Practica3EQ6

Carreras del Equipo 6 : Industrial , Informatica, Electrica Y Sistemas

library(readr)
datos<- read.csv("C:/Users/Usuario/Downloads/alumnos inscritos ene-jun 2018.csv")

Alumnos de industrial con promedio > 0

alumnosIndustrial <- datos$promedio[which(datos$carrera == 'INDUSTRIAL' & datos$promedio > 0)]
alumnosIndustrial

##   [1] 84.28 88.58 77.41 79.32 84.62 79.16 89.00 79.33 78.08 81.16 92.65
##  [12] 93.03 82.69 79.10 85.00 81.10 92.94 89.38 91.53 85.59 83.95 81.94
##  [23] 82.56 83.30 86.96 76.75 90.27 87.66 83.07 87.77 82.13 84.85 79.35
##  [34] 82.00 80.34 81.70 91.18 83.81 92.09 77.05 79.78 78.33 83.67 79.58
##  [45] 77.78 85.38 82.11 83.50 93.89 83.73 77.10 82.21 80.00 81.67 77.43
##  [56] 89.31 79.65 85.15 83.42 81.29 88.42 91.29 85.74 75.53 79.14 88.17
##  [67] 86.47 86.10 84.55 93.37 82.43 81.29 82.65 94.09 80.00 77.74 79.49
##  [78] 86.86 82.64 83.05 84.17 83.03 83.03 93.47 80.37 84.00 88.70 85.55
##  [89] 79.61 79.85 83.32 81.89 88.79 81.85 89.23 81.43 80.78 87.06 77.13
## [100] 77.74 82.55 87.10 88.75 82.89 86.81 82.59 80.09 78.10 93.50 80.53
## [111] 80.00 81.38 86.75 81.94 80.63 85.39 90.79 79.34 82.23 90.95 81.26
## [122] 78.07 89.75 77.89 78.44 79.25 79.30 85.78 82.16 87.50 82.20 81.21
## [133] 81.60 82.03 82.16 86.23 87.32 82.07 89.90 83.38 80.18 84.52 87.96
## [144] 80.82 84.83 77.38 77.69 79.21 77.28 88.52 91.36 83.69 84.45 84.52
## [155] 89.63 82.59 93.87 74.89 80.71 84.79 84.63 80.38 80.60 78.09 87.92
## [166] 90.32 87.38 90.58 78.02 85.61 87.62 82.81 88.78 93.29 82.70 87.57
## [177] 93.49 87.21 78.68 86.06 79.33 89.77 80.94 82.44 84.12 87.06 92.90
## [188] 78.63 84.68 78.58 93.85 92.74 87.51 88.95 80.35 85.45 92.43 77.56
## [199] 88.89 83.43 88.10 84.00 79.39 81.41 82.41 89.81 81.36 88.55 85.71
## [210] 90.06 79.85 85.47 80.51 82.90 84.92 91.53 80.81 81.88 82.58 84.21
## [221] 76.23 89.50 86.85 79.53 94.44 80.65 90.85 79.32 92.79 80.90 87.29
## [232] 83.52 82.32 79.95 93.85 84.81 95.21 83.12 83.36 84.98 82.69 86.29
## [243] 91.27 86.11 83.23 81.84 81.80 86.16 83.57 87.09 88.79 80.39 84.77
## [254] 83.51 84.54 82.78 81.21 77.71 84.43 83.66 76.84 94.47 78.75 78.94
## [265] 87.10 88.85 88.42 83.86 92.21 86.65 80.08 89.35 81.64 81.13 78.34
## [276] 85.86 78.11 88.71 79.06 80.00 91.38 87.37 78.47 79.66 78.53 83.05
## [287] 85.50 81.93 81.35 88.17 88.44 86.84 83.11 82.26 81.26 82.84 77.48
## [298] 85.04 80.29 80.72 81.83 81.24 84.00 86.00 86.25 87.14 88.93 87.55
## [309] 91.60 88.26 85.81 82.86 77.77 82.60 78.96 91.23 87.50 80.25 78.26
## [320] 85.21 77.83 81.36 93.60 83.17 90.84 80.16 80.59 91.07 87.21 92.91
## [331] 88.27 92.74 85.83 82.31 81.07 84.50 78.91 92.14 83.17 91.08 87.53
## [342] 83.80 90.37 84.20 86.38 85.52 88.32 89.31 79.98 91.04 82.21 84.02
## [353] 90.45 87.79 92.45 82.00 92.15 85.63 82.56 88.60 82.45 77.36 78.30
## [364] 89.74 83.45 94.54 81.83 78.00 85.50 79.22 81.09 76.31 89.08 78.68
## [375] 87.03 92.05 92.16 87.38 84.91 88.25 90.19 84.23 83.40 86.49 81.65
## [386] 88.04 78.80 79.94 86.64 84.00 83.50 77.37 82.08 80.64 81.03 83.59
## [397] 84.96 90.68 87.96 94.30 84.97 86.00 88.28 84.23 80.72 83.88 75.46
## [408] 79.12 88.00 77.76 80.55 91.16 84.73 82.40 81.69 80.15 80.90 79.52
## [419] 93.14 95.71 79.96 84.92 85.37 87.28 80.30 79.57 82.94 88.00 87.34
## [430] 85.15 80.82 92.10 81.02 84.59 84.70 83.03 84.44 80.03 92.33 81.60
## [441] 81.52 81.41 86.74 88.71 80.54 83.78 89.20 76.65 79.77 92.60 86.63
## [452] 91.47 80.50 80.55 79.77 78.79 80.21 89.89 94.82 82.35 81.70 80.13
## [463] 82.36 93.35 90.64 86.84 80.61 83.03 79.21 88.95 77.85 81.42 94.42
## [474] 84.38 85.28 81.06 90.33 81.25 90.00 82.14 83.32 76.27 94.45 93.70
## [485] 81.21 81.36 86.16 84.33 79.82 80.34 86.38 79.91 84.08 79.64 82.28
## [496] 79.91 81.25 78.12 82.48 77.50 77.60 81.72 88.33 88.08 88.83 87.80
## [507] 92.67 88.92 89.17 88.50 88.75 87.09 85.67 88.20 81.50 92.00 84.09
## [518] 94.83 89.92 83.45 93.83 90.00 89.40 84.67 86.50 80.38 80.40 91.08
## [529] 85.92 83.00 92.54 86.08 83.75 89.67 89.58 88.50 94.33 91.33 91.50
## [540] 83.50 90.00 82.70 83.09 90.33 91.33 89.17 90.08 90.20 91.17 92.33
## [551] 89.00 95.17 91.33 84.25 92.00 93.83 90.42 85.33 84.25 85.18 82.20
## [562] 82.50 94.17 88.17 84.17 88.17 88.83 93.00 87.00 90.50 85.33 88.18
## [573] 91.67 91.00 86.00 81.33 86.33 86.50 89.60 89.67 92.17 86.75 90.17
## [584] 88.83 89.33 94.00 90.60 85.50 82.91 92.17 83.82 88.00 92.33 89.17
## [595] 83.90 84.42 95.67 84.69 92.83 84.50 86.00 85.08 90.67 88.25 89.33
## [606] 84.55 90.45 91.80 83.67 90.33 88.83 82.80 88.20 91.92 81.20 91.67
## [617] 84.45 79.46 82.17 91.50 90.60 93.67 93.67 88.17 94.33 84.83 87.08
## [628] 92.25 84.58 83.92 82.50 90.80 85.33 84.40 87.17 91.00 86.50 88.00
## [639] 84.57 86.33 86.69 86.67 86.67 90.67 85.50 88.67 94.67 84.75 82.33
## [650] 86.92 84.67 84.10 91.67 84.17 88.33 94.67 95.83 92.00 88.33

Media de los promedios de Industrial

media=mean(datos$promedio[which(datos$carrera == 'INDUSTRIAL' & datos$promedio > 0)])
media

## [1] 85.18449

varianza de los promedios de Industrial

varianza=var(datos$promedio[which(datos$carrera == 'INDUSTRIAL' & datos$promedio > 0)])
varianza

## [1] 22.27528

Desviacion estandar de Industrial

desviacionEstandar=sd(datos$promedio[which(datos$carrera == 'INDUSTRIAL' & datos$promedio > 0)])
desviacionEstandar

## [1] 4.719669

Alumnos de INFORMATICA con promedio > 0

alumnosINFORMATICA <- datos$promedio[which(datos$carrera == 'INFORMATICA' & datos$promedio > 0)]
alumnosINFORMATICA

##   [1] 84.00 87.07 84.53 82.38 81.32 87.00 81.19 91.71 92.47 83.55 86.42
##  [12] 95.67 84.48 84.22 84.67 92.29 82.79 87.86 79.24 89.78 80.50 80.59
##  [23] 77.88 87.92 77.70 82.36 82.60 84.67 85.13 89.50 82.44 82.35 85.81
##  [34] 77.12 89.10 85.12 85.30 82.73 85.06 85.92 84.96 80.26 84.75 89.45
##  [45] 86.54 89.13 84.17 79.51 80.02 79.76 77.45 79.94 82.44 79.00 90.41
##  [56] 83.82 79.25 80.09 86.64 80.04 86.76 85.57 80.45 85.92 74.67 80.24
##  [67] 78.88 92.25 78.25 80.44 82.96 78.03 90.44 85.05 95.59 81.37 80.48
##  [78] 84.29 79.30 76.36 81.36 83.72 80.43 81.96 87.66 85.79 84.32 92.43
##  [89] 80.86 91.04 78.00 81.50 82.00 85.20 86.67 86.60 86.00 84.20 80.33
## [100] 84.33 87.00 84.60 82.00 86.00 87.67 85.67 86.00 85.83 82.50 85.00
## [111] 86.50 81.25 92.67 86.17 85.00 81.83 85.33

Media de los promedios de INFORMATICA

mediaInfo=mean(datos$promedio[which(datos$carrera == 'INFORMATICA' & datos$promedio > 0)])
mediaInfo

## [1] 84.12641

varianza de los promedios de INFORMATICA

varianzaInfo=var(datos$promedio[which(datos$carrera == 'INFORMATICA' & datos$promedio > 0)])
varianzaInfo

## [1] 17.16531

Desviacion estandar de INFORMATICA

desviacionEstandarInfo=sd(datos$promedio[which(datos$carrera == 'INFORMATICA' & datos$promedio > 0)])
desviacionEstandarInfo

## [1] 4.143104

Alumnos de ELECTRICA, con promedio > 0

alumnosElectrica <- datos$promedio[which(datos$carrera == 'ELECTRICA' & datos$promedio > 0)]
alumnosElectrica

##   [1] 84.84 83.19 89.59 83.94 80.56 81.16 82.09 78.88 87.84 89.62 84.69
##  [12] 80.52 83.61 82.28 83.88 80.88 78.97 82.63 83.27 84.06 82.48 90.26
##  [23] 91.17 81.59 81.61 85.83 80.92 84.65 81.62 86.85 85.15 88.25 86.00
##  [34] 83.07 84.44 84.70 89.44 84.70 84.00 82.35 91.26 83.18 90.70 80.94
##  [45] 82.60 81.81 82.70 85.33 81.13 83.25 89.02 86.67 83.21 83.93 82.82
##  [56] 82.52 83.78 90.10 89.57 94.44 82.38 82.83 86.29 84.04 83.71 87.50
##  [67] 80.33 80.92 82.45 85.06 80.71 82.14 80.05 83.07 81.13 82.54 82.95
##  [78] 80.07 88.81 86.83 79.50 85.76 82.08 89.13 79.35 90.83 84.14 80.88
##  [89] 83.67 90.28 81.27 86.17 77.61 83.81 79.71 90.72 90.23 85.57 86.81
## [100] 84.09 84.83 78.75 83.33 85.12 82.48 88.37 82.81 88.81 88.16 84.65
## [111] 89.48 85.29 81.44 80.61 88.96 87.93 90.11 85.46 82.86 83.15 80.47
## [122] 93.23 85.02 89.00 91.47 91.95 91.16 83.19 80.69 86.84 79.92 85.32
## [133] 81.77 80.59 86.35 81.00 88.07 82.72 84.06 82.43 80.65 85.16 88.14
## [144] 82.89 81.75 81.23 82.45 81.73 80.47 84.59 86.90 85.46 81.39 84.16
## [155] 81.49 83.33 93.33 90.37 82.54 82.70 81.42 83.25 85.63 82.25 86.22
## [166] 85.22 84.71 83.75 85.14 82.90 86.28 80.55 79.59 83.31 81.82 82.76
## [177] 86.17 88.09 81.96 88.78 81.31 82.82 81.94 88.22 82.00 83.33 80.62
## [188] 80.86 80.77 84.71 82.13 82.68 86.50 91.00 88.75 85.38 88.33 90.83
## [199] 88.83 86.67 87.00 83.50 89.00 86.00 85.67 83.17 87.25 89.75 83.00
## [210] 85.60 88.00 84.67 87.25 92.83 87.50 84.67 88.33 86.67 87.80 82.33
## [221] 89.00 86.89 94.17 87.00 85.83 85.27 83.00 86.67 85.00 78.67 85.83
## [232] 90.17 86.22 87.50 86.50 85.50

Media de los promedios de ELECTRICA

mediaE=mean(datos$promedio[which(datos$carrera == 'ELECTRICA' & datos$promedio > 0)])
mediaE

## [1] 84.78487

varianza de los promedios de ELECTRICA

varianzaE=var(datos$promedio[which(datos$carrera == 'ELECTRICA' & datos$promedio > 0)])
varianzaE

## [1] 11.64047

Desviacion estandar de ELECTRICA

desviacionEstandarE=sd(datos$promedio[which(datos$carrera == 'ELECTRICA' & datos$promedio > 0)])
desviacionEstandarE

## [1] 3.411814

Alumnos de SISTEMAS con promedio > 0

alumnosSistemas <- datos$promedio[which(datos$carrera == 'SISTEMAS' & datos$promedio > 0)]
alumnosSistemas

##   [1] 83.51 87.37 81.57 90.06 85.85 84.00 89.27 84.54 81.59 95.26 94.10
##  [12] 84.82 85.65 87.86 81.29 90.94 83.90 83.27 78.90 89.59 86.90 92.50
##  [23] 84.14 79.74 79.29 83.10 83.38 89.17 79.20 88.71 92.65 94.70 81.52
##  [34] 97.13 77.64 82.75 89.22 82.33 82.30 80.72 80.04 86.03 80.20 85.97
##  [45] 82.72 82.33 94.50 81.82 87.02 94.61 86.15 81.60 87.94 87.10 82.14
##  [56] 84.40 78.50 85.22 84.42 84.13 89.50 89.39 92.32 81.80 87.00 79.94
##  [67] 77.31 91.46 84.92 93.25 85.17 88.10 84.32 87.30 73.11 86.11 83.14
##  [78] 79.11 78.67 80.00 86.19 93.62 90.58 83.11 82.34 86.93 87.36 81.60
##  [89] 87.00 81.40 85.68 82.27 89.61 90.88 83.81 83.53 83.46 81.04 83.53
## [100] 82.56 91.11 80.14 86.23 79.68 81.19 83.83 84.50 79.46 81.59 84.11
## [111] 84.15 86.62 84.72 85.13 85.79 84.50 84.73 89.69 89.85 83.24 80.86
## [122] 79.32 83.73 93.39 84.44 84.54 91.82 90.87 85.81 85.17 84.58 79.21
## [133] 88.83 88.71 80.88 81.46 84.15 93.42 83.81 80.93 82.12 89.74 83.69
## [144] 83.43 82.50 89.00 93.18 90.31 85.95 83.97 90.94 91.94 81.56 79.70
## [155] 94.22 84.15 87.41 81.50 82.28 90.38 91.19 82.92 79.14 77.81 84.49
## [166] 76.50 85.87 86.91 79.64 85.19 85.70 87.61 80.52 78.25 80.43 80.87
## [177] 81.85 84.72 82.66 84.44 82.56 85.49 91.44 87.98 93.89 89.43 90.87
## [188] 81.03 82.33 84.63 82.16 87.73 86.66 91.39 84.89 86.64 83.38 89.93
## [199] 81.81 83.56 82.07 91.44 93.20 83.33 95.49 82.43 74.79 84.28 83.87
## [210] 83.16 87.00 84.43 82.92 87.40 86.33 86.61 81.54 77.42 87.22 86.28
## [221] 79.06 79.05 85.32 85.91 90.18 85.94 86.48 82.45 83.59 85.05 75.98
## [232] 82.69 84.13 77.88 83.79 81.82 81.11 89.03 91.83 83.41 92.02 84.37
## [243] 92.30 87.53 80.05 94.89 80.36 91.11 82.03 78.39 83.91 86.87 87.90
## [254] 84.04 82.85 91.83 89.53 85.77 87.30 80.26 82.55 93.50 85.70 79.83
## [265] 80.49 86.35 80.50 83.67 86.00 84.62 85.90 86.32 91.29 84.96 84.28
## [276] 82.21 77.54 79.05 87.50 79.61 81.54 89.28 90.78 85.35 81.38 77.67
## [287] 80.50 84.50 80.80 88.33 79.20 83.67 88.33 90.83 88.25 79.44 85.20
## [298] 81.11 86.67 94.83 82.60 76.67 89.83 77.67 83.20 92.00 84.09 89.50
## [309] 92.50 89.67 89.00 82.20 86.33 82.50 77.50 81.11 84.80 88.64 93.33
## [320] 86.09 80.30 90.67 81.50 81.78 93.00 86.82 81.33 78.40 85.80 87.40
## [331] 85.33 80.60 78.00 81.00 87.00 83.22 87.80 91.67 81.22 80.09 79.75
## [342] 82.17 79.60 83.82 78.56 83.33 87.36 89.00 87.00 87.83 84.09 85.67
## [353] 86.00 84.67 83.64 80.09 85.50 82.60 83.00 89.67 81.90 82.33 83.42
## [364] 86.33 84.73 84.10 88.50 81.20 77.00 82.25 77.00 82.80 80.50 92.50
## [375] 79.83 92.00 82.00 82.33 82.80 81.80 85.11 86.20 73.50 78.20 81.90
## [386] 82.25 84.60 85.25 80.45 82.09 88.33 87.00 81.00 85.33 88.20 81.33
## [397] 85.75 80.50 77.88 78.38 80.67 77.60 88.00 87.20 82.11 82.33 80.00
## [408] 83.00 88.50 84.00 85.10

Media de los promedios de SISTEMAS

mediaS=mean(datos$promedio[which(datos$carrera == 'SISTEMAS' & datos$promedio > 0)])
mediaS

## [1] 84.73406

varianza de los promedios de SISTEMAS

varianzaS=var(datos$promedio[which(datos$carrera == 'SISTEMAS' & datos$promedio > 0)])
varianzaS

## [1] 18.9757

Desviacion estandar de SISTEMAS

desviacionEstandarS=sd(datos$promedio[which(datos$carrera == 'SISTEMAS' & datos$promedio > 0)])
desviacionEstandarS

## [1] 4.356111

Valores de las medias de las carreras

carreras=c(media,mediaInfo,mediaE,mediaS)
color=c("gray90","gray75","gray60","gray45")
leyenda=c("Industrial","Informatica","Electrica","Sistemas")
barplot(carreras,col=color,main="Medias De las Carreras",ylab="Medias",xlab="Carreras",legend.text = leyenda,args.legend = list(x="bottomright"))

Varianza

varianzaC=c(varianzaS,varianzaE,varianzaInfo,varianza)
color=c("gray90","gray75","gray60","gray45")
leyenda=c("Sistemas","Electronica","Informatica","Industrial")
barplot(varianzaC,col=color,main="Varianza De las Carreras",ylab="Varianzas",xlab="Carreras",legend.text = leyenda,args.legend = list(x="bottomright"))

Coeficientee de varianza Industrial

cfi<-desviacionEstandar/media*100
cfi

## [1] 5.540526

Coeficiente de varianza electrica

cfe<-desviacionEstandarE/mediaE*100
cfe

## [1] 4.024083

Coeficiente de varianza informatica

cfin<-desviacionEstandarInfo/mediaInfo*100
cfin

## [1] 4.924855

Coeficiente de varianza Sistemas

cfs<-desviacionEstandarS/mediaS*100
cfs

## [1] 5.140921

Coeficiente de varianza grafica de las carreras

graficavar<-c(cfi,cfe,cfin,cfs)
color=c("gray90","gray75","gray60","gray45")
leyenda=c("Industrial","Electrica","Informatica","Sistemas")
barplot(graficavar,col=color,main="Coeficiente de varianza De las Carreras",ylab="Coeficiente de varianza",xlab="Carreras",legend.text = leyenda,args.legend = list(x="bottomright"))

Como se puede ver en la grafica el coeficiente de varianza de las calificaciones de industrial (5.54) es mayor que las demas y el que demuestra menor coeficiente de varianza es ingenieria electrica (4.02) despues le sigue informatica (4.52) y en segundo lugar quedaria sistemas (5.14)