mmajogn

#moda#

x<-c(3.0,5.8,5.6,4.8,5.1,3.6,5.5,4.7,5.7,5.0,5.9,5.7,4.4,5.4,4.2,5.3)
sort(x, decreasing=TRUE)
[1] 5.9 5.8 5.7 5.7 5.6 5.5 5.4 5.3 5.1 5.0 4.8 4.7 4.4 4.2 3.6 3.0
y <- 5.7
y
plot(x, col="blue", ylab="Eje Y", xlab="Eje X", main="Moda de datos")
points(y, col="brown")

mmajogn

#sd#

x<-c(3.0,5.8,5.6,4.8,5.1,3.6,5.5,4.7,5.7,5.0,5.9,5.7,4.4,5.4,4.2,5.3,0.3,0.14)
plot(x)
y<-sd(x)
y
plot(x, col="blue", ylab="Eje Y", xlab="Eje X", main="Desviacion estandar de datos")
points(y, col="purple")

mmajogn

#varianza#

x<-c(3.0,5.8,5.6,4.8,5.1,3.6,5.5,4.7,5.7,5.0,5.9,5.7,4.4,5.4,4.2,5.3,0.3,0.14)
plot(x)
k<-var(x)
k
plot(x, col="blue", ylab="Eje Y", xlab="Eje X", main="Varianza de datos")
points(k, col="green")

mmajogn

#median#

x<-c(3.0,5.8,5.6,4.8,5.1,3.6,5.5,4.7,5.7,5.0,5.9,5.7,4.4,5.4,4.2,5.3)
plot(x)
z<-median(x)
z
plot(x, col="blue", ylab="Eje Y", xlab="Eje X", main="Mediana de datos")
median(x)

mmajogn

#mean#

x<-c(3.0,5.8,5.6,4.8,5.1,3.6,5.5,4.7,5.7,5.0,5.9,5.7,4.4,5.4,4.2,5.3)
plot(x)
y<-mean(x)
y
plot(x, col="blue", ylab="Eje Y", xlab="Eje X", main="Media de datos")
points(y, col="red")

mmajogn

#Gráfica de jitter#
install.packages("HistData")
library(HistData)
data(Galton)
plot(Galton)
plot(jitter(Galton$parent), Galton$child))
plot(jitter(Galton$parent), Galton$child)
plot(jitter(Galton$parent), jitter(Galton$child))
plot(jitter(Galton$parent), jitter(Galton$child), main="Grafica de funcion jitter")

mmajogn

#Gráfica de girasol#
install.packages("HistData")
library(HistData)
data(Galton)
head(Galton)
sunflowerplot(Galton)
sunflowerplot(Galton, cex=.5, col="brown", seg.lwd=1.5, seg.col="purple", main="Grafica de girasol", xlab="Padres", ylab="Ninios")

mmajogn

#Gráficas de burbuja#
crime <- read.csv("http://datasets.flowingdata.com/crimeRatesByState2005.tsv", header=TRUE, sep="\t")
symbols(crime$murder, crime$burglary, circles=crime$population)
radius <- sqrt( crime$population/ pi )
symbols(crime$murder, crime$burglary, circles=radius)
symbols(crime$murder, crime$burglary, circles=radius, inches=0.35, fg="white", bg="orange", xlab="Murder Rate", ylab="Burglary Rate", main="Grafica de burbujas")

mmajogn

#Gráficas de burbuja#
crime <- read.csv("http://datasets.flowingdata.com/crimeRatesByState2005.tsv", header=TRUE, sep="\t")
symbols(crime$murder, crime$burglary, circles=crime$population)
radius <- sqrt( crime$population/ pi )
symbols(crime$murder, crime$burglary, circles=radius)
symbols(crime$murder, crime$burglary, circles=radius, inches=0.35, fg="white", bg="orange", xlab="Murder Rate", ylab="Burglary Rate")

mmajogn

#Gráfica en .R points#
x<--10:10
y<-x^2
plot(x,y)
points(0, 30)
y2<-0.5*x^2
plot(x,y2,type="p")
points(x,y,type="p")
plot(x,y, col="orange")
plot(x,y,pch=18, , main="Grafica en .R points")