1. Simulace alternativného rozdělení

sample(c(0, 1), size = 1000, replace = TRUE)

##    [1] 0 1 1 1 1 1 0 0 1 0 0 1 1 1 0 1 0 1 1 1 0 0 0 0 0 1 0 1 0 1 1 1 0 1 0 1 1
##   [38] 1 1 1 0 0 0 1 0 0 0 1 1 1 0 1 1 1 0 1 1 1 1 0 0 1 1 0 0 0 0 1 1 0 1 1 1 1
##   [75] 0 0 0 0 1 1 0 1 1 0 0 0 1 0 1 0 1 0 1 1 0 1 0 0 1 1 1 0 0 1 1 1 1 1 1 0 0
##  [112] 1 1 1 0 0 0 1 0 0 1 0 0 1 0 1 0 1 1 0 0 0 1 0 1 1 0 0 0 0 1 1 0 0 1 1 0 0
##  [149] 1 0 1 1 0 1 0 1 1 0 0 0 1 0 0 1 1 1 0 1 1 1 0 0 1 1 0 0 0 1 1 0 1 0 1 1 1
##  [186] 0 0 1 0 1 0 1 0 0 0 0 1 1 0 0 1 0 1 0 1 0 0 1 1 0 0 0 1 0 0 1 0 0 1 0 0 1
##  [223] 1 1 0 1 0 0 1 0 1 1 0 1 1 1 0 0 0 0 0 1 1 0 1 0 0 1 0 0 0 0 0 1 0 1 0 0 0
##  [260] 1 0 0 1 0 1 0 1 1 1 1 0 1 0 1 1 0 0 0 1 1 1 0 0 1 0 1 0 1 0 1 1 0 0 1 0 0
##  [297] 1 1 0 0 1 1 0 1 1 1 0 0 1 1 0 0 0 0 1 1 0 0 0 0 1 1 1 1 0 1 0 1 1 0 0 1 1
##  [334] 0 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 0 0 0 0 1 0 1 1 0 1 1 1 1 1 0 0 1 0 0 0
##  [371] 1 0 0 1 1 0 1 1 1 1 0 1 1 0 1 0 0 1 0 1 0 0 0 1 1 0 1 0 0 0 1 1 1 1 1 1 1
##  [408] 0 0 1 0 1 1 1 0 1 1 1 1 0 0 1 1 1 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0 1 0 0 1 0
##  [445] 1 0 0 0 1 1 1 1 1 0 1 0 1 1 0 0 1 0 1 1 0 1 0 0 1 1 1 1 0 0 0 0 1 0 1 1 1
##  [482] 0 1 1 0 1 0 1 0 1 0 0 0 1 0 1 0 1 1 0 1 0 1 0 0 1 1 0 1 0 0 1 0 1 1 1 0 1
##  [519] 0 1 1 0 1 1 1 0 1 1 0 1 0 1 1 1 0 1 0 0 1 0 0 0 0 0 0 1 1 0 0 1 0 0 1 0 1
##  [556] 1 1 1 0 0 0 0 1 0 0 0 1 0 1 1 0 0 1 0 0 0 1 0 0 1 1 1 0 0 1 0 0 1 1 0 1 1
##  [593] 1 1 0 1 1 0 0 0 1 1 1 1 1 0 0 0 0 1 1 1 1 1 1 0 1 1 0 1 1 1 0 0 1 0 0 1 0
##  [630] 1 1 0 0 1 0 1 0 0 1 1 1 1 1 0 1 0 1 0 1 1 1 0 0 1 0 1 1 0 0 0 0 1 0 1 0 0
##  [667] 0 1 1 1 1 0 1 1 0 0 0 0 1 0 0 1 1 0 1 0 1 1 1 0 0 1 0 0 1 1 0 1 0 1 1 1 1
##  [704] 0 0 0 0 0 0 1 0 0 1 1 1 0 1 1 0 1 0 1 1 1 1 0 0 0 1 1 1 1 1 1 0 0 0 0 1 1
##  [741] 0 0 1 0 0 1 1 0 0 1 0 0 0 1 0 1 1 1 1 1 0 1 0 1 1 1 0 0 1 1 0 0 0 0 0 0 1
##  [778] 0 0 0 0 0 0 0 0 0 1 1 1 1 0 0 1 0 1 0 1 0 0 1 1 1 0 0 0 0 0 0 0 1 0 0 1 1
##  [815] 0 1 0 1 1 0 0 1 1 1 0 1 0 0 1 1 1 1 1 0 1 1 0 0 0 0 0 1 0 1 0 0 0 0 0 1 1
##  [852] 1 0 0 1 1 0 1 0 1 1 0 0 0 0 1 1 1 1 0 0 0 0 0 1 0 0 1 0 0 1 0 0 1 0 0 1 0
##  [889] 1 0 0 1 1 0 1 1 1 0 0 1 0 0 0 0 1 1 0 1 1 1 1 1 0 0 1 0 0 0 0 1 0 1 1 0 1
##  [926] 0 1 1 1 0 0 0 1 0 1 1 1 0 0 1 0 0 1 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 1 0 0 0
##  [963] 0 0 0 1 1 0 0 1 0 1 0 0 1 0 1 1 1 0 0 1 1 0 1 1 0 0 1 1 1 0 1 0 0 1 0 1 1
## [1000] 1

barplot(table(sample(c(0, 1), size = 1000, replace = TRUE)), xlab = "číslo", ylab = "četnost", main = "Hody mincí")

2. Deskriptivní analýza výšek studentů Statistiky I

data <- read.csv("data_vyska.txt")

mean(data$vyska) #průměr

## [1] 170.9797

median(data$vyska) #medián

## [1] 169

sd(data$vyska) #směrodatná odchylka

## [1] 9.467914

var(data$vyska) #rozptyl

## [1] 89.6414

quantile(data$vyska, probs = c(0.25, 0.75))  # dolní kvartil, horní kvartil

## 25% 75% 
## 164 177

quantile(data$vyska, probs = c(0.5)) 

## 50% 
## 169

hist(data$vyska) #histogram

boxplot(data$vyska) #krabicový graf