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STATISTIKA DESKRIPTIF

tugas<-read.csv("C:/Users/Saintek9/Downloads/iris.csv",header= TRUE)
head(tugas)
##   Id SepalLengthCm SepalWidthCm PetalLengthCm PetalWidthCm     Species
## 1  1           5.1          3.5           1.4          0.2 Iris-setosa
## 2  2           4.9          3.0           1.4          0.2 Iris-setosa
## 3  3           4.7          3.2           1.3          0.2 Iris-setosa
## 4  4           4.6          3.1           1.5          0.2 Iris-setosa
## 5  5           5.0          3.6           1.4          0.2 Iris-setosa
## 6  6           5.4          3.9           1.7          0.4 Iris-setosa

Statistik

Mean, Q1, Median, Mean, Q3, Minimal, dan Maximal

summary(tugas)
##        Id         SepalLengthCm    SepalWidthCm   PetalLengthCm  
##  Min.   :  1.00   Min.   :4.300   Min.   :2.000   Min.   :1.000  
##  1st Qu.: 38.25   1st Qu.:5.100   1st Qu.:2.800   1st Qu.:1.600  
##  Median : 75.50   Median :5.800   Median :3.000   Median :4.350  
##  Mean   : 75.50   Mean   :5.843   Mean   :3.054   Mean   :3.759  
##  3rd Qu.:112.75   3rd Qu.:6.400   3rd Qu.:3.300   3rd Qu.:5.100  
##  Max.   :150.00   Max.   :7.900   Max.   :4.400   Max.   :6.900  
##   PetalWidthCm     Species         
##  Min.   :0.100   Length:150        
##  1st Qu.:0.300   Class :character  
##  Median :1.300   Mode  :character  
##  Mean   :1.199                     
##  3rd Qu.:1.800                     
##  Max.   :2.500

Modus

modus <- function(x){
  uniqx<- unique(x)
  uniqx[which.max(tabulate(match(x, uniqx)))]
}
modus(tugas$SepalLengthCm)
## [1] 5
modus(tugas$SepalWidthCm)
## [1] 3
modus(tugas$PetalLengthCm)
## [1] 1.5
modus(tugas$PetalWidthCm)
## [1] 0.2
modus(tugas$Species)
## [1] "Iris-setosa"

Rata-rata Geometri

mn.geom <-  function(x){
  exp(mean(log(x)))
}
mn.geom(tugas$SepalLengthCm)
## [1] 5.78572
mn.geom(tugas$SepalWidthCm)
## [1] 3.023582
mn.geom(tugas$PetalLengthCm)
## [1] 3.239757
mn.geom(tugas$PetalWidthCm)
## [1] 0.837827

Rata-rata Harmoni

harmoni<- function(x){
  1/(mean(1/x))
}
harmoni(tugas$SepalLengthCm)
## [1] 5.728905
harmoni(tugas$SepalWidthCm)
## [1] 2.993137
harmoni(tugas$PetalLengthCm)
## [1] 2.696472
harmoni(tugas$PetalWidthCm)
## [1] 0.4866465

Skewness dan Kurtosis

library(e1071)
skewness(tugas$SepalLengthCm)
## [1] 0.3086407
skewness(tugas$SepalWidthCm)
## [1] 0.3274013
skewness(tugas$PetalLengthCm)
## [1] -0.2689994
skewness(tugas$PetalWidthCm)
## [1] -0.102906
kurtosis(tugas$SepalLengthCm)
## [1] -0.6058125
kurtosis(tugas$SepalWidthCm)
## [1] 0.1983681
kurtosis(tugas$PetalLengthCm)
## [1] -1.416683
kurtosis(tugas$PetalWidthCm)
## [1] -1.357368

Menampilkan Grafik

Boxplot

boxplot(tugas$SepalLengthCm, xlab="Sepal Length", ylab="cm", col = "pink")

boxplot(tugas$SepalWidthCm, xlab="Sepal Width", ylab="cm", col = "skyblue")

boxplot(tugas$PetalLengthCm, xlab="Petal Length", ylab="cm", col = "darkseagreen1")

boxplot(tugas$PetalWidthCm, xlab="Petal Width", ylab="cm", col = "darkslategray1")

bp <- cbind(tugas$SepalLengthCm , tugas$SepalWidthCm , tugas$PetalLengthCm , tugas$PetalWidthCm)
boxplot(bp, xlab="grup", ylab="cm",col=c("pink","skyblue","darkseagreen1","darkslategray1"))

Histogram

par(mfrow = c(2, 2))
hist(tugas$SepalLengthCm, main = "Sepal Length",xlab = "Sepal Legth (cm) ", col = "lavenderblush" )
hist(tugas$SepalWidthCm, main = "Sepal Width",xlab = "Sepal Width (cm)", col = "lightcyan")
hist(tugas$PetalLengthCm, main = "Petal Length",xlab = "Petal Length (cm)", col = "lightpink")
hist(tugas$PetalWidthCm, main = "Petal Width",xlab = "Petal Width (cm)", col = "lightsalmon")

Scatter PLot

par(mfrow = c(2, 2))
plot(tugas$SepalLengthCm,tugas$SepalWidthCm, pch = 19, cex = 0.8, frame = FALSE, xlab = "Sepal Length", ylab = "Sepal Width", main ="Korelasi", col="blue")
plot(tugas$SepalLengthCm,tugas$PetalLengthCm, pch = 19, cex = 0.8, frame = FALSE, xlab = "Sepal Length", ylab = "Petal Length", main ="Korelasi", col="lightsalmon")
plot(tugas$SepalLengthCm,tugas$PetalWidthCm, pch = 19, cex = 0.8, frame = FALSE, xlab = "Sepal Length", ylab = "Petal Width", main ="Korelasi", col="palegreen")
plot(tugas$SepalWidthCm,tugas$PetalLengthCm, pch = 19, cex = 0.8, frame = FALSE, xlab = "Sepal Width", ylab = "Petal Length", main ="Korelasi", col="mistyrose" )

par(mfrow = c(2, 2))
plot(tugas$SepalWidthCm,tugas$PetalWidthCm, pch = 19, cex = 0.8, frame = FALSE, xlab = "Sepal Width", ylab = "Petal Width", main ="Korelasi", col="lightsalmon" )
plot(tugas$PetalLengthCm,tugas$PetalWidthCm, pch = 19, cex = 0.8, frame = FALSE, xlab = "Petal Length", ylab = "Petal Width", main ="Korelasi", col="palegreen" )

Diagram Batang

barplot(tugas$SepalLengthCm, names.arg = "Sepal Length", col="lavenderblush")

barplot(tugas$SepalWidthCm, names.arg = "Sepal Length", col="skyblue")

barplot(tugas$PetalLengthCm, names.arg = "Sepal Length", col="lightsalmon")

barplot(tugas$PetalLengthCm, names.arg = "Sepal Length", col="lightgreen")

Pie Chart

library(plotrix)
dl <- c("Iris Sentosa", "Iris Versi Color", "Iris Virginica")

pie(table(tugas$Species), col = c("darkseagreen1", "darkseagreen3", "darkolivegreen1"))

pie3D(table(tugas$Species),labels = dl, explode = 0.1, main = "Pie Chart of Species", col = c("darkseagreen1", "darkseagreen3", "darkolivegreen1"))

Note that the echo = FALSE parameter was added to the code chunk to prevent printing of the R code that generated the plot.