, 9, 1, 12, 33, 37, 17, 29, 39, 32, 2, 21, 16, 27, 35, 10, 44, 42, 48, 17, 40, 27, 27, 33, 36, 23, 18, 17, 15, 9, 40, 4, 47, 19, 44, 48, 7, 47, 15, 40, 7, 32, 15, 1, 24, 18, 6, 4, 28, 29, 47, 6, 27, 24, 4, 14, 13, 48, 16, 11, 43, 13, 39, 41, 11, 10, 27, 23, 45, 2, 28, 11, 20, 5, 31, 44, 27, 35, 43, 40, 6, 30, 24, 8, 38, 19, 45, 4, 26, 26, 28, 14, 2, 39, 32, 3, 3, 34, 4, 28, 10, 15, 20, 9, 2, 5, 34, 8, 28, 30, 26, 29, 28, 21, 23, 26, 10, 2, 36, 1, 25, 37, 38, 49, 32, 5, 6, 49, 45, 22, 27, 37, 12, 47, 3, 31, 16, 41, 46, 45, 36, 36, 27, 18, 42, 35, 2, 1, 14, 22, 41, 24, 22, 17, 33, 36, 30, 16, 23, 35, 27, 46, 29, 29, 33, 46, 35, 18, 3, 39, 13, 46, 26, 2, 22, 34, 37, 47, 45, 31, 38, 47, 21, 3, 8, 47, 46, 19, 13, 32, 32, 21, 38, 35, 37, 42, 4, 11, 24, 36, 32, 26, 2, 43, 17, 42, 1, 32, 11, 5, 47, 5, 28, 49, 47, 39, 42, 44, 34, 10, 46, 38, 40, 21, 41, 15, 26, 34, 8, 9, 45, 37, 31, 6, 4, 17, 19, 36, 39, 5, 37, 38, 34, 38, 40, 33, 34, 14, 1, 16, 34, 4, 42, 35, 46, 27, 45, 43, 12, 29, 21, 32, 2, 4, 47, 4, 39, 11, 22, 12, 42, 47, 9, 21, 48, 48, 2, 48, 6, 19, 18, 49, 43, 39, 42, 30, 23, 16, 45, 49, 7, 4, 40, 14, 8, 23, 40, 22, 36, 21, 36, 35, 14, 45, 22, 9, 39, 41, 19, 3, 46, 20, 27, 29, 11, 14, 43, 16, 19, 25, 23, 6, 17, 23, 44, 43, 18, 7, 35, 42, 47, 11, 15, 21, 1, 9, 21, 24, 20, 11, 41, 24, 19, 46, 32, 6, 32, 42, 9, 39, 35, 34, 26, 22, 13, 27, 12, 40, 25, 45, 41, 27, 39, 36, 48, 8, 2, 3, 20, 37, 38, 35, 24, 15, 20, 21, 42, 1, 9, 41, 35, 15, 43, 2, 25, 34, 3, 12, 29, 45, 24, 20, 3, 22, 26, 32, 26, 7, 22, 14, 33, 4, 40, 22, 5, 39, 29, 2, 8, 4, 32, 10, 4, 49, 32, 34, 10, 15, 29, 24, 13, 45, 48, 38, 41, 46, 31, 16, 14, 6, 38, 34, 38, 32, 36, 12, 12, 5, 39, 42, 33, 47, 1, 21, 19, 49, 30, 25, 22, 41, 27, 9, 1, 17, 7, 15, 46, 46, 47, 20, 39, 40, 19, 24, 2, 43, 12, 41, 10, 21, 17, 42, 8, 30, 2, 12, 49, 21, 24, 40, 40, 20, 31, 3, 46, 14, 38, 12, 39, 13, 44, 6, 6, 39, 44, 16, 19, 41, 21, 30, 48, 31, 36, 17, 12, 36, 31, 18, 16, 25, 7, 45, 41, 11, 42, 43, 49, 26, 30, 16, 27, 39, 30, 19, 29, 21, 35, 1, 44, 28, 48, 41, 20, 19, 1, 26, 23, 14, 25, 6, 34, 43, 19, 23, 37, 16, 29, 2, 29, 24, 18, 35, 12, 3, 26, 20, 29, 6, 30, 37, 43, 40, 9, 49, 17, 19, 18, 22, 27, 45, 39, 12, 28, 36, 25, 19, 13, 41, 3, 1, 26, 13, 43, 8, 19, 49, 21, 39, 25, 11, 48, 47, 26, 31, 1, 46, 25, 15, 9, 9, 13, 26, 43, 18, 24, 41, 31, 17, 39, 5, 45, 46, 49, 40, 35, 36, 46, 8, 15, 17, 19, 41, 24, 20, 21, 33, 31, 20, 17, 22, 44, 12, 1, 14, 26, 8, 49, 30, 31, 45, 37, 21, 39, 41, 27, 12, 19, 41, 48, 41, 36, 24, 20, 13, 1, 35, 2, 20, 12, 10, 47, 36, 31, 3, 13, 17, 46, 16, 22, 31, 46, 45, 32, 22, 41, 40, 14, 48, 47, 42, 41, 13, 33, 23, 26, 7, 49, 1, 38, 23, 42, 24, 29, 10, 45, 33, 27, 23, 27, 10, 17, 38, 31, 39, 31, 1, 3, 26, 47, 48, 36, 33, 17, 31, 8, 7, 35, 44, 16, 35, 8, 30, 32, 3, 12, 13, 16, 19, 22, 39, 37, 13, 21, 28, 9, 22, 24, 3, 13, 17, 30, 10, 12, 32, 29, 40, 21, 41, 21, 29, 28, 45, 37, 12, 20, 5, 23, 24, 15, 6, 38, 25, 43, 40, 2, 11, 8, 17, 49, 32, 46, 39, 19, 47, 15, 38, 3, 45, 7, 18, 38, 32, 23, 16, 23, 31, 16, 16, 2, 23, 23, 31, 34, 40, 9, 31, 36, 18, 49, 48, 43, 8, 5, 31, 7, 12, 11, 32, 29, 20, 34, 3, 44, 24, 40, 36, 21, 13, 22, 29, 40, 1, 13, 45, 24, 43, 48, 28, 19, 18, 35, 42, 13, 7, 12, 23, 29, 38, 34, 17, 18, 37, 2, 23, 1, 35, 16, 10, 16, 28, 16, 42, 35, 7, 8, 44, 35, 3, 7, 23, 43, 24, 38, 41, 4, 47, 49, 33, 33, 17, 3, 26, 2, 38, 4, 37, 38, 35, 30, 13, 18, 38, 3, 35, 3, 47, 46, 32, 35, 37, 8, 32, 26, 29, 39, 32, 14, 32, 21, 45, 42, 9, 27, 25, 23, 38, 35, 32, 32, 33, 48, 17, 25, 30, 37, 8, 6, 32, 40, 42, 30, 43, 20, 27, 10, 37, 39, 23, 18, 11, 22, 12, 10, 49, 40, 26, 28, 15, 14, 23, 7, 35, 49, 30, 18, 27, 37, 5, 26, 40, 14, 41, 19, 40, 36, 13, 10, 13, 9, 14, 21, 38, 33, 45, 47, 11, 24, 32, 1, 32, 49, 39, 34, 8, 17, 6, 36, 34, 32, 21, 10, 35, 31, 40, 26, 15, 21, 30, 25, 14, 18, 6, 43, 19, 27, 34, 10, 11, 31, 34, 44, 22, 7, 8, 3, 23, 11, 37, 37, 14, 40, 27, 35, 30, 5, 33, 10, 34, 21, 35, 4, 15, 49, 48, 4, 17, 15, 2, 25, 30, 36, 33, 42, 38, 37, 3, 10, 37, 31, 14, 4, 47, 40, 23, 6, 2, 46, 19, 8, 31, 14, 39, 17, 47, 24, 25, 14, 47, 26, 5, 13, 38, 3, 24, 14, 10, 33, 3, 12, 1, 7, 16, 46, 39, 5, 18, 49, 17, 6, 41, 28, 1, 21, 26, 3, 18, 47, 45, 38, 35, 20, 48, 22, 27, 27, 46, 20, 48, 5, 4, 38, 10, 38, 17, 12, 36, 18, 1, 37, 42, 46, 40, 6, 30, 38, 6, 44, 32, 9, 9, 46, 48, 5, 24, 32, 37, 3, 49, 47, 41, 49, 18, 24, 31, 25, 23, 1, 27, 7, 30, 46, 47, 27, 16, 2, 49, 28, 7, 31, 45, 22, 33, 24, 31, 37, 49, 41, 1, 32, 28, 45, 15, 31, 43, 20, 37, 18, 7, 47, 13, 35, 23, 41, 39, 25, 43, 46, 40, 16, 18, 37, 11, 1, 3, 40, 4, 31, 38, 5, 47, 20, 9, 33, 4, 11, 7, 13, 33, 36, 26, 18, 43, 21, 39, 49, 38, 10, 6, 8, 32, 14, 13, 42, 37, 36, 42, 26, 40, 43, 39, 32, 45, 33, 30, 45, 16, 9, 8, 10, 3, 2, 20, 38, 13, 5, 30, 1, 18, 35, 24, 34, 38, 35, 13, 28, 42, 3, 1, 39, 22, 23, 17, 36, 37, 46, 31, 3, 24, 6, 30, 17, 41, 42, 43, 42, 5, 3, 45, 47, 21, 33, 8, 37, 5, 5, 12, 13, 18, 49, 3, 2, 10, 6, 27, 6, 8, 28, 32, 1, 31, 6, 8, 17, 9, 22, 5, 14, 15, 8, 23, 12, 18, 9, 15, 15, 28, 7, 24, 31, 16, 40, 26, 31, 24, 31, 29, 15, 49, 18, 47, 15, 37, 36, 37, 23, 47, 26, 44, 36, 15, 24, 25, 27, 4, 25, 46, 48, 19, 31, 32, 25, 28, 45, 20, 45, 35, 17, 7, 48, 9, 21, 30, 20, 44, 34, 14, 38, 12, 25, 30, 44, 30, 37, 11, 19, 44, 22, 43, 11, 32, 10, 43, 12, 9, 33, 31, 5, 22, 41, 2, 20, 35, 37, 26, 19, 19, 41, 46, 40, 23, 44, 22, 17, 17, 20, 19, 21, 8, 8, 43, 9, 20, 17, 26, 24, 11, 42, 29, 48, 1, 49, 26, 35, 40, 17, 19, 43, 38, 16, 14, 20, 22, 44, 35, 6, 41, 31, 22, 25, 26, 36, 21, 27, 6, 41, 42, 21, 2, 38, 12, 3, 42, 11, 14, 1, 25, 42, 38, 6, 35, 4, 37, 8, 21, 27, 48, 33, 42, 46, 2, 31, 9, 49, 44, 37, 8, 12, 29, 49, 7, 12, 45, 12, 7, 43, 3, 42, 4, 26, 20, 20, 19, 3, 46, 11, 36, 17, 36, 28, 43, 37, 20, 37, 30, 36, 37, 16, 20, 29, 24, 38, 22, 1, 13, 43, 25, 33, 12, 49, 15, 33, 34, 40, 40, 13, 17, 2, 8, 47, 33, 34, 11, 5, 2, 21, 49, 37, 5, 11, 31, 17, 46, 19, 22, 46, 38, 40, 4, 34, 32, 5, 3, 19, 1, 12, 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25, 39, 27, 25, 10, 37, 4, 45, 7, 38, 15, 21, 39, 38, 38, 7, 6, 3, 40, 25, 15, 16, 6, 19, 23, 6, 48, 23, 25, 5, 14, 28, 29, 7, 48, 18, 14, 38, 26, 24, 30, 9, 38, 4, 11, 9, 44, 2, 21, 16, 16, 44, 13, 10, 40, 29, 47, 35, 36, 43, 47, 2, 15, 21, 1, 14, 14, 42, 31, 2, 19, 26, 19, 24, 1, 40, 45, 49, 25, 36, 4, 41, 27, 44, 26, 4, 19, 12, 21, 46, 16, 49, 1, 38, 27, 46, 29, 37, 38, 46, 12, 2, 18, 49, 10, 34, 24, 49, 22, 37, 3, 10, 32, 16, 39, 44, 28, 26, 48, 45, 49, 40, 47, 6, 22, 31, 46, 9, 21, 4, 23, 41, 36, 23, 22, 29, 4, 18, 32, 13, 45, 42, 40, 17, 18, 3, 30, 42, 4, 7, 15, 33, 12, 39, 41, 23, 47, 49, 45, 34, 5, 24, 19, 4, 18, 29, 33, 6, 43, 29, 14, 15, 40, 49, 8, 46, 8, 6, 20, 35, 5, 3, 43, 14, 42, 9, 10, 26, 37, 17, 3, 28, 23, 8, 30, 8, 10, 26, 28, 48, 12, 1, 13, 20, 16, 49, 39, 38, 1, 26, 21, 39, 24, 7, 24, 34, 32, 20, 20, 3, 2, 25, 37, 34, 36, 45, 2, 22, 48, 15, 14, 30, 31, 25, 15, 2, 39, 40, 32, 47, 22, 47, 23, 38, 6, 15, 20, 10, 44, 16, 3, 49, 28, 21, 7, 27, 27, 21, 12, 38, 47, 30, 23, 24, 36, 16, 3, 24, 13, 42, 39, 29, 29, 28, 19, 49, 45, 9, 46, 45, 37, 30, 6, 47, 25, 4, 14, 3, 41, 23, 11, 26, 22, 19, 38, 18, 25, 36, 27, 25, 49, 33, 30, 19, 9, 9, 9, 26, 3, 17, 49, 46, 3, 12, 40, 5, 14, 31, 44, 6, 37, 21, 16, 4, 46, 24, 32, 5, 29, 25, 46, 11, 49, 29, 13, 32, 46, 10, 31, 40, 13, 30, 4, 42, 10, 5, 1, 19, 20, 46, 44, 18, 25, 33, 35, 47, 19, 14, 5, 12, 27, 28, 5, 26, 20, 29, 16, 11, 11, 9, 47, 9, 34, 22, 16, 10, 11, 25, 3, 3, 28, 25, 25, 36, 30, 24, 2, 16, 9, 37, 10, 20, 10, 8, 22, 44, 34, 45, 39, 41, 34, 17, 41, 9, 45, 29, 3, 18, 40, 27, 24, 2, 42, 42, 2, 34, 32, 35, 36, 48, 37, 11, 27, 7, 38, 1, 8, 10, 34, 47, 46, 16, 44, 7, 42, 15, 43, 26, 49, 46, 26, 40, 36, 43, 11, 9, 45, 13, 25, 34, 21, 16, 18, 7, 15, 26, 5, 45, 8, 29, 28, 16, 2, 10, 48, 27, 23, 15, 7, 46, 36, 23, 4, 49, 5, 26, 22, 15, 40, 46, 40, 23, 10, 39, 35, 13, 12, 11, 10, 5, 1, 20, 18, 2, 17, 9, 44, 42, 38, 7, 43, 20, 7, 6, 37, 6, 35, 39, 45, 43, 41, 17, 1, 9, 16, 44, 45, 4, 48, 5, 45, 17, 28, 12, 32, 36, 15, 16, 18, 24, 19, 48, 22, 1, 11, 8, 20, 31, 8, 9, 5, 19, 18, 25, 47, 17, 30, 13, 16, 46, 9, 27, 43, 17, 15, 24, 39, 27, 26, 26, 5, 25, 10, 9, 47, 5, 25, 15, 15, 38, 3, 27, 43, 28, 25, 12, 11, 23, 48, 29, 49, 37, 7, 21, 13, 1, 31, 41, 36, 47, 8, 14, 31, 29, 29, 45, 48, 12, 22, 18, 29, 34, 10, 21, 47, 19, 28, 46, 47, 21, 5, 39, 44, 7, 18, 20, 23, 30, 29, 40, 23, 42, 16, 7, 23, 30, 14, 34, 2, 1, 48, 4, 11, 5, 10, 24, 2, 20, 25, 10, 48, 30, 1, 20, 21, 28, 8, 12, 25, 1, 36, 16, 11, 35, 11, 40, 39, 37, 18, 37, 12, 22, 5, 18, 14, 12, 5, 1, 48, 35, 13, 21, 44, 38, 21, 46, 8, 21, 27, 1, 4, 33, 44, 20, 44, 25, 42, 14, 47, 30, 6, 13, 38, 31, 25, 44, 9, 28, 42, 9, 30, 43, 19, 3, 48, 27, 29, 45, 7, 32, 46, 15, 4, 18, 38, 42, 20, 35, 38, 36, 21, 31, 14, 33, 41, 46, 8, 14, 9, 10, 19, 13, 6, 2, 19, 15, 19, 33, 37, 9, 43, 48, 38, 16, 15, 3, 1, 17, 2, 41, 15, 16, 3, 36, 14, 7, 36, 28, 47, 22, 23, 14, 11, 32, 9, 33, 2, 31, 11, 34, 10, 45, 37, 2, 4, 26, 10, 46, 21, 45, 19, 6, 13, 11, 2, 5, 44, 12, 12, 22, 49, 49, 13, 49, 45, 46, 37, 38, 2, 31, 17, 37, 37, 40, 20, 31, 20, 39, 23, 24, 41, 1, 33, 14, 45, 36, 22, 46, 3, 11, 1, 32, 45, 28, 24, 42, 5, 25, 2, 35, 4, 2, 20, 48, 24, 49, 26, 45, 37, 16, 48, 34, 38, 44, 5, 46, 38, 15, 15, 12, 23, 17, 30, 33, 32, 29, 48, 33, 11, 14, 6, 13, 14, 36, 6, 6, 1, 42, 36, 3, 37, 8, 23, 39, 6, 39, 47, 27, 37, 5, 22, 29, 8, 32, 34, 42, 45, 37, 32, 10, 13, 20, 25, 35, 41, 46, 11, 43, 46, 27, 29, 28, 45, 30, 34, 21, 6, 19, 46, 19, 23, 15, 46, 5, 49, 14, 10, 43, 13, 22, 12, 18, 39, 2, 15, 11, 5, 23, 13, 4, 31, 17, 22, 33, 7, 46, 38, 23, 8, 46, 7, 5, 24, 12, 47, 11, 4, 19, 20, 42, 45, 18, 35, 4, 2, 46, 38, 12, 31, 42, 24, 44, 14, 6, 4, 31, 34, 30, 14, 43, 3, 35, 35, 40, 40, 2, 26, 40, 23, 35, 36, 43, 30, 11, 37, 28, 7, 39, 29, 14, 26, 32, 30, 45, 22, 25, 19, 15, 21, 24, 36, 38, 33, 37, 20, 31, 9, 35, 31, 8, 13, 36, 26, 9, 37, 36, 1, 12, 41, 19, 6, 39, 38, 48, 7, 16, 48, 11, 41, 5, 4, 17, 34, 8, 14, 4, 4, 49, 28, 2, 11, 8, 18, 13, 21, 47, 9, 32, 28, 23, 5, 21, 32, 44, 32, 3, 8, 48, 33, 18, 23, 2, 30, 15, 18, 37, 20, 38, 15, 46, 11, 21, 4, 38, 6, 26, 24, 3, 19, 42, 29, 40, 18, 26, 32, 35, 25, 27, 4, 22, 47, 23, 12, 5, 4, 35, 9, 7, 42, 46, 46, 32, 11, 25, 23, 25, 24, 15, 32, 18, 6, 37, 24, 35, 40, 37, 6, 43, 48, 8, 38, 19, 4, 22, 5, 43, 49, 38, 47, 37, 43, 43, 31, 36, 41, 32, 30, 25, 48, 42, 38, 43, 22, 37, 38, 7, 39, 7, 28, 45, 32, 17, 43, 36, 41, 33, 2, 18, 21, 29, 9, 48, 17, 47, 8, 36, 39, 18, 14, 47, 16, 37, 4, 11, 25, 43, 46, 35, 21, 30, 31, 31, 15, 22, 41, 49, 29, 36, 6, 46, 44, 24, 28, 16, 30, 18, 17, 45, 12, 36, 12, 30, 15, 24, 13, 49, 12, 28, 16, 48, 15, 34, 28, 49, 17, 21, 31, 7, 32, 1, 1, 2, 9, 4, 39, 23, 9, 6, 7, 10, 15, 9, 24, 22, 17, 1, 9, 22, 7, 30, 41, 35, 7, 8, 18, 26, 47, 41, 6, 13, 17, 9, 30, 14, 29, 37, 42, 27, 37, 12, 25, 1, 42, 26, 35, 2, 26, 27, 2, 44, 5, 13, 13, 37, 46, 21, 39, 24, 31, 7, 19, 11, 33, 32, 9, 24, 41, 14, 20, 38, 6, 46, 48, 39, 44, 29, 3, 25, 35, 40, 20, 7, 3, 27, 8, 24, 37, 14, 16, 9, 48, 38, 22, 7, 33, 48, 18, 14, 23, 2, 36, 6, 26, 19, 23, 18, 37, 44, 35, 31, 6, 27, 18, 32, 10, 20, 13, 26, 37, 26, 38, 1, 6, 18, 45, 30, 25, 7, 2, 9, 25, 16, 39, 5, 13, 4, 33, 42, 42, 37, 20, 46, 10, 3, 36, 20, 23, 39, 25, 48, 26, 15, 13, 7, 43, 19, 26, 8, 3, 25, 26, 47, 37, 20, 18, 25, 25, 20, 41, 18, 13, 25, 48, 39, 29, 21, 27, 8, 33, 41, 3, 46, 28, 18, 34, 37, 47, 49, 29, 29, 29, 45, 40, 16, 43, 24, 10, 42, 9, 7, 23, 39, 32, 14, 41, 39, 32, 46, 40, 10, 14, 24, 5, 30, 27, 13, 9, 27, 11, 49, 40, 26, 2, 33, 15, 8, 38, 8, 37, 14, 17, 2, 4, 23, 38, 23, 49, 42, 42, 40, 31, 35, 6, 10, 16, 16, 27, 45, 25, 31, 4, 26, 7, 48, 16, 49, 41, 42, 12, 12, 43, 48, 25, 5, 36, 11, 13, 24, 12, 31, 41, 2, 41, 35, 49, 44, 34, 3, 15, 27, 45, 34, 34, 38, 16, 36, 14, 31, 13, 38, 39, 48, 40, 26, 45, 29, 9, 1, 40, 4, 5, 38, 6, 19, 25, 11, 28, 48, 17, 19, 20, 45, 4, 32, 25, 41, 37, 49, 9, 15, 18, 34, 30, 8, 11, 26, 6, 34, 48, 3, 46, 18, 13, 31, 41, 34, 49, 15, 38, 44, 28, 29, 21, 19, 23, 47, 19, 19, 21, 12, 35, 6, 3, 3, 10, 34, 14, 9, 37, 46, 7, 25, 23, 30, 31, 32, 25, 30, 31, 48, 20, 32, 32, 49, 42, 38, 17, 45, 15, 25, 38, 40, 6, 32, 26, 40, 33, 24, 28, 36, 35, 24, 38, 27, 16, 32, 39, 28, 35, 39, 20, 45, 2, 48, 26, 33, 5, 17, 41, 6, 14, 43, 33, 40, 13, 7, 26, 6, 47, 12, 35, 32, 21, 23, 42, 48, 33, 9, 28, 36, 11, 7, 38) DreiVer1<-cbind(c(0.422397960324712, 0.47702271843427, 0.383637538170753, 0.0184630463831127, 0.115016676392406, 0.0416680132523644, 0.0191384089179337, 0.00812920885528097, 0.0383190710502554, 0.101579565834254, 0.111256310902536, 0.0685281252488494, 0.202248695298078, 0.129540913645178, 0.0664491265080869, 0.0545609943568707, 0.511756447304912, 0.181988402261379, 0.385453382862692, 0.48916718100471, 0.512496317525334, 0.456264712013141, 0.390917744098191, 0.062279838975519, 0.116418310906738, 0.047469365503639, 0.130367879755795, 0.145252988851609, 0.194971477418187, 0.253730357429924, 0.257694595484974, 0.348833579925780, 0.173287847569745, 0.41461133098412, 0.28631920738328, 0.232993582627716, 0.62471625950552, 0.0996522382833064, 0.0556286692632572, 0.0561177984811366, 0.0480572456623331, 0.123180271871388, 0.0431078668683767, 0.0107274088781595, 0.00119589546867329, 0.283436967425580, 0.0674109847284853, 0.0278653827495873, 0.0646740917116404, 0.794211338045907, 0.56017348137701, 0.584242378141651, 0.0472973593510687, 0.0398736983537674, 0.295955683633898, 0.0351241528987885, 0.252449185951593, 0.0523687105039767, 0.0161146667668887, 0.0390748202800751, 0.00787614197514443, 0.344670936448460, 0.0926254001446068, 0.183084282557792, 0.128794072754681, 0.246403431325200, 0.0207594224251807, 0.484490850915141, 0.128571520559490, 0.271763686454835, 0.0228831343352795, 0.0804112375094965, 0.0813425928513321, 0.369792151590052, 0.464156212116472, 0.446763235677905, 0.290656318126206, 0.172229230209234, 0.331126305816655, 0.0663113132119179, 0.100773508753628, 0.0752776739370222, 0.176756336159053, 0.528860587228961, 0.0228841263800859, 0.0402635515667498, 0.399916207028513, 0.227036102293971, 0.765699229719949, 0.154036442182615, 0.00254843777674367, 0.102310708723962, 0.693902335158905, 0.0126413853839040, 0.0883189894258976, 0.180174361077598, 0.388700577972417, 0.00102633908390999, 0.249561622544172, 0.0726559112779796 ),c(15.0259722865735, 18.3572258215177, 16.1405680656707, 21.4830274253361, 6.84397957458572, 10.2983370833291, 19.0522648048922, 8.05816123263659, 31.2897740059302, 10.7473547202492, 3.57592021388819, 9.75978019400037, 25.0890752278273, 30.1910778000131, 29.981163998059, 10.0407610751745, 3.69881030711759, 28.5696223511913, 7.89599876590863, 16.1578963066822, 15.2587395138375, 23.6371197757416, 11.2398132699891, 17.3659396226082, 16.4142146854206, 23.6384262365035, 11.4360935633280, 19.3698608951302, 13.7473643608828, 17.6355202817373, 1.95099775640914, 28.3520299097917, 4.14716978567617, 14.7462948674969, 11.4783981031502, 17.9305652558025, -3.09781948745495, 23.9658619134491, 21.3220880962720, 1.92909622049929, 26.7547652291715, 15.6706642053128, -3.18485623137209, 2.56955640411194, 23.4960796489590, -12.5485073103351, 20.9168810515983, 12.1070946534463, 18.8797937168703, 24.2616362605711, 25.3393730328735, 25.2930157312872, 11.6675516679676, 22.9861348598902, 10.8113859710769, 2.58823356289480, 12.2099505312039, 14.6277202250358, 28.3283757712605, 7.33567031212822, 17.5713818559751, 19.4292058279361, -7.94368170410396, -2.82674688253459, 18.9337743055647, 15.5190422526940, 15.5264746692058, 18.4700114585249, 20.8656676457778, 1.40451161150845, 11.7050263190307, -4.14204075495626, -4.50425216397405, 23.3233588590916, 6.20426758982214, 14.629315385978, 11.6460606170870, 2.9335577058265, 13.1957285318509, 28.1041780319289, 21.5637752011958, 17.3481764097642, 9.07766631706767, 21.5896023274046, 14.1713727740762, 1.37679838162832, 17.0768040047235, 11.0779899750465, 33.3335570357548, 8.58161658607597, 16.9314424070838, 35.7533060816715, 8.18828349909646, 16.0593026348892, 20.7256684647106, 12.8303850903635, 18.9523086786165, 27.5852979083634, 20.2392692955201, 11.5204948860979 ),c(1.66511286199709, 2.11361553123257, 4.56107183405983, 3.98036794172840, 7.59744935723206, 10.4394865027995, 7.23656806724716, 5.80772905864953, 6.94529640385313, 6.50759661944917, 5.77005470868034, 3.63974682162544, 12.6835784493452, 4.57917447967219, 11.5392554346811, 4.17114241442235, 12.3383042752899, 10.3016075563438, 4.84643752242097, 14.3098795058124, 7.66629594033265, 9.18616585584015, 9.10707100485404, 7.40863799246378, 2.57733610527976, 6.71382877127643, 4.65953485735696, 18.8621647908418, 2.02673408767123, 7.25082304402373, 7.17726782116888, 2.31994978074761, 4.65168482695693, 11.7865466197703, 3.22647587044417, 7.85659257543378, 12.7888338435221, 9.70596734048734, 9.59857808991073, 6.44181709206253, 10.1200937751089, 2.97035416093146, 10.0385197103496, 3.56824762791628, 5.60429164719811, 4.57075070705357, 8.05214918479159, 1.56179927265857, 4.96953210138977, 3.0137739175165, 3.26683272028820, 3.27817537011311, 18.8291637101266, 9.42381993633753, 3.95710346966193, 3.65702013583957, 1.89465976307306, 8.2054298308981, 0.590176298602967, 11.1165756311458, 4.00238220953494, 2.55872006057559, 8.99599817914762, 3.44271811724616, 5.37799118918434, 6.17094257656045, 11.3772163115669, 4.5972081006798, 7.16478858391115, 5.96953728793977, 4.2013728327147, 3.36015107092473, 3.31260174625871, 11.3649240347886, 4.42383699349577, 6.52432730147447, 10.4865412510431, 5.12496005244745, 7.38843077686514, 15.0363525326788, 14.6693540641721, 9.03179930479493, 15.2838521821913, 8.94932802856613, 7.14606882922812, 11.8584928519815, 4.97639903734474, 5.04450821642787, 12.0598422946167, 5.3216307053711, 3.72477388867798, 4.33395281231823, 5.30187361890414, 3.87696439966086, 5.40544378189723, 8.18963405797453, 11.6297899217661, 8.6009096527087, 3.61141263976630, 7.90114954978952)) DreiVer2<-cbind(c(0.0937488930299878, 0.139495056672933, 0.0346748752519488, 0.175469008405512, 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3.25579253733065, 9.35450897293236, 7.32249718917315, 3.22758307113636, 6.5871206708322, 17.2804901107791, 9.55949804598131, 7.11347821165326, 4.94000262982763, 7.12986771351575, 5.64057756965824, 2.36318188114121, 4.03007917570869, 2.88291526992308, 1.49026353082333, 5.23566566797071, 14.0761517728291, 4.67585185916735, 4.58976408754605, 3.73713970524437, 1.07394411251270, 2.50334605894322, 3.58901535549985, 13.6135740164525, 3.0505145341734, 7.72137804727692, 2.18447382206452, 2.83221980310305, 7.29150420058469, 3.37905424658775, 14.1688570947054, 6.21146027684116, 20.775631032269, 12.5548464183328, 0.85518162631887, 4.40347707346407, 4.94314422197521, 14.0316612493149, 8.47220554754182, 6.2093525052169, 7.6748683198741, 5.06816611758527, 12.0433587630453, 3.78040855746145, 9.06772195983608, 11.2819434795583, 7.47649463624162, 6.49655109863442, 2.95139096394618, 6.31146573320041, 3.96833777138267, 11.805363265766, 2.54491383199190, 10.7316903013745, 5.772665018164, 7.60551385031036, 5.94787440576949, 13.4014609990531, 13.2816782132443, 7.73389992742276, 5.9234811697691, 1.68480501231411, 2.91781077531111, 9.85751212816448, 7.53869602759864, 5.29161523416729, 7.06076483368974, 20.9685168161718, 7.40738205793368, 7.78804676282249, 6.77929411224476, 10.077784374342, 4.18285888354158, 5.94652399149118, 4.31634328678401, 3.47762105593315, 5.3242436850457, 5.84047933804421, 5.1336829513459, 24.5439319805346, 11.8608170367939, 9.46930455586197, 5.77351673677197, 7.2931941699705, 5.82016056182897, 15.4207355328985, 4.80743476290296, 9.94863704650517, 5.12338430242898, 16.3688896912693, 6.52754674104129, 1.86357232435388, 10.9847134919192, 5.98226169162396, 9.41988254407321, 12.1429443578058, 15.1433879517146, 14.872323955026, 6.41845969165003, 5.34481861346907, 12.6225302107239, 29.5157611620250, 5.86247385483423, 7.60718698292858, 3.54370574405895, 14.151735329211, 7.55422948521204, 7.03648445779652, 2.25255058765220, 15.1016430698638, 4.20098647359579, 13.9468475716433, 13.5531740435745, 1.80588262095458, 5.12928998694454, 5.11434637378379, 1.72255518147574, 3.77302179804583, 5.13715810293698, 8.2757242833779, 6.40177708013573, 3.33109207567345, 4.54626087567971, 6.81257980713157, 5.94381960172676, 10.8200464671455, 6.08867308000827, 7.61989558773517, 4.66267679223716, 10.5992370860406, 9.9302055578473, 9.16748351410144, 6.38553434852607, 6.28592625400542, 4.01806101295693, 2.502538129239, 7.33624298832544, 4.59159415987613, 5.93464100508142, 4.98130676354231, 7.62822527660636, 10.5375135316476, 9.07436299192907, 9.6986071844412, 14.3096872229064, 9.14266851392924, 8.9164926402248, 3.96408210587199, 8.33426619877214, 5.18367026781783, 17.6845713137306, 4.88530049514766, 11.4375080775339, 17.8231605144629, 4.19776925111791, 8.36001225052216, 9.5364137646935, 14.0744650381144, 14.67639516308, 5.6062770569464, 9.97974184267796, 9.15822184309252, 3.14474819006722, 3.40677406910176, 12.3309645748134, 5.09926141368774, 7.0905582091287, 6.54646299754346, 8.0715311167543, 9.16910957134914, 4.47407327068985, 2.73188649572931, 4.67681986373903, 3.30330175961286, 13.5623892533042, 7.42447164319943, 7.36374877616648, 7.31940078609495, 4.84731827390214, 4.91829705036024, 5.50056728589784, 7.50297084608046, 8.29888219296886, 4.84859391656472, 4.34094740293160, 12.3875463406153, 11.1077371298974, 8.8740448711274, 9.53068191425205, 3.47428719702125, 8.04463936576697, 4.40778584342791, 3.96812987516867, 6.46692777481746, 4.93270442452538, 5.02743516690524, 11.3078649780106, 0.66076657923927, 14.8554031603262, 8.40835975995486, 5.09484242608673, 3.25724075833388, 5.56094289304279, 9.61226208146603, 3.72455868004751, 5.88546061252442, 1.34483099440897, 5.66959950638026, 0.676642802539942, 4.01119673624283, 3.84628208955331, 5.32709236058717, 4.58820115180987, 3.69277515183949, 1.74367881499735, 17.0097052403451, 11.3228937992345, 8.43238473177002, 4.79651554841391, 4.1202867357277, 8.80136511734005, 4.97073981134671, 1.42988727805668, 9.38906925360606, 11.9267844065574, 4.40382329565413, 4.54480628066647, 2.84384249304579, 9.15913122340664, 4.24322905160979, 4.26660591933456, 12.5132231007358, 2.90449512280722, 4.19584165835053, 7.56412097039349, 5.50383924152335, 4.52429052857264, 2.08195418335683, 7.30595617866918, 4.85425372430956, 13.9798777067354, 8.13196884839968, 8.09778604526061, 7.06659315784476, 4.39327245990907, 7.28227554621236, 7.08225283732574, 4.82058875399037, 1.81513269032324, 8.4710083956372, 5.025771277378, 9.90913136630843, 7.80296701457678, 2.23573691163688, 7.07724528236983, 10.3756022452816, 6.77027542034263, 5.58121251581571, 2.64292814999956, 9.91970553586743, 9.09457177275335, 3.25406955019263, 2.89921645977929, 3.53300462514508, 4.72982738804401, 5.55921785773775, 3.7782114642618, 3.42801388865651, 2.50500702631471, 5.07570345988335, 14.8264646721391, 4.14670741599201, 7.23418169551814, 8.6764868240638, 25.8523865596457, 13.0616141157174, 1.93854902692677 )) gerste<-c(185, 162, 136, 157, 141, 130, 129, 176, 171, 190, 157, 147, 176, 126, 175, 134, 169, 189, 180, 128, 169, 205, 129, 117, 144, 125, 165, 170, 153, 186, 164, 123, 165, 203, 156, 182, 164, 176, 176, 150, 216, 134, 184, 203, 166, 155, 215, 190, 164, 204, 194, 148, 162, 146, 174, 185, 171, 181, 158, 147, 165, 157, 180, 165, 127, 186, 133, 170, 134, 177, 109, 169, 128, 152, 165, 139, 146, 144, 178, 188, 133, 128, 161, 160, 167, 156, 125, 162, 128, 103, 116, 87, 123, 143, 130, 119, 141, 174, 157, 168, 195, 180, 158, 139, 139, 168, 145, 166, 118, 171, 143, 132, 126, 171, 176, 115, 165, 148, 186, 157, 187, 174, 172, 191, 155, 169, 139, 144, 130, 146, 159, 164, 160, 122, 175, 156, 119, 135, 116, 134, 157, 182, 209, 136, 153, 160, 142, 179, 125, 149, 171, 186, 196, 175, 189, 214, 169, 166, 164, 195, 189, 108, 188, 149, 178, 171, 151, 192, 127, 148, 158, 174, 191, 134, 188, 248, 164, 206, 185, 192, 147, 178, 189, 141, 173, 187, 167, 128, 139, 152, 167, 131, 203, 231, 214, 177, 161, 194, 141, 161, 124, 130, 112, 122, 192, 155, 196, 179, 166, 156, 131, 179, 201, 122, 207, 189, 164, 131, 211, 172, 170, 140, 156, 199, 181, 181, 150, 184, 154, 200, 187, 169, 155, 107, 143, 145, 190, 176, 162, 123, 189, 194, 146, 22, 160, 107, 70, 84, 112, 162, 124, 156, 138, 101, 138, 141, 143, 135, 163, 183, 99, 118, 150, 151, 83, 136, 171, 191, 155, 164, 98, 134, 115, 168, 130, 111, 136, 129, 122, 120, 179, 172, 192, 171, 151, 142, 193, 174, 146, 180, 140, 137, 138, 194, 109, 120, 124, 126, 126, 147, 115, 148, 195, 154, 149, 139, 163, 118, 126, 127, 139, 174, 167, 175, 179, 172, 174, 167, 142, 169, 122, 163, 144, 147, 123, 160, 137, 161, 122, 101, 158, 103, 119, 164, 112, 57, 94, 106, 132, 122, 164, 142, 155, 147, 115, 143, 68, 184, 183, 167, 160, 138, 191, 133, 160, 156, 122, 111, 153, 148, 103, 131, 180, 142, 191, 175, 146, 181, 111, 110, 154, 176, 168, 175, 175, 146, 148, 167, 106, 123, 121, 154, 148, 91, 93, 74, 113, 79, 131, 119, 96, 80, 97, 198, 106, 107, 69, 86, 94, 129) Gewicht_m<-c(76, 71, 73, 68, 93, 65, 53, 75, 85, 83, 85, 75, 85, 67, 68, 82, 126, 83, 70, 72, 75, 78, 65, 76, 84, 90, 70, 84, 85, 58, 81, 85, 80, 90, 75, 74, 69, 68, 80, 66, 65, 90, 57, 92, 82, 66, 68, 90, 70, 67, 72, 63, 62, 87, 80, 82, 98, 65, 137, 66, 85, 82, 72, 81, 83, 62, 74, 82, 72, 72, 75, 74, 75, 87, 72, 75, 75, 86, 69, 75, 69, 74, 78, 66, 96, 110, 80, 62, 77, 65, 95, 69, 60, 80, 60, 80, 72, 70, 89, 62, 80, 65, 74, 82, 62, 102, 69, 61, 110, 67, 68, 78, 75, 74, 70, 88, 68, 75, 70, 78, 63, 77, 73, 65, 86) Gewicht_w<-c(48, 50, 65, 86, 73, 56, 65, 57, 53, 67, 78, 58, 50, 60, 56, 50, 52, 57, 57, 45, 65, 58, 55, 60, 53, 52, 63, 57, 62, 72, 58, 50, 65, 49, 60, 53, 58, 57, 50, 50, 100, 57, 65, 78, 70, 68, 43, 60, 50, 62, 68, 54, 68, 43, 57, 52, 60, 55, 65, 62, 64, 62, 60, 62, 59, 55, 55, 51, 60, 65, 53, 60, 55, 55, 75, 56, 67, 67, 55, 52, 76, 55, 55, 49, 78, 53, 67, 52, 60, 50, 49, 70, 65, 60, 53, 50, 63, 78) ##################################### ##Datensaz leo #### ##und Funktion Leo() #### ##################################### leo<-c(8804810,9166882,9286948,8855458,7091353,2923084,3962010,9048118,9322135,9444234, 9198770,7365556,2773922,3985565,9185580,9823344,10245704,9910162,7606304,3094485,4780219, 10093619,10182114,10332184,9806537,7855018,3338575,4897611,9113485,10206414,10342101, 9873709,8105652,3217839,5187866) leo<-round(leo/1000000,1) Leo<-function() { leo<-c(8804810,9166882,9286948,8855458,7091353,2923084,3962010,9048118,9322135,9444234, 9198770,7365556,2773922,3985565,9185580,9823344,10245704,9910162,7606304,3094485,4780219, 10093619,10182114,10332184,9806537,7855018,3338575,4897611,9113485,10206414,10342101, 9873709,8105652,3217839,5187866) leo<-round(leo/1000000,1) gridw<-function (xlo, xhi, xdels, xdell, ylo, yhi, ydels, ydell, cols = "grey75", coll = "grey50", lwds = 0.5, lwdl = 0.5, ...) { nxs <- ceiling((xhi - xlo)/xdels) nxl <- ceiling((xhi - xlo)/xdell) nys <- ceiling((yhi - ylo)/ydels) nyl <- ceiling((yhi - ylo)/ydell) segments(rep(xlo, nys), seq(ylo, yhi, ydels), rep(xhi, nys), seq(ylo, yhi, ydels), col = cols, lwd = lwds) segments(seq(xlo, xhi, xdels), rep(ylo, nxs), seq(xlo, xhi, xdels), rep(yhi, nxs), col = cols, lwd = lwds) segments(rep(xlo, nyl), seq(ylo, yhi, ydell), rep(xhi, nyl), seq(ylo, yhi, ydell), col = coll, lwd = lwdl) segments(seq(xlo, xhi, xdell), rep(ylo, nxl), seq(xlo, xhi, xdell), rep(yhi, nxl), col = coll, lwd = lwdl) } par(mfrow=c(1,1),mar=c(4,6,3,1),mgp=c(2,0.6,0),lab=c(8,3,8),xaxs="i",yaxs="i",las=1) Woche<-c("Mo","Di","Mi","Do","Fr","Sa","So") xlo=0 xhi=36 ylo=0 yhi=12 x<-seq(xlo,xhi,length=1000) y<-seq(ylo,yhi,length=1000) plot(x,y,type="n",axes=F,cex.lab=1.5,cex.axis=1.2,xlab = "Tag", ylab="Anfragen in Mio.") axis(1,pos=ylo,at=seq(xlo,xhi,by=1),labels =c(" ",rep(Woche,5)," "), cex.axis=0.8) axis(2,pos=xlo,at=seq(ylo,yhi,by=1),cex.axis=1.2) gridw(xlo=xlo, xhi=xhi, xdels=1, xdell=7, ylo=ylo, yhi=yhi, ydels=0.1, ydell=1,lwds = 0.5, lwdl = 1) par(xpd=T) segments(xlo,yhi,xhi,yhi) segments(xlo,ylo,xhi,ylo) par(xpd=FALSE) abline(h=0,v=0,lwd=2) abline(h=0,v=0,lwd=2) par(mfrow=c(1,1),mar=c(4,6,3,1),mgp=c(2,0.6,0),lab=c(8,3,8),xaxs="i",yaxs="i",las=1) lines(1:35,leo,type="o",lwd=2) } ################ ### muenze.fun ### R-Funktion / Pfad der relativen Haeufigkeiten beim Muenzwurf ################ muenze.fun<-function (n, prob = 0.5) { stichpr <- sample(c(0, 1), size = n, repl = T, prob = c(1 - prob, prob)) plot(1:n, cumsum(stichpr)/1:n, type = "l", ylim = c(0, 1), main = "Pfad der relativen Häufigkeiten", xlab = "Anzahl Würfe", ylab = "relative Häufigkeit", col = 2, lwd = 2) abline(h = prob) } ################################################################## ##Aufg. 1 ##### ##Datensatz ProKopf und die benoetigten R-Befehle ##### ################################################################## BIP<-c(32.811,34.721,24.482,20.665,39.758,50.504,35.638,20.294,25.845,29.146,25.827, 28.777,21.873,20.996,25.472,20.883) Einkommen<-c(19.261,18.775,14.797,14.634,19.933,22.908,18.658,13.953,17.105,18.724,17.101,17.138,14.599,14.005,16.920,14.152) Land<-c("BW","BY","BE","BR","HB","HH","HE","MV","NI","NW","RP","SL", "SN","ST","SH","TH") ProKopf<-cbind(BIP,Einkommen) dimnames(ProKopf)[1]<-list(Land) ########################## ##Datensatz raucher + inc.emp ### ########################## raucher<-c(26,44,241,264,41,75,142,127,128,161,274,305,563,167,243,200) raucher<-matrix(raucher,ncol=4,byrow=T) dimnames(raucher)[2]<-list(c("12-15","16-17","18-21","22-25")) dimnames(raucher)[1]<-list(c("Staendiger Raucher","Gelegenheitsraucher","Nichtraucher","Nieraucher")) inc.emp<-c(7,17,34,30,10,17,23,17,14,21,36,33,5,17,20,16,4,14,44,24) inc.emp<-matrix(inc.emp,ncol=4,byrow=T) dimnames(inc.emp)[2]<-list(c("< 0%","0%","0-20%",">20%")) dimnames(inc.emp)[1]<-list(c("0","1","2-4","5-9",">9")) ############################################# ##Datensatz Wetten #### ##und die benoetigten R-Befehle #### ############################################# Wetten<-c(14.92,17.56,18.84,17.63,21.12,20.69,20.84,17.64,18.23,18.67,15.89, 18.65,14.67,14.68,13.64,15.49,15.39,14.91,15.61,13.78,15.07,13.89,14.72,14.06,13.34,12.98, 12.08) Wetten <- ts(Wetten, start=1981, freq=1) wuerfel.fun<-function(n1,n2) { rel.hf1<-table(sample(c(1,2,3,4,5,6),n1,replace=T))/n1 rel.hf2<-table(sample(c(1,2,3,4,5,6),n2,replace=T))/n2 par(mfrow=c(2,1)) barplot(rel.hf1,ylim=c(0,max(rel.hf1)),xlab="Augenzahl",ylab="relative Häufigkeit",main="kleinere Stichprobe") abline(h=1/6,col=2,lwd=2) barplot(rel.hf2,ylim=c(0,max(rel.hf1)),xlab="Augenzahl",ylab="relative Häufigkeit",main="größere Stichprobe") abline(h=1/6,col=2,lwd=2) } Würfelsumme<-function(n){Wurf1<-sample(c(1,2,3,4,5,6),n,replace=T);Wurf2<-sample(c(1,2,3,4,5,6),n,replace=T);Summe<-Wurf1+Wurf2;lines(1:n,cumsum(Summe)/1:n)}