INTRODUCCION

A CONTINUACION SE PRESENTAN LAS ESTADISTICAS BASICAS POSTERIORMENTE SE OBSERVARA COMO REALIZAR LOS CALCULOS CON R_estudio http://rmarkdown.rstudio.com.

Medidas de tendencia central

Moda Mediana Promedio

#generamos datos
#rnorm: sirve para generar datos(a,b,c)> a: numero de datos, b: la media que se simula, c: la desviacion standar
#En este caso estoy generando para "x" he genarado 100 datos, con simulacion de media 10 y desviacion 2 y lo mismo para "y" y para "z" he sacado las difrencias de x - y
#as.factor: permite categorizar datos de una variable nominal este caso he generado w: y he pedido que genere 15 datos con categoria "A",50"B"y35 "C"
x=rnorm(100,10,2)
y=rnorm(100,5,1)
z=x-y
w=as.factor(c(rep("A",15), rep("B",50),rep("c",35)))
#crear data con data.frame
datapro=data.frame(x,y,z,w)
View(datapro)
datapro
##             x        y          z w
## 1   12.117121 4.903525  7.2135964 A
## 2   10.503115 4.619116  5.8839998 A
## 3    9.383837 3.465039  5.9187978 A
## 4   10.687263 6.788587  3.8986762 A
## 5    9.166585 5.294623  3.8719620 A
## 6    9.142840 5.302826  3.8400142 A
## 7    9.963923 4.494240  5.4696836 A
## 8    8.999813 6.899405  2.1004082 A
## 9   10.308462 5.872485  4.4359769 A
## 10  10.820497 3.911069  6.9094285 A
## 11   8.495810 5.038954  3.4568563 A
## 12   9.930799 5.540796  4.3900031 A
## 13  10.050826 3.774987  6.2758392 A
## 14  11.997140 4.585846  7.4112939 A
## 15  10.507549 4.481287  6.0262619 A
## 16   9.701724 5.399341  4.3023835 B
## 17   8.252645 4.462720  3.7899250 B
## 18  12.960469 3.988233  8.9722360 B
## 19  12.721535 5.609068  7.1124667 B
## 20  10.642315 5.191765  5.4505500 B
## 21  11.704611 4.399064  7.3055472 B
## 22  13.154405 5.458599  7.6958069 B
## 23   9.389512 4.068850  5.3206616 B
## 24  11.256755 6.660682  4.5960727 B
## 25   9.626749 4.519231  5.1075186 B
## 26  11.477761 5.444883  6.0328774 B
## 27  10.838335 4.240635  6.5977004 B
## 28  11.790133 5.266427  6.5237063 B
## 29   7.003170 2.946019  4.0571506 B
## 30  12.987587 3.440104  9.5474829 B
## 31  10.462421 6.721026  3.7413952 B
## 32  10.258296 5.204904  5.0533918 B
## 33  11.130927 5.086713  6.0442143 B
## 34   8.099231 3.597336  4.5018950 B
## 35   7.830680 6.077269  1.7534111 B
## 36  11.240634 4.690631  6.5500039 B
## 37  10.657558 4.692644  5.9649141 B
## 38   6.734003 5.080531  1.6534722 B
## 39  13.154309 6.232300  6.9220083 B
## 40   9.442885 3.314773  6.1281125 B
## 41  10.563499 2.945081  7.6184172 B
## 42  12.616793 4.840405  7.7763879 B
## 43   7.675929 6.380883  1.2950457 B
## 44   8.491870 4.099526  4.3923444 B
## 45  11.772085 7.003648  4.7684361 B
## 46  10.187947 6.023077  4.1648706 B
## 47  10.170455 6.100078  4.0703763 B
## 48  11.439360 5.063248  6.3761128 B
## 49   7.498857 5.470771  2.0280853 B
## 50   6.611952 6.360715  0.2512372 B
## 51   9.272807 4.883241  4.3895662 B
## 52   7.207912 4.568196  2.6397154 B
## 53  10.989556 6.767829  4.2217265 B
## 54   8.535457 5.136879  3.3985777 B
## 55  10.117885 4.993911  5.1239741 B
## 56   9.815649 5.531545  4.2841039 B
## 57  13.410256 4.701589  8.7086669 B
## 58   8.453436 5.298584  3.1548526 B
## 59  11.968051 4.009386  7.9586656 B
## 60  13.276186 5.954459  7.3217278 B
## 61  14.551390 4.745657  9.8057332 B
## 62   7.317045 2.845258  4.4717862 B
## 63  13.029721 4.380970  8.6487514 B
## 64  11.045091 4.223773  6.8213181 B
## 65  12.410625 5.420403  6.9902226 B
## 66   8.690208 4.549141  4.1410677 c
## 67   8.956512 6.151104  2.8054079 c
## 68  11.037324 4.754910  6.2824140 c
## 69   9.816396 3.760486  6.0559091 c
## 70  11.432498 4.424879  7.0076185 c
## 71   8.508542 4.666950  3.8415920 c
## 72   5.818231 6.368600 -0.5503695 c
## 73  11.132177 4.720847  6.4113301 c
## 74  10.808561 3.848324  6.9602369 c
## 75   7.181836 6.722806  0.4590309 c
## 76  11.561883 5.019795  6.5420877 c
## 77   8.237405 5.953666  2.2837388 c
## 78  14.350181 4.882916  9.4672646 c
## 79   9.848830 4.128405  5.7204252 c
## 80  10.343584 4.807443  5.5361416 c
## 81  13.473277 3.490980  9.9822968 c
## 82   7.760757 3.817501  3.9432557 c
## 83   7.853419 5.348448  2.5049706 c
## 84   6.826847 5.913320  0.9135277 c
## 85  10.128647 4.923836  5.2048114 c
## 86  10.117705 4.883440  5.2342658 c
## 87   9.524848 4.731212  4.7936362 c
## 88   9.072948 4.221606  4.8513418 c
## 89   9.223100 5.487536  3.7355635 c
## 90   7.715994 5.786928  1.9290661 c
## 91  11.116703 5.752441  5.3642622 c
## 92  12.515027 4.355751  8.1592759 c
## 93  10.591193 4.112982  6.4782113 c
## 94  11.157568 4.351844  6.8057244 c
## 95   7.202025 4.890398  2.3116265 c
## 96  12.558109 4.604003  7.9541060 c
## 97   9.871751 5.222651  4.6490992 c
## 98   9.292319 5.980909  3.3114097 c
## 99  12.336000 6.802405  5.5335950 c
## 100  7.415827 5.043870  2.3719568 c
#promedio de las variables
mean(x)
## [1] 10.16502
mean(y)
## [1] 4.98998
mean(z)
## [1] 5.175043
#moda
mode(x)
## [1] "numeric"
mode(y)
## [1] "numeric"
#mediana
median(x)
## [1] 10.1792
median(y)
## [1] 4.896961
#Histogramas
#hist: sirve para realizar histogramas(x= se coloca la variable de la data que se quiere haccer el histograma, en este caso he simulado datos y "x" es mi variable de interes, col: permite darle color al histograma, ylim:permite limitar el eje "Y": en este caso he puesto que el eje "y" sea de 0 a 30, xlab: permite poner nombre a los ejes, main: permite darle nombre al histograma)
hist(x=x, col="green",ylim = c(0,30),
     xlab = "ALUMNOS",
     ylab = "PROMEDIO",
     main = "DistribuCION DE PROMEDIO DE ALUMNOS")

#Grafico de dispersion, polt: permite realizar grafico de dispersion
plot(x,y)

plot(x,y, main="Gráfico de dispersión")

plot(x,y, main="Grafico de dispersion", pch=16)

plot(x,y, main="Grafico de dispersion", pch=16, col="orange")

plot(x,y, main="Grafico de dispersion", pch=17, col="blue", cex=2)

plot(x,y, main="Grafico de dispersion", pch=20, cex=2, col="red", bg="yellow")

plot(x,y, main="Grafico de dispersion", pch=17, cex=2, lwd=5, col="blue", bg="yellow",
     sub = "grafico de dispersión")

plot(x,y, main="Grafico de dispersion", pch=16, col=w)

#par:permite ingresar varios grafico en uno
par(mfrow=c(1,3))
boxplot(x, main="grafico de boxplot")
boxplot(x, main="grafico de boxplot", col="red")
boxplot(x, main="grafico de boxplot", col="red", ylab="promedio")

par(mfrow=c(1,1))
boxplot(x~w)

boxplot(x~w, col=c("red","green"))

boxplot(x~w, col=c("red","green"), main = "boxplot",
        xlab = "grupos", ylab = "promedio")
#graficos con ggplot2, primero intalar ggplot2
library(ggplot2)

ggplot(data = datapro, aes(x=x, y=y, color=w)) +
  geom_point()