Várias funções que utilizo no R

Seguem algumas funções que normalmente utilizo nos meus artigos.
O R pode ser obtido de http://cran.r-project.org/.

Ler arquivo

f = read.table(file="C:\\Downloads\\resultado.txt",sep=";",header=TRUE)
separador enter coluna o ";"
separador decimal o "."

Mostrar informações estatísticas

> summary(f)
      CPU                ON               AMAZON    
 Min.   :0.05239   Min.   :0.005996   Min.   :0.05323
 1st Qu.:0.12850   1st Qu.:0.132863   1st Qu.:0.13046
 Median :0.14586   Median :0.150601   Median :0.15615
 Mean   :0.22330   Mean   :0.323834   Mean   :0.61537
 3rd Qu.:0.18229   3rd Qu.:0.186492   3rd Qu.:0.27418
 Max.   :6.74142   Max.   :6.567323   Max.   :6.49501

Desvio padrão

> sd(f)
      CPU        ON    AMAZON
0.4042940 0.7079139 1.1460376

Erro padrão médio 

> 100*sd(f)/mean(f)
     CPU       ON   AMAZON
181.0572 218.6043 186.2357

Gráficos

> boxplot(f)
> hist(f$CPU)
> hist(f$ON)
> hist(f$AMAZON)
> plot(f$CPU)
> plot(f$ON)
> plot(f$AMAZON)
> matplot(f, type = 'l')

par(mfrow=c(1,3))
par(ps=18)
plot(f$CPU, col=2, xlab="CPU", ylab="Segundos")
plot(f$ON, col=3, xlab="MV Privada", ylab="Segundos")
plot(f$AMAZON, col=4, xlab="MV Pública", ylab="Segundos")

par(mfrow=c(1,3))
par(ps=18)
boxplot(f$CPU, col=2, xlab="CPU", ylab="Segundos")
boxplot(f$ON, col=3, xlab="MV Privada", ylab="Segundos")
boxplot(f$AMAZON, col=4, xlab="MV Pública", ylab="Segundos")

par(mfrow=c(1,3))
par(ps=18)
hist(f$CPU, col=2, xlab="CPU", ylab="Segundos")
hist(f$ON, col=3, xlab="MV Privada", ylab="Segundos")
hist(f$AMAZON, col=4, xlab="MV Pública", ylab="Segundos")

par(mfrow=c(1,3))
par(ps=18)
matplot(f$CPU, type="l", col=2, xlab="CPU", ylab="Segundos")
matplot(f$ON, type="l", col=3, xlab="MV Privada", ylab="Segundos")
matplot(f$AMAZON, type="l", col=4, xlab="MV Pública", ylab="Segundos")

Intervalo de confiança

> t.test(f$CPU)

        One Sample t-test

data:  f$CPU
t = 38.1655, df = 4774, p-value < 2.2e-16
alternative hypothesis: true mean is not equal to 0
95 percent confidence interval:
 0.2118261 0.2347664
sample estimates:
mean of x
0.2232962

> t.test(f$ON)

        One Sample t-test

data:  f$ON
t = 31.6103, df = 4774, p-value < 2.2e-16
alternative hypothesis: true mean is not equal to 0
95 percent confidence interval:
 0.3037495 0.3439176
sample estimates:
mean of x
0.3238335

> t.test(f$AMAZON)

        One Sample t-test

data:  f$AMAZON
t = 37.1043, df = 4774, p-value < 2.2e-16
alternative hypothesis: true mean is not equal to 0
95 percent confidence interval:
 0.5828555 0.6478835
sample estimates:
mean of x
0.6153695