library(fdth)
##
## Attaching package: 'fdth'
## The following objects are masked from 'package:stats':
##
## sd, var
library(readr)
datos.alumnos <- read.csv("https://raw.githubusercontent.com/rpizarrog/probabilidad-y-estad-stica/master/datos/promedios%20alumnos/datos%20alumnos%20promedios%20SEP%202020.csv")
header = TRUE;
encoding = "ISO-8859-1"
head(datos.alumnos)
## No..Control Alumno Semestre Cr..Apr. Carga Promedio Carrera
## 1 20190001 1 11 198 19 80.21 SISTEMAS
## 2 20190002 2 11 235 10 84.33 SISTEMAS
## 3 20190003 3 9 235 10 95.25 SISTEMAS
## 4 20190004 4 9 226 19 95.00 SISTEMAS
## 5 20190005 5 10 231 14 82.32 SISTEMAS
## 6 20190006 6 9 212 23 95.02 SISTEMAS
tail(datos.alumnos)
## No..Control Alumno Semestre Cr..Apr. Carga Promedio Carrera
## 5924 20195924 5924 2 27 28 92.83 ADMINISTRACION
## 5925 20195925 5925 7 94 13 80.95 ADMINISTRACION
## 5926 20195926 5926 5 103 32 92.68 ADMINISTRACION
## 5927 20195927 5927 4 79 34 86.18 ADMINISTRACION
## 5928 20195928 5928 5 108 32 90.48 ADMINISTRACION
## 5929 20195929 5929 7 169 32 92.33 ADMINISTRACION
alumnosPrimero<- subset(datos.alumnos, Semestre == 1)
tabla.frec.Primero <- data.frame(fdt_cat(alumnosPrimero$Carrera))
tabla.frec.Primero
## Category f rf rf... cf cf...
## 1 ARQUITECTURA 128 0.12415131 12.415131 128 12.41513
## 2 GESTION EMPRESARIAL 89 0.08632396 8.632396 217 21.04753
## 3 QUIMICA 89 0.08632396 8.632396 306 29.67992
## 4 INDUSTRIAL 88 0.08535403 8.535403 394 38.21532
## 5 CIVIL 86 0.08341416 8.341416 480 46.55674
## 6 BIOQUIMICA 84 0.08147430 8.147430 564 54.70417
## 7 ADMINISTRACION 83 0.08050436 8.050436 647 62.75461
## 8 SISTEMAS 78 0.07565470 7.565470 725 70.32008
## 9 ELECTRICA 77 0.07468477 7.468477 802 77.78855
## 10 MECANICA 76 0.07371484 7.371484 878 85.16004
## 11 MECATRONICA 70 0.06789525 6.789525 948 91.94956
## 12 ELECTRONICA 36 0.03491756 3.491756 984 95.44132
## 13 INFORMATICA 30 0.02909796 2.909796 1014 98.35112
## 14 TIC 17 0.01648885 1.648885 1031 100.00000
names(tabla.frec.Primero) <- c("Carrera","Frec.Absoluta","Frec.Relativa","Frec.Parc","Frec.Acum","Porc")
barplot(main = "Alumnos de Primer Semestre",
xlab = "Carreras", ylab = "Frecuencia Absoluta",
height = tabla.frec.Primero$Frec.Absoluta,
names.arg = substr(tabla.frec.Primero$Carrera,1,3))
tabla.frec <- data.frame(fdt_cat(datos.alumnos$Carrera))
names(tabla.frec) <- c("Carrera","Frec.Absoluta","Frec.Relativa","Frec.Porc","Frec.Acum","Frec.Acum.Porc")
tabla.frec
## Carrera Frec.Absoluta Frec.Relativa Frec.Porc Frec.Acum
## 1 INDUSTRIAL 707 0.11924439 11.924439 707
## 2 ARQUITECTURA 675 0.11384719 11.384719 1382
## 3 CIVIL 648 0.10929330 10.929330 2030
## 4 GESTION EMPRESARIAL 585 0.09866757 9.866757 2615
## 5 QUIMICA 568 0.09580030 9.580030 3183
## 6 ADMINISTRACION 497 0.08382527 8.382527 3680
## 7 SISTEMAS 452 0.07623545 7.623545 4132
## 8 BIOQUIMICA 441 0.07438017 7.438017 4573
## 9 MECATRONICA 432 0.07286220 7.286220 5005
## 10 MECANICA 301 0.05076741 5.076741 5306
## 11 ELECTRICA 280 0.04722550 4.722550 5586
## 12 ELECTRONICA 161 0.02715466 2.715466 5747
## 13 INFORMATICA 101 0.01703491 1.703491 5848
## 14 TIC 81 0.01366166 1.366166 5929
## Frec.Acum.Porc
## 1 11.92444
## 2 23.30916
## 3 34.23849
## 4 44.10525
## 5 53.68528
## 6 62.06780
## 7 69.69135
## 8 77.12936
## 9 84.41558
## 10 89.49233
## 11 94.21488
## 12 96.93034
## 13 98.63383
## 14 100.00000
barplot(main = "Alumnos de Todos los Semestre",
xlab = "Carreras", ylab = "Frecuencia Absoluta",
height = tabla.frec$Frec.Absoluta,
names.arg = substr(tabla.frec$Carrera,1,3))
barplot(main = "Alumnos de Todos los Semestre",
xlab = "Carreras", ylab = "Frecuencia Relativa",
height = tabla.frec$Frec.Relativa,
names.arg = substr(tabla.frec$Carrera,1,3))
barplot(main = "Alumnos de Todos los Semestre",
xlab = "Carreras", ylab = "Frecuencia Porcentual %",
height = tabla.frec$Frec.Porc,
names.arg = substr(tabla.frec$Carrera,1,3))
ADMINISTRACION <- subset(datos.alumnos, Carrera == "ADMINISTRACION")
ADMINISTRACION$Semestre <- factor(ADMINISTRACION$Semestre)
tabla.frec.adm <- data.frame(fdt_cat(ADMINISTRACION$Semestre))
names(tabla.frec.adm) <- c("Semestre","Frec.Absoluta","Frec.Relativa","Frec.Porc","Frec.Acum","Frec.Acum.Porc")
tabla.frec.adm
## Semestre Frec.Absoluta Frec.Relativa Frec.Porc Frec.Acum Frec.Acum.Porc
## 1 1 83 0.16700201 16.700201 83 16.70020
## 2 5 66 0.13279678 13.279678 149 29.97988
## 3 7 65 0.13078471 13.078471 214 43.05835
## 4 3 62 0.12474849 12.474849 276 55.53320
## 5 8 49 0.09859155 9.859155 325 65.39235
## 6 9 46 0.09255533 9.255533 371 74.64789
## 7 2 37 0.07444668 7.444668 408 82.09256
## 8 6 31 0.06237425 6.237425 439 88.32998
## 9 4 27 0.05432596 5.432596 466 93.76258
## 10 10 15 0.03018109 3.018109 481 96.78068
## 11 11 12 0.02414487 2.414487 493 99.19517
## 12 12 4 0.00804829 0.804829 497 100.00000
ARQUITECTURA <- subset(datos.alumnos, Carrera == "ARQUITECTURA")
ARQUITECTURA$Semestre <- factor(ARQUITECTURA$Semestre)
tabla.frec.arq <- data.frame(fdt_cat(ARQUITECTURA$Semestre))
names(tabla.frec.arq) <- c("Semestre","Frec.Absoluta","Frec.Relativa","Frec.Porc","Frec.Acum","Frec.Acum.Porc")
tabla.frec.arq
## Semestre Frec.Absoluta Frec.Relativa Frec.Porc Frec.Acum Frec.Acum.Porc
## 1 1 128 0.18962963 18.962963 128 18.96296
## 2 2 87 0.12888889 12.888889 215 31.85185
## 3 3 66 0.09777778 9.777778 281 41.62963
## 4 6 64 0.09481481 9.481481 345 51.11111
## 5 4 62 0.09185185 9.185185 407 60.29630
## 6 8 60 0.08888889 8.888889 467 69.18519
## 7 5 58 0.08592593 8.592593 525 77.77778
## 8 7 53 0.07851852 7.851852 578 85.62963
## 9 9 47 0.06962963 6.962963 625 92.59259
## 10 10 31 0.04592593 4.592593 656 97.18519
## 11 12 11 0.01629630 1.629630 667 98.81481
## 12 11 8 0.01185185 1.185185 675 100.00000
SISTEMAS <- subset(datos.alumnos, Carrera == "SISTEMAS")
SISTEMAS$Semestre <- factor(SISTEMAS$Semestre)
tabla.frec.sis <- data.frame(fdt_cat(SISTEMAS$Semestre))
names(tabla.frec.sis) <- c("Semestre","Frec.Absoluta","Frec.Relativa","Frec.Porc","Frec.Acum","Frec.Acum.Porc")
tabla.frec.sis
## Semestre Frec.Absoluta Frec.Relativa Frec.Porc Frec.Acum Frec.Acum.Porc
## 1 1 78 0.172566372 17.2566372 78 17.25664
## 2 3 64 0.141592920 14.1592920 142 31.41593
## 3 7 58 0.128318584 12.8318584 200 44.24779
## 4 5 51 0.112831858 11.2831858 251 55.53097
## 5 8 46 0.101769912 10.1769912 297 65.70796
## 6 4 38 0.084070796 8.4070796 335 74.11504
## 7 9 35 0.077433628 7.7433628 370 81.85841
## 8 2 29 0.064159292 6.4159292 399 88.27434
## 9 10 15 0.033185841 3.3185841 414 91.59292
## 10 11 15 0.033185841 3.3185841 429 94.91150
## 11 6 14 0.030973451 3.0973451 443 98.00885
## 12 13 5 0.011061947 1.1061947 448 99.11504
## 13 12 4 0.008849558 0.8849558 452 100.00000
BIOQUIMICA <- subset(datos.alumnos, Carrera == "BIOQUIMICA")
BIOQUIMICA$Semestre <- factor(BIOQUIMICA$Semestre)
tabla.frec.bio <- data.frame(fdt_cat(BIOQUIMICA$Semestre))
names(tabla.frec.bio) <- c("Semestre","Frec.Absoluta","Frec.Relativa","Frec.Porc","Frec.Acum","Frec.Acum.Porc")
tabla.frec.bio
## Semestre Frec.Absoluta Frec.Relativa Frec.Porc Frec.Acum Frec.Acum.Porc
## 1 1 84 0.190476190 19.0476190 84 19.04762
## 2 3 65 0.147392290 14.7392290 149 33.78685
## 3 7 55 0.124716553 12.4716553 204 46.25850
## 4 5 47 0.106575964 10.6575964 251 56.91610
## 5 4 40 0.090702948 9.0702948 291 65.98639
## 6 9 38 0.086167800 8.6167800 329 74.60317
## 7 6 36 0.081632653 8.1632653 365 82.76644
## 8 2 34 0.077097506 7.7097506 399 90.47619
## 9 8 17 0.038548753 3.8548753 416 94.33107
## 10 11 11 0.024943311 2.4943311 427 96.82540
## 11 10 10 0.022675737 2.2675737 437 99.09297
## 12 12 3 0.006802721 0.6802721 440 99.77324
## 13 13 1 0.002267574 0.2267574 441 100.00000
CIVIL <- subset(datos.alumnos, Carrera == "CIVIL")
CIVIL$Semestre <- factor(CIVIL$Semestre)
tabla.frec.civ <- data.frame(fdt_cat(CIVIL$Semestre))
names(tabla.frec.civ) <- c("Semestre","Frec.Absoluta","Frec.Relativa","Frec.Porc","Frec.Acum","Frec.Acum.Porc")
tabla.frec.civ
## Semestre Frec.Absoluta Frec.Relativa Frec.Porc Frec.Acum Frec.Acum.Porc
## 1 1 86 0.13271605 13.271605 86 13.27160
## 2 2 74 0.11419753 11.419753 160 24.69136
## 3 6 72 0.11111111 11.111111 232 35.80247
## 4 5 71 0.10956790 10.956790 303 46.75926
## 5 3 66 0.10185185 10.185185 369 56.94444
## 6 4 66 0.10185185 10.185185 435 67.12963
## 7 7 58 0.08950617 8.950617 493 76.08025
## 8 8 57 0.08796296 8.796296 550 84.87654
## 9 9 44 0.06790123 6.790123 594 91.66667
## 10 10 30 0.04629630 4.629630 624 96.29630
## 11 12 15 0.02314815 2.314815 639 98.61111
## 12 11 8 0.01234568 1.234568 647 99.84568
## 13 15 1 0.00154321 0.154321 648 100.00000
ELECTRONICA <- subset(datos.alumnos, Carrera == "ELECTRONICA")
ELECTRONICA$Semestre <- factor(ELECTRONICA$Semestre)
tabla.frec.ele <- data.frame(fdt_cat(ELECTRONICA$Semestre))
names(tabla.frec.ele) <- c("Semestre","Frec.Absoluta","Frec.Relativa","Frec.Porc","Frec.Acum","Frec.Acum.Porc")
tabla.frec.ele
## Semestre Frec.Absoluta Frec.Relativa Frec.Porc Frec.Acum Frec.Acum.Porc
## 1 1 36 0.22360248 22.360248 36 22.36025
## 2 3 32 0.19875776 19.875776 68 42.23602
## 3 5 26 0.16149068 16.149068 94 58.38509
## 4 9 22 0.13664596 13.664596 116 72.04969
## 5 7 21 0.13043478 13.043478 137 85.09317
## 6 11 10 0.06211180 6.211180 147 91.30435
## 7 6 6 0.03726708 3.726708 153 95.03106
## 8 10 5 0.03105590 3.105590 158 98.13665
## 9 8 3 0.01863354 1.863354 161 100.00000
ELECTRICA <- subset(datos.alumnos, Carrera == "ELECTRICA")
ELECTRICA$Semestre <- factor(ELECTRICA$Semestre)
tabla.frec.elec <- data.frame(fdt_cat(ELECTRICA$Semestre))
names(tabla.frec.elec) <- c("Semestre","Frec.Absoluta","Frec.Relativa","Frec.Porc","Frec.Acum","Frec.Acum.Porc")
tabla.frec.elec
## Semestre Frec.Absoluta Frec.Relativa Frec.Porc Frec.Acum Frec.Acum.Porc
## 1 1 77 0.275000000 27.5000000 77 27.50000
## 2 5 54 0.192857143 19.2857143 131 46.78571
## 3 3 42 0.150000000 15.0000000 173 61.78571
## 4 7 27 0.096428571 9.6428571 200 71.42857
## 5 9 21 0.075000000 7.5000000 221 78.92857
## 6 11 15 0.053571429 5.3571429 236 84.28571
## 7 6 12 0.042857143 4.2857143 248 88.57143
## 8 10 12 0.042857143 4.2857143 260 92.85714
## 9 12 8 0.028571429 2.8571429 268 95.71429
## 10 8 6 0.021428571 2.1428571 274 97.85714
## 11 15 3 0.010714286 1.0714286 277 98.92857
## 12 2 1 0.003571429 0.3571429 278 99.28571
## 13 13 1 0.003571429 0.3571429 279 99.64286
## 14 14 1 0.003571429 0.3571429 280 100.00000
INDUSTRIAL <- subset(datos.alumnos, Carrera == "INDUSTRIAL")
INDUSTRIAL$Semestre <- factor(INDUSTRIAL$Semestre)
tabla.frec.ind <- data.frame(fdt_cat(INDUSTRIAL$Semestre))
names(tabla.frec.ind) <- c("Semestre","Frec.Absoluta","Frec.Relativa","Frec.Porc","Frec.Acum","Frec.Acum.Porc")
tabla.frec.ind
## Semestre Frec.Absoluta Frec.Relativa Frec.Porc Frec.Acum Frec.Acum.Porc
## 1 1 88 0.124469590 12.4469590 88 12.44696
## 2 3 87 0.123055163 12.3055163 175 24.75248
## 3 5 82 0.115983027 11.5983027 257 36.35078
## 4 7 77 0.108910891 10.8910891 334 47.24187
## 5 6 76 0.107496464 10.7496464 410 57.99151
## 6 2 75 0.106082037 10.6082037 485 68.59972
## 7 4 69 0.097595474 9.7595474 554 78.35926
## 8 8 69 0.097595474 9.7595474 623 88.11881
## 9 9 38 0.053748232 5.3748232 661 93.49364
## 10 10 24 0.033946252 3.3946252 685 96.88826
## 11 11 8 0.011315417 1.1315417 693 98.01980
## 12 12 6 0.008486563 0.8486563 699 98.86846
## 13 14 5 0.007072136 0.7072136 704 99.57567
## 14 13 3 0.004243281 0.4243281 707 100.00000
MECANICA <- subset(datos.alumnos, Carrera == "MECANICA")
MECANICA$Semestre <- factor(MECANICA$Semestre)
tabla.frec.mec <- data.frame(fdt_cat(MECANICA$Semestre))
names(tabla.frec.mec) <- c("Semestre","Frec.Absoluta","Frec.Relativa","Frec.Porc","Frec.Acum","Frec.Acum.Porc")
tabla.frec.mec
## Semestre Frec.Absoluta Frec.Relativa Frec.Porc Frec.Acum Frec.Acum.Porc
## 1 1 76 0.252491694 25.2491694 76 25.24917
## 2 3 58 0.192691030 19.2691030 134 44.51827
## 3 5 43 0.142857143 14.2857143 177 58.80399
## 4 7 41 0.136212625 13.6212625 218 72.42525
## 5 6 21 0.069767442 6.9767442 239 79.40199
## 6 9 18 0.059800664 5.9800664 257 85.38206
## 7 8 14 0.046511628 4.6511628 271 90.03322
## 8 11 14 0.046511628 4.6511628 285 94.68439
## 9 10 11 0.036544850 3.6544850 296 98.33887
## 10 12 3 0.009966777 0.9966777 299 99.33555
## 11 4 2 0.006644518 0.6644518 301 100.00000
MECATRONICA <- subset(datos.alumnos, Carrera == "MECATRONICA")
MECATRONICA$Semestre <- factor(MECATRONICA$Semestre)
tabla.frec.mct <- data.frame(fdt_cat(MECATRONICA$Semestre))
names(tabla.frec.mct) <- c("Semestre","Frec.Absoluta","Frec.Relativa","Frec.Porc","Frec.Acum","Frec.Acum.Porc")
tabla.frec.mct
## Semestre Frec.Absoluta Frec.Relativa Frec.Porc Frec.Acum Frec.Acum.Porc
## 1 1 70 0.162037037 16.2037037 70 16.20370
## 2 5 64 0.148148148 14.8148148 134 31.01852
## 3 3 61 0.141203704 14.1203704 195 45.13889
## 4 7 56 0.129629630 12.9629630 251 58.10185
## 5 4 45 0.104166667 10.4166667 296 68.51852
## 6 8 32 0.074074074 7.4074074 328 75.92593
## 7 9 28 0.064814815 6.4814815 356 82.40741
## 8 2 26 0.060185185 6.0185185 382 88.42593
## 9 6 23 0.053240741 5.3240741 405 93.75000
## 10 10 16 0.037037037 3.7037037 421 97.45370
## 11 11 8 0.018518519 1.8518519 429 99.30556
## 12 12 3 0.006944444 0.6944444 432 100.00000
QUIMICA <- subset(datos.alumnos, Carrera == "QUIMICA")
QUIMICA$Semestre <- factor(QUIMICA$Semestre)
tabla.frec.qui <- data.frame(fdt_cat(QUIMICA$Semestre))
names(tabla.frec.qui) <- c("Semestre","Frec.Absoluta","Frec.Relativa","Frec.Porc","Frec.Acum","Frec.Acum.Porc")
tabla.frec.qui
## Semestre Frec.Absoluta Frec.Relativa Frec.Porc Frec.Acum Frec.Acum.Porc
## 1 1 89 0.156690141 15.6690141 89 15.66901
## 2 3 77 0.135563380 13.5563380 166 29.22535
## 3 2 65 0.114436620 11.4436620 231 40.66901
## 4 5 65 0.114436620 11.4436620 296 52.11268
## 5 7 58 0.102112676 10.2112676 354 62.32394
## 6 9 57 0.100352113 10.0352113 411 72.35915
## 7 8 54 0.095070423 9.5070423 465 81.86620
## 8 4 39 0.068661972 6.8661972 504 88.73239
## 9 6 32 0.056338028 5.6338028 536 94.36620
## 10 10 19 0.033450704 3.3450704 555 97.71127
## 11 11 8 0.014084507 1.4084507 563 99.11972
## 12 12 4 0.007042254 0.7042254 567 99.82394
## 13 13 1 0.001760563 0.1760563 568 100.00000
GESTION <- subset(datos.alumnos, Carrera == "GESTION EMPRESARIAL")
GESTION$Semestre <- factor(GESTION$Semestre)
tabla.frec.ges <- data.frame(fdt_cat(GESTION$Semestre))
names(tabla.frec.ges) <- c("Semestre","Frec.Absoluta","Frec.Relativa","Frec.Porc","Frec.Acum","Frec.Acum.Porc")
tabla.frec.ges
## Semestre Frec.Absoluta Frec.Relativa Frec.Porc Frec.Acum Frec.Acum.Porc
## 1 1 89 0.152136752 15.2136752 89 15.21368
## 2 3 73 0.124786325 12.4786325 162 27.69231
## 3 5 67 0.114529915 11.4529915 229 39.14530
## 4 8 63 0.107692308 10.7692308 292 49.91453
## 5 7 58 0.099145299 9.9145299 350 59.82906
## 6 6 54 0.092307692 9.2307692 404 69.05983
## 7 9 48 0.082051282 8.2051282 452 77.26496
## 8 2 41 0.070085470 7.0085470 493 84.27350
## 9 4 40 0.068376068 6.8376068 533 91.11111
## 10 10 29 0.049572650 4.9572650 562 96.06838
## 11 11 16 0.027350427 2.7350427 578 98.80342
## 12 12 6 0.010256410 1.0256410 584 99.82906
## 13 13 1 0.001709402 0.1709402 585 100.00000
INFORMATICA <- subset(datos.alumnos, Carrera == "INFORMATICA")
INFORMATICA$Semestre <- factor(INFORMATICA$Semestre)
tabla.frec.inf <- data.frame(fdt_cat(INFORMATICA$Semestre))
names(tabla.frec.inf) <- c("Semestre","Frec.Absoluta","Frec.Relativa","Frec.Porc","Frec.Acum","Frec.Acum.Porc")
tabla.frec.inf
## Semestre Frec.Absoluta Frec.Relativa Frec.Porc Frec.Acum Frec.Acum.Porc
## 1 1 30 0.29702970 29.702970 30 29.70297
## 2 3 23 0.22772277 22.772277 53 52.47525
## 3 5 14 0.13861386 13.861386 67 66.33663
## 4 7 14 0.13861386 13.861386 81 80.19802
## 5 9 13 0.12871287 12.871287 94 93.06931
## 6 11 5 0.04950495 4.950495 99 98.01980
## 7 4 1 0.00990099 0.990099 100 99.00990
## 8 13 1 0.00990099 0.990099 101 100.00000
barplot(main = "Alumnos de ADMINISTRACION por semestre",
xlab = "Semestres", ylab = "Frecuencia Absoluta",
height = tabla.frec.adm$Frec.Absoluta,
names.arg = tabla.frec.adm$Semestre)
barplot(main = "Alumnos de ARQUITECTURA por semestre",
xlab = "Semestres", ylab = "Frecuencia Absoluta",
height = tabla.frec.arq$Frec.Absoluta,
names.arg = tabla.frec.arq$Semestre)
barplot(main = "Alumnos de BIOQUIMICA por semestre",
xlab = "Semestres", ylab = "Frecuencia Absoluta",
height = tabla.frec.bio$Frec.Absoluta,
names.arg = tabla.frec.bio$Semestre)
barplot(main = "Alumnos de CIVIL por semestre",
xlab = "Semestres", ylab = "Frecuencia Absoluta",
height = tabla.frec.civ$Frec.Absoluta,
names.arg = tabla.frec.civ$Semestre)
barplot(main = "Alumnos de ELECTRICA por semestre",
xlab = "Semestres", ylab = "Frecuencia Absoluta",
height = tabla.frec.elec$Frec.Absoluta,
names.arg = tabla.frec.elec$Semestre)
barplot(main = "Alumnos de ELECTRONICA por semestre",
xlab = "Semestres", ylab = "Frecuencia Absoluta",
height = tabla.frec.ele$Frec.Absoluta,
names.arg = tabla.frec.ele$Semestre)
barplot(main = "Alumnos de GESTION EMPRESARIAL por semestre",
xlab = "Semestres", ylab = "Frecuencia Absoluta",
height = tabla.frec.ges$Frec.Absoluta,
names.arg = tabla.frec.ges$Semestre)
barplot(main = "Alumnos de INDUSTRIAL por semestre",
xlab = "Semestres", ylab = "Frecuencia Absoluta",
height = tabla.frec.ind$Frec.Absoluta,
names.arg = tabla.frec.ind$Semestre)
barplot(main = "Alumnos de INFORMATICA por semestre",
xlab = "Semestres", ylab = "Frecuencia Absoluta",
height = tabla.frec.inf$Frec.Absoluta,
names.arg = tabla.frec.inf$Semestre)
barplot(main = "Alumnos de BIOQUIMICA por semestre",
xlab = "Semestres", ylab = "Frecuencia Absoluta",
height = tabla.frec.bio$Frec.Absoluta,
names.arg = tabla.frec.bio$Semestre)
barplot(main = "Alumnos de QUIMICA por semestre",
xlab = "Semestres", ylab = "Frecuencia Absoluta",
height = tabla.frec.qui$Frec.Absoluta,
names.arg = tabla.frec.qui$Semestre)
barplot(main = "Alumnos de SISTEMAS por semestre",
xlab = "Semestres", ylab = "Frecuencia Absoluta",
height = tabla.frec.sis$Frec.Absoluta,
names.arg = tabla.frec.sis$Semestre)
barplot(main = "Alumnos de MECATRONICA por semestres",
xlab = "Semestres", ylab = "Frecuencia Absoluta",
height = tabla.frec.mct$Frec.Absoluta,
names.arg = tabla.frec.mct$Semestre)
barplot(main = "Alumnos de MECANICA por semestres",
xlab = "Semestres", ylab = "Frecuencia Absoluta",
height = tabla.frec.mec$Frec.Absoluta,
names.arg = tabla.frec.mec$Semestre)
Son 11 filas en total, las cuales, las variables mas importantes las de obtener frecuencia es el total de alumnos y las carreras. se puede ver que los alumnos de arquitectura y civil, son los que tienen mas estudiantes y los que tienen menos alumnos son informatica. los alumnos que representan el 35% son los de Mecanica y Electronica y el 50% son los que estan en la carrera de Industrial, Civil ,Quimica y los alumnos de sistemas se encuentran en un punto medio. Las tablas de distribucion sirven para medir los datos mediante sus frecuencias y poder sacar una conclusion. En las graficas, se interpreta los valores que representan los numeros y los datos recopilados para llegar a una conclusion. Hubo complicaciones, pero se pudo hacer lo que se pudo,y corregir algunos errores, ya que es la primera vez que se maneja este programa y es dificil el saber lo que estas haciendo.