Pengendalian Statistik MEET 2

# 1. Analisis Deskriptif
mean(morley$Speed)

## [1] 852.4

var(morley$Speed)

## [1] 6242.667

sqrt(var(morley$Speed))

## [1] 79.01055

range(morley$Speed) - min(morley$Speed)

## [1]   0 450

quantile(morley$Speed, c(0.25, 0.5, 0.75))

##   25%   50%   75% 
## 807.5 850.0 892.5

stem(morley$Speed)

## 
##   The decimal point is 2 digit(s) to the right of the |
## 
##    6 | 2
##    6 | 5
##    7 | 222444
##    7 | 566666788999
##    8 | 000001111111111223344444444
##    8 | 5555555566677778888888888999
##    9 | 0011233444
##    9 | 55566667888
##   10 | 000
##   10 | 7

hist(morley$Speed)

boxplot(morley$Speed)

# 2. Distribusi Frekuensi (Aturan Sturges)
n <- length(morley$Speed)
sturgess <- 1 + 3.3 * log10(n)
kelas <- round(sturgess) + 1
breaks <- seq(min(morley$Speed), max(morley$Speed), length.out = kelas)

as.data.frame(table(cut(morley$Speed, breaks = breaks)))

##                  Var1 Freq
## 1           (620,676]    1
## 2           (676,732]    3
## 3           (732,789]   12
## 4           (789,845]   30
## 5           (845,901]   30
## 6           (901,958]   11
## 7      (958,1.01e+03]   11
## 8 (1.01e+03,1.07e+03]    1

# 3. Histogram kustom
breaks_custom <- seq(600, 1100, by = 50)
hist(morley$Speed, breaks = breaks_custom)