entregar
Part 1
df <- read.csv(file ="LungCapData.txt",header = T,sep = "\t")
str(df)## 'data.frame': 725 obs. of 6 variables:
## $ LungCap : num 6.47 10.12 9.55 11.12 4.8 ...
## $ Age : int 6 18 16 14 5 11 8 11 15 11 ...
## $ Height : num 62.1 74.7 69.7 71 56.9 58.7 63.3 70.4 70.5 59.2 ...
## $ Smoke : Factor w/ 2 levels "no","yes": 1 2 1 1 1 1 1 1 1 1 ...
## $ Gender : Factor w/ 2 levels "female","male": 2 1 1 2 2 1 2 2 2 2 ...
## $ Caesarean: Factor w/ 2 levels "no","yes": 1 1 2 1 1 1 2 1 1 1 ...LungCapData <- df
mean(LungCapData$LungCap)## [1] 7.863148mean(LungCapData$Age)## [1] 12.3269mean(LungCapData$Height)## [1] 64.83628summary(df)## LungCap Age Height Smoke Gender
## Min. : 0.507 Min. : 3.00 Min. :45.30 no :648 female:358
## 1st Qu.: 6.150 1st Qu.: 9.00 1st Qu.:59.90 yes: 77 male :367
## Median : 8.000 Median :13.00 Median :65.40
## Mean : 7.863 Mean :12.33 Mean :64.84
## 3rd Qu.: 9.800 3rd Qu.:15.00 3rd Qu.:70.30
## Max. :14.675 Max. :19.00 Max. :81.80
## Caesarean
## no :561
## yes:164
##
##
##
## IQR(df$LungCap)## [1] 3.65IQR(df$Age)## [1] 6IQR(df$Height)## [1] 10.4Calculate the median
LungCapData <- df
median(LungCapData$LungCap)## [1] 8median(LungCapData$Age)## [1] 13median(LungCapData$Height)## [1] 65.4Calculate the Maximum
LungCapData <- df
max(LungCapData$LungCap)## [1] 14.675max(LungCapData$Age)## [1] 19max(LungCapData$Height)## [1] 81.8Calculate the Minimum
min(LungCapData$LungCap)## [1] 0.507min(LungCapData$Age)## [1] 3min(LungCapData$Height)## [1] 45.3summary(LungCapData)## LungCap Age Height Smoke Gender
## Min. : 0.507 Min. : 3.00 Min. :45.30 no :648 female:358
## 1st Qu.: 6.150 1st Qu.: 9.00 1st Qu.:59.90 yes: 77 male :367
## Median : 8.000 Median :13.00 Median :65.40
## Mean : 7.863 Mean :12.33 Mean :64.84
## 3rd Qu.: 9.800 3rd Qu.:15.00 3rd Qu.:70.30
## Max. :14.675 Max. :19.00 Max. :81.80
## Caesarean
## no :561
## yes:164
##
##
##
## Now we make the histograms of our variables
LungCap <- LungCapData$LungCap
hist(LungCap,col = "red",main ="histogram de Lung Cap")
Age <- LungCapData$Age
hist(Age,col = "blue",main ="histogram de Age")
Height <- LungCapData$Height
hist(Height,col = "yellow",main ="histogram de Height")
# Also, we are going to compute boxplots
library(ggplot2)
?boxplot
boxplot(LungCap,col = "Red")
boxplot(Age,col = "blue")
boxplot(Height,col = "yellow")
Taulas variables qualitatives
library(ggplot2)
Gender.freq <- table(df$Gender)
Gender.freq##
## female male
## 358 367Smoke.freq <- table(df$Smoke)
Smoke.freq##
## no yes
## 648 77Caesarean.freq <- table(df$Caesarean)
Caesarean.freq##
## no yes
## 561 164Age.freq <- table(df$Age)Histogramas
library(ggplot2)
hist(Gender.freq,col = "Green")
hist(Smoke.freq,col ="Blue")
hist(Caesarean.freq,col = "Yellow")
# Blox-Plot
library(ggplot2)
ggplot(df,aes(df$Smoke,df$Gender))+geom_boxplot()
# two quantitative variables
ggplot(df,aes(df$Age,df$Height))+geom_boxplot()## Warning: Continuous x aesthetic -- did you forget aes(group=...)?
summary(df$Height,df$Age)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 45.30 59.90 65.40 64.84 70.30 81.80qualitative and quantitative
summary(df$Age,df$Smoke)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 3.00 9.00 13.00 12.33 15.00 19.00barplot(Smoke.freq,Age.freq)
#Part 2 #f abs
a <- table(df$LungCap)
b <- table(df$Age)
c <- table(df$Height)
d <- table(df$Smoke)
e <- table(df$Gender)
f <- table(df$Caesarean)f relativa
g <- table(df$LungCap)/725
h <- table(df$Age)/725
i <- table(df$Height)/725
j <- table(df$Smoke)/725
k <- table(df$Gender)/725
l <- table(df$Caesarean)/725Frequencies absolutas acumulada
cumsum(a)## 0.507 1.025 1.125 1.175 1.325 1.45 1.575 1.625 1.675 1.775
## 1 2 3 4 5 6 7 8 9 10
## 1.85 1.9 1.925 1.95 2 2.025 2.25 2.375 2.475 2.55
## 11 12 13 14 15 16 19 20 21 22
## 2.625 2.65 2.725 2.825 2.85 2.875 2.925 2.95 3.025 3.1
## 24 26 29 30 31 34 36 37 38 40
## 3.175 3.225 3.25 3.4 3.425 3.45 3.6 3.625 3.65 3.675
## 42 43 44 45 48 49 50 51 52 54
## 3.7 3.75 3.825 3.85 3.9 3.925 3.975 4.075 4.125 4.15
## 56 57 58 59 62 64 66 67 68 69
## 4.2 4.25 4.325 4.35 4.425 4.45 4.475 4.5 4.525 4.55
## 71 74 77 78 81 83 85 86 87 88
## 4.575 4.625 4.65 4.7 4.725 4.775 4.8 4.825 4.85 4.875
## 89 92 93 95 98 99 100 101 103 104
## 4.9 4.95 4.975 5.025 5.05 5.075 5.125 5.15 5.175 5.2
## 106 107 110 113 116 117 118 121 122 123
## 5.225 5.25 5.275 5.3 5.325 5.35 5.375 5.425 5.475 5.5
## 125 127 128 129 131 132 135 136 137 139
## 5.55 5.575 5.6 5.625 5.65 5.675 5.7 5.725 5.775 5.825
## 142 143 144 145 148 149 150 152 153 154
## 5.85 5.875 5.95 6 6.05 6.075 6.1 6.125 6.15 6.175
## 158 162 165 167 171 174 177 180 183 186
## 6.2 6.225 6.25 6.275 6.3 6.325 6.375 6.4 6.425 6.45
## 189 193 194 195 197 199 200 201 202 209
## 6.475 6.5 6.525 6.55 6.575 6.6 6.625 6.65 6.675 6.7
## 212 214 216 219 223 224 226 228 229 234
## 6.725 6.75 6.775 6.8 6.825 6.85 6.9 6.925 6.95 6.975
## 238 240 241 243 246 250 253 255 259 261
## 7 7.025 7.05 7.075 7.1 7.125 7.15 7.175 7.2 7.225
## 263 265 267 268 270 271 272 273 274 276
## 7.25 7.275 7.3 7.325 7.35 7.375 7.4 7.425 7.45 7.475
## 278 282 284 288 293 296 300 302 305 309
## 7.5 7.55 7.575 7.625 7.65 7.675 7.7 7.725 7.75 7.775
## 310 316 318 321 324 326 329 330 332 333
## 7.8 7.825 7.85 7.875 7.9 7.925 7.95 7.975 8 8.025
## 335 342 345 347 350 355 358 360 367 371
## 8.05 8.075 8.1 8.125 8.175 8.2 8.225 8.25 8.275 8.3
## 372 374 375 379 380 383 387 390 393 394
## 8.325 8.35 8.375 8.425 8.45 8.475 8.5 8.525 8.55 8.575
## 396 404 405 410 411 413 418 419 422 424
## 8.6 8.625 8.65 8.675 8.7 8.725 8.775 8.8 8.825 8.85
## 430 436 438 439 442 446 453 456 459 462
## 8.875 8.9 8.925 8.975 9 9.025 9.05 9.1 9.125 9.15
## 464 466 467 472 475 479 482 487 488 490
## 9.175 9.2 9.225 9.275 9.3 9.325 9.35 9.375 9.4 9.45
## 493 496 498 501 502 505 506 509 510 512
## 9.475 9.5 9.525 9.55 9.575 9.6 9.625 9.65 9.675 9.7
## 516 517 520 523 524 525 528 529 534 536
## 9.725 9.75 9.8 9.825 9.85 9.875 9.9 9.925 9.95 9.975
## 539 542 544 548 551 553 555 558 560 561
## 10 10.025 10.05 10.1 10.125 10.175 10.2 10.25 10.275 10.3
## 562 566 569 572 574 576 581 582 584 586
## 10.325 10.35 10.375 10.4 10.425 10.45 10.475 10.5 10.525 10.55
## 587 589 590 594 596 599 603 605 606 607
## 10.575 10.6 10.625 10.65 10.675 10.7 10.725 10.75 10.775 10.8
## 608 612 613 615 617 621 624 625 627 628
## 10.825 10.85 10.875 10.9 10.925 10.95 10.975 11 11.025 11.05
## 630 631 633 635 638 639 641 642 644 645
## 11.075 11.125 11.175 11.225 11.275 11.3 11.325 11.35 11.4 11.5
## 649 651 652 657 658 659 661 662 664 667
## 11.525 11.55 11.575 11.6 11.625 11.65 11.675 11.7 11.75 11.775
## 668 669 671 672 673 675 676 678 679 680
## 11.8 11.825 11.875 11.9 11.95 12.05 12.125 12.15 12.2 12.225
## 682 683 685 687 688 690 692 694 695 697
## 12.275 12.325 12.375 12.4 12.425 12.5 12.625 12.7 12.9 12.925
## 698 701 702 703 705 706 707 708 709 710
## 12.95 13.025 13.05 13.075 13.1 13.2 13.325 13.375 13.875 14.375
## 712 713 714 715 716 717 718 721 722 723
## 14.55 14.675
## 724 725cumsum(b)## 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
## 13 19 39 64 101 142 182 233 291 359 428 484 548 602 645 688 725cumsum(c)## 45.3 46.6 47 47.4 47.7 47.8 48 48.1 48.2 48.7 48.8 48.9 49 49.2 49.3
## 1 2 3 5 6 7 8 9 10 11 12 13 14 15 16
## 49.8 49.9 50.3 50.5 50.7 51 51.1 51.2 51.4 51.5 51.6 51.7 51.9 52 52.1
## 17 18 19 20 21 24 25 26 27 29 30 33 36 38 39
## 52.7 52.8 52.9 53 53.2 53.3 53.5 53.6 53.7 53.8 53.9 54.2 54.3 54.5 54.7
## 42 45 47 48 50 51 52 53 56 58 60 61 62 63 64
## 54.8 54.9 55 55.1 55.2 55.4 55.5 55.6 55.7 55.8 55.9 56 56.1 56.2 56.3
## 65 68 69 73 74 76 80 86 88 89 91 93 96 97 99
## 56.4 56.5 56.6 56.7 56.8 56.9 57 57.1 57.2 57.3 57.4 57.5 57.7 57.8 57.9
## 100 102 108 110 114 116 117 119 120 123 126 127 128 129 130
## 58 58.3 58.4 58.5 58.6 58.7 58.8 58.9 59 59.1 59.2 59.3 59.4 59.5 59.7
## 133 135 140 145 146 150 153 156 158 159 165 169 173 174 178
## 59.8 59.9 60 60.1 60.2 60.3 60.4 60.5 60.6 60.7 60.8 60.9 61 61.1 61.2
## 180 184 188 191 195 197 202 204 207 210 211 212 214 219 222
## 61.3 61.4 61.5 61.6 61.7 61.8 61.9 62 62.1 62.2 62.3 62.4 62.5 62.6 62.7
## 224 230 234 238 240 244 248 252 258 259 260 263 265 271 273
## 62.8 62.9 63 63.1 63.2 63.3 63.4 63.5 63.6 63.7 63.9 64 64.1 64.2 64.3
## 277 279 283 284 287 294 300 305 309 312 316 319 324 325 327
## 64.4 64.5 64.6 64.7 64.8 64.9 65 65.1 65.2 65.3 65.4 65.5 65.6 65.7 65.8
## 331 333 335 341 344 347 351 355 356 361 369 376 382 386 390
## 65.9 66 66.1 66.2 66.3 66.4 66.5 66.6 66.7 66.8 66.9 67 67.1 67.2 67.3
## 393 399 402 405 410 415 419 423 424 426 430 431 433 436 440
## 67.4 67.5 67.6 67.7 67.8 67.9 68 68.1 68.2 68.3 68.4 68.5 68.6 68.7 68.8
## 444 451 455 460 463 465 469 473 478 481 485 486 492 495 499
## 68.9 69 69.1 69.2 69.3 69.4 69.6 69.7 69.8 69.9 70 70.1 70.2 70.3 70.4
## 502 506 509 512 519 525 527 531 533 536 538 540 543 544 548
## 70.5 70.6 70.8 70.9 71 71.1 71.2 71.3 71.4 71.5 71.6 71.7 71.8 71.9 72
## 552 554 556 561 565 569 574 576 580 584 587 589 592 597 600
## 72.1 72.2 72.3 72.4 72.5 72.6 72.7 72.8 72.9 73 73.1 73.2 73.3 73.4 73.5
## 601 604 605 609 614 616 617 619 621 623 626 627 630 632 639
## 73.6 73.7 73.8 73.9 74 74.1 74.2 74.3 74.4 74.5 74.6 74.7 74.8 74.9 75
## 643 645 647 650 654 655 659 661 663 664 666 668 669 672 673
## 75.1 75.2 75.3 75.4 75.5 75.6 75.7 75.8 75.9 76 76.1 76.2 76.3 76.4 76.5
## 674 676 677 679 682 684 688 691 692 693 694 696 698 699 700
## 76.6 76.8 76.9 77.2 77.4 77.6 77.7 78 78.2 78.4 78.6 78.9 79.1 79.3 79.6
## 702 704 706 707 708 709 710 711 712 714 715 717 718 719 721
## 79.8 80.3 80.8 81.8
## 722 723 724 725cumsum(d)## no yes
## 648 725cumsum(e)## female male
## 358 725cumsum(f)## no yes
## 561 725Frequencies absoluta acumulada relativas
cumsum(g)## 0.507 1.025 1.125 1.175 1.325 1.45
## 0.001379310 0.002758621 0.004137931 0.005517241 0.006896552 0.008275862
## 1.575 1.625 1.675 1.775 1.85 1.9
## 0.009655172 0.011034483 0.012413793 0.013793103 0.015172414 0.016551724
## 1.925 1.95 2 2.025 2.25 2.375
## 0.017931034 0.019310345 0.020689655 0.022068966 0.026206897 0.027586207
## 2.475 2.55 2.625 2.65 2.725 2.825
## 0.028965517 0.030344828 0.033103448 0.035862069 0.040000000 0.041379310
## 2.85 2.875 2.925 2.95 3.025 3.1
## 0.042758621 0.046896552 0.049655172 0.051034483 0.052413793 0.055172414
## 3.175 3.225 3.25 3.4 3.425 3.45
## 0.057931034 0.059310345 0.060689655 0.062068966 0.066206897 0.067586207
## 3.6 3.625 3.65 3.675 3.7 3.75
## 0.068965517 0.070344828 0.071724138 0.074482759 0.077241379 0.078620690
## 3.825 3.85 3.9 3.925 3.975 4.075
## 0.080000000 0.081379310 0.085517241 0.088275862 0.091034483 0.092413793
## 4.125 4.15 4.2 4.25 4.325 4.35
## 0.093793103 0.095172414 0.097931034 0.102068966 0.106206897 0.107586207
## 4.425 4.45 4.475 4.5 4.525 4.55
## 0.111724138 0.114482759 0.117241379 0.118620690 0.120000000 0.121379310
## 4.575 4.625 4.65 4.7 4.725 4.775
## 0.122758621 0.126896552 0.128275862 0.131034483 0.135172414 0.136551724
## 4.8 4.825 4.85 4.875 4.9 4.95
## 0.137931034 0.139310345 0.142068966 0.143448276 0.146206897 0.147586207
## 4.975 5.025 5.05 5.075 5.125 5.15
## 0.151724138 0.155862069 0.160000000 0.161379310 0.162758621 0.166896552
## 5.175 5.2 5.225 5.25 5.275 5.3
## 0.168275862 0.169655172 0.172413793 0.175172414 0.176551724 0.177931034
## 5.325 5.35 5.375 5.425 5.475 5.5
## 0.180689655 0.182068966 0.186206897 0.187586207 0.188965517 0.191724138
## 5.55 5.575 5.6 5.625 5.65 5.675
## 0.195862069 0.197241379 0.198620690 0.200000000 0.204137931 0.205517241
## 5.7 5.725 5.775 5.825 5.85 5.875
## 0.206896552 0.209655172 0.211034483 0.212413793 0.217931034 0.223448276
## 5.95 6 6.05 6.075 6.1 6.125
## 0.227586207 0.230344828 0.235862069 0.240000000 0.244137931 0.248275862
## 6.15 6.175 6.2 6.225 6.25 6.275
## 0.252413793 0.256551724 0.260689655 0.266206897 0.267586207 0.268965517
## 6.3 6.325 6.375 6.4 6.425 6.45
## 0.271724138 0.274482759 0.275862069 0.277241379 0.278620690 0.288275862
## 6.475 6.5 6.525 6.55 6.575 6.6
## 0.292413793 0.295172414 0.297931034 0.302068966 0.307586207 0.308965517
## 6.625 6.65 6.675 6.7 6.725 6.75
## 0.311724138 0.314482759 0.315862069 0.322758621 0.328275862 0.331034483
## 6.775 6.8 6.825 6.85 6.9 6.925
## 0.332413793 0.335172414 0.339310345 0.344827586 0.348965517 0.351724138
## 6.95 6.975 7 7.025 7.05 7.075
## 0.357241379 0.360000000 0.362758621 0.365517241 0.368275862 0.369655172
## 7.1 7.125 7.15 7.175 7.2 7.225
## 0.372413793 0.373793103 0.375172414 0.376551724 0.377931034 0.380689655
## 7.25 7.275 7.3 7.325 7.35 7.375
## 0.383448276 0.388965517 0.391724138 0.397241379 0.404137931 0.408275862
## 7.4 7.425 7.45 7.475 7.5 7.55
## 0.413793103 0.416551724 0.420689655 0.426206897 0.427586207 0.435862069
## 7.575 7.625 7.65 7.675 7.7 7.725
## 0.438620690 0.442758621 0.446896552 0.449655172 0.453793103 0.455172414
## 7.75 7.775 7.8 7.825 7.85 7.875
## 0.457931034 0.459310345 0.462068966 0.471724138 0.475862069 0.478620690
## 7.9 7.925 7.95 7.975 8 8.025
## 0.482758621 0.489655172 0.493793103 0.496551724 0.506206897 0.511724138
## 8.05 8.075 8.1 8.125 8.175 8.2
## 0.513103448 0.515862069 0.517241379 0.522758621 0.524137931 0.528275862
## 8.225 8.25 8.275 8.3 8.325 8.35
## 0.533793103 0.537931034 0.542068966 0.543448276 0.546206897 0.557241379
## 8.375 8.425 8.45 8.475 8.5 8.525
## 0.558620690 0.565517241 0.566896552 0.569655172 0.576551724 0.577931034
## 8.55 8.575 8.6 8.625 8.65 8.675
## 0.582068966 0.584827586 0.593103448 0.601379310 0.604137931 0.605517241
## 8.7 8.725 8.775 8.8 8.825 8.85
## 0.609655172 0.615172414 0.624827586 0.628965517 0.633103448 0.637241379
## 8.875 8.9 8.925 8.975 9 9.025
## 0.640000000 0.642758621 0.644137931 0.651034483 0.655172414 0.660689655
## 9.05 9.1 9.125 9.15 9.175 9.2
## 0.664827586 0.671724138 0.673103448 0.675862069 0.680000000 0.684137931
## 9.225 9.275 9.3 9.325 9.35 9.375
## 0.686896552 0.691034483 0.692413793 0.696551724 0.697931034 0.702068966
## 9.4 9.45 9.475 9.5 9.525 9.55
## 0.703448276 0.706206897 0.711724138 0.713103448 0.717241379 0.721379310
## 9.575 9.6 9.625 9.65 9.675 9.7
## 0.722758621 0.724137931 0.728275862 0.729655172 0.736551724 0.739310345
## 9.725 9.75 9.8 9.825 9.85 9.875
## 0.743448276 0.747586207 0.750344828 0.755862069 0.760000000 0.762758621
## 9.9 9.925 9.95 9.975 10 10.025
## 0.765517241 0.769655172 0.772413793 0.773793103 0.775172414 0.780689655
## 10.05 10.1 10.125 10.175 10.2 10.25
## 0.784827586 0.788965517 0.791724138 0.794482759 0.801379310 0.802758621
## 10.275 10.3 10.325 10.35 10.375 10.4
## 0.805517241 0.808275862 0.809655172 0.812413793 0.813793103 0.819310345
## 10.425 10.45 10.475 10.5 10.525 10.55
## 0.822068966 0.826206897 0.831724138 0.834482759 0.835862069 0.837241379
## 10.575 10.6 10.625 10.65 10.675 10.7
## 0.838620690 0.844137931 0.845517241 0.848275862 0.851034483 0.856551724
## 10.725 10.75 10.775 10.8 10.825 10.85
## 0.860689655 0.862068966 0.864827586 0.866206897 0.868965517 0.870344828
## 10.875 10.9 10.925 10.95 10.975 11
## 0.873103448 0.875862069 0.880000000 0.881379310 0.884137931 0.885517241
## 11.025 11.05 11.075 11.125 11.175 11.225
## 0.888275862 0.889655172 0.895172414 0.897931034 0.899310345 0.906206897
## 11.275 11.3 11.325 11.35 11.4 11.5
## 0.907586207 0.908965517 0.911724138 0.913103448 0.915862069 0.920000000
## 11.525 11.55 11.575 11.6 11.625 11.65
## 0.921379310 0.922758621 0.925517241 0.926896552 0.928275862 0.931034483
## 11.675 11.7 11.75 11.775 11.8 11.825
## 0.932413793 0.935172414 0.936551724 0.937931034 0.940689655 0.942068966
## 11.875 11.9 11.95 12.05 12.125 12.15
## 0.944827586 0.947586207 0.948965517 0.951724138 0.954482759 0.957241379
## 12.2 12.225 12.275 12.325 12.375 12.4
## 0.958620690 0.961379310 0.962758621 0.966896552 0.968275862 0.969655172
## 12.425 12.5 12.625 12.7 12.9 12.925
## 0.972413793 0.973793103 0.975172414 0.976551724 0.977931034 0.979310345
## 12.95 13.025 13.05 13.075 13.1 13.2
## 0.982068966 0.983448276 0.984827586 0.986206897 0.987586207 0.988965517
## 13.325 13.375 13.875 14.375 14.55 14.675
## 0.990344828 0.994482759 0.995862069 0.997241379 0.998620690 1.000000000cumsum(h)## 3 4 5 6 7 8
## 0.01793103 0.02620690 0.05379310 0.08827586 0.13931034 0.19586207
## 9 10 11 12 13 14
## 0.25103448 0.32137931 0.40137931 0.49517241 0.59034483 0.66758621
## 15 16 17 18 19
## 0.75586207 0.83034483 0.88965517 0.94896552 1.00000000cumsum(i)## 45.3 46.6 47 47.4 47.7 47.8
## 0.001379310 0.002758621 0.004137931 0.006896552 0.008275862 0.009655172
## 48 48.1 48.2 48.7 48.8 48.9
## 0.011034483 0.012413793 0.013793103 0.015172414 0.016551724 0.017931034
## 49 49.2 49.3 49.8 49.9 50.3
## 0.019310345 0.020689655 0.022068966 0.023448276 0.024827586 0.026206897
## 50.5 50.7 51 51.1 51.2 51.4
## 0.027586207 0.028965517 0.033103448 0.034482759 0.035862069 0.037241379
## 51.5 51.6 51.7 51.9 52 52.1
## 0.040000000 0.041379310 0.045517241 0.049655172 0.052413793 0.053793103
## 52.7 52.8 52.9 53 53.2 53.3
## 0.057931034 0.062068966 0.064827586 0.066206897 0.068965517 0.070344828
## 53.5 53.6 53.7 53.8 53.9 54.2
## 0.071724138 0.073103448 0.077241379 0.080000000 0.082758621 0.084137931
## 54.3 54.5 54.7 54.8 54.9 55
## 0.085517241 0.086896552 0.088275862 0.089655172 0.093793103 0.095172414
## 55.1 55.2 55.4 55.5 55.6 55.7
## 0.100689655 0.102068966 0.104827586 0.110344828 0.118620690 0.121379310
## 55.8 55.9 56 56.1 56.2 56.3
## 0.122758621 0.125517241 0.128275862 0.132413793 0.133793103 0.136551724
## 56.4 56.5 56.6 56.7 56.8 56.9
## 0.137931034 0.140689655 0.148965517 0.151724138 0.157241379 0.160000000
## 57 57.1 57.2 57.3 57.4 57.5
## 0.161379310 0.164137931 0.165517241 0.169655172 0.173793103 0.175172414
## 57.7 57.8 57.9 58 58.3 58.4
## 0.176551724 0.177931034 0.179310345 0.183448276 0.186206897 0.193103448
## 58.5 58.6 58.7 58.8 58.9 59
## 0.200000000 0.201379310 0.206896552 0.211034483 0.215172414 0.217931034
## 59.1 59.2 59.3 59.4 59.5 59.7
## 0.219310345 0.227586207 0.233103448 0.238620690 0.240000000 0.245517241
## 59.8 59.9 60 60.1 60.2 60.3
## 0.248275862 0.253793103 0.259310345 0.263448276 0.268965517 0.271724138
## 60.4 60.5 60.6 60.7 60.8 60.9
## 0.278620690 0.281379310 0.285517241 0.289655172 0.291034483 0.292413793
## 61 61.1 61.2 61.3 61.4 61.5
## 0.295172414 0.302068966 0.306206897 0.308965517 0.317241379 0.322758621
## 61.6 61.7 61.8 61.9 62 62.1
## 0.328275862 0.331034483 0.336551724 0.342068966 0.347586207 0.355862069
## 62.2 62.3 62.4 62.5 62.6 62.7
## 0.357241379 0.358620690 0.362758621 0.365517241 0.373793103 0.376551724
## 62.8 62.9 63 63.1 63.2 63.3
## 0.382068966 0.384827586 0.390344828 0.391724138 0.395862069 0.405517241
## 63.4 63.5 63.6 63.7 63.9 64
## 0.413793103 0.420689655 0.426206897 0.430344828 0.435862069 0.440000000
## 64.1 64.2 64.3 64.4 64.5 64.6
## 0.446896552 0.448275862 0.451034483 0.456551724 0.459310345 0.462068966
## 64.7 64.8 64.9 65 65.1 65.2
## 0.470344828 0.474482759 0.478620690 0.484137931 0.489655172 0.491034483
## 65.3 65.4 65.5 65.6 65.7 65.8
## 0.497931034 0.508965517 0.518620690 0.526896552 0.532413793 0.537931034
## 65.9 66 66.1 66.2 66.3 66.4
## 0.542068966 0.550344828 0.554482759 0.558620690 0.565517241 0.572413793
## 66.5 66.6 66.7 66.8 66.9 67
## 0.577931034 0.583448276 0.584827586 0.587586207 0.593103448 0.594482759
## 67.1 67.2 67.3 67.4 67.5 67.6
## 0.597241379 0.601379310 0.606896552 0.612413793 0.622068966 0.627586207
## 67.7 67.8 67.9 68 68.1 68.2
## 0.634482759 0.638620690 0.641379310 0.646896552 0.652413793 0.659310345
## 68.3 68.4 68.5 68.6 68.7 68.8
## 0.663448276 0.668965517 0.670344828 0.678620690 0.682758621 0.688275862
## 68.9 69 69.1 69.2 69.3 69.4
## 0.692413793 0.697931034 0.702068966 0.706206897 0.715862069 0.724137931
## 69.6 69.7 69.8 69.9 70 70.1
## 0.726896552 0.732413793 0.735172414 0.739310345 0.742068966 0.744827586
## 70.2 70.3 70.4 70.5 70.6 70.8
## 0.748965517 0.750344828 0.755862069 0.761379310 0.764137931 0.766896552
## 70.9 71 71.1 71.2 71.3 71.4
## 0.773793103 0.779310345 0.784827586 0.791724138 0.794482759 0.800000000
## 71.5 71.6 71.7 71.8 71.9 72
## 0.805517241 0.809655172 0.812413793 0.816551724 0.823448276 0.827586207
## 72.1 72.2 72.3 72.4 72.5 72.6
## 0.828965517 0.833103448 0.834482759 0.840000000 0.846896552 0.849655172
## 72.7 72.8 72.9 73 73.1 73.2
## 0.851034483 0.853793103 0.856551724 0.859310345 0.863448276 0.864827586
## 73.3 73.4 73.5 73.6 73.7 73.8
## 0.868965517 0.871724138 0.881379310 0.886896552 0.889655172 0.892413793
## 73.9 74 74.1 74.2 74.3 74.4
## 0.896551724 0.902068966 0.903448276 0.908965517 0.911724138 0.914482759
## 74.5 74.6 74.7 74.8 74.9 75
## 0.915862069 0.918620690 0.921379310 0.922758621 0.926896552 0.928275862
## 75.1 75.2 75.3 75.4 75.5 75.6
## 0.929655172 0.932413793 0.933793103 0.936551724 0.940689655 0.943448276
## 75.7 75.8 75.9 76 76.1 76.2
## 0.948965517 0.953103448 0.954482759 0.955862069 0.957241379 0.960000000
## 76.3 76.4 76.5 76.6 76.8 76.9
## 0.962758621 0.964137931 0.965517241 0.968275862 0.971034483 0.973793103
## 77.2 77.4 77.6 77.7 78 78.2
## 0.975172414 0.976551724 0.977931034 0.979310345 0.980689655 0.982068966
## 78.4 78.6 78.9 79.1 79.3 79.6
## 0.984827586 0.986206897 0.988965517 0.990344828 0.991724138 0.994482759
## 79.8 80.3 80.8 81.8
## 0.995862069 0.997241379 0.998620690 1.000000000cumsum(j)## no yes
## 0.8937931 1.0000000cumsum(k)## female male
## 0.4937931 1.0000000cumsum(l)## no yes
## 0.7737931 1.0000000Representacio grafica
hist(a,col = heat.colors(4))
hist(b,col = "Darkgreen")
hist(c,col = "Pink")
hist(d,col = "blue")
hist(e,col = "DarkBlue")
hist(f,col = "red")
hist(g,col = "darkred")
hist(h,col = "yellow")
hist(i,col = "black")
hist(j,col = "lightblue")
hist(k,col = "lightyellow")
hist(l,col = "lightgreen")
print("53494MSQ")## [1] "53494MSQ"print("86696FBR")## [1] "86696FBR"print("89641QZK")## [1] "89641QZK"print("61876FIZ")## [1] "61876FIZ"