simpan=read.table("data4.1.csv",header=TRUE,sep=";")
simpan
## data1 data2 data3
## 1 1 10 1
## 2 2 10 2
## 3 3 10 2
## 4 4 20 3
## 5 5 20 3
## 6 6 30 3
## 7 7 30 3
## 8 8 30 3
## 9 9 30 4
## 10 10 30 4
## 11 11 30 4
## 12 11 30 5
## 13 12 40 5
## 14 13 40 6
## 15 14 40 6
## 16 15 50 NA
## 17 16 50 NA
## 18 17 50 NA
## 19 18 50 NA
data_1=simpan$data1
data_11=na.omit(data_1)
data_2=simpan$data2
data_21=na.omit(data_2)
data_3=simpan$data3
data_31=na.omit(data_3)
data_1
## [1] 1 2 3 4 5 6 7 8 9 10 11 11 12 13 14 15 16 17 18
data_11
## [1] 1 2 3 4 5 6 7 8 9 10 11 11 12 13 14 15 16 17 18
data_2
## [1] 10 10 10 20 20 30 30 30 30 30 30 30 40 40 40 50 50 50 50
data_21
## [1] 10 10 10 20 20 30 30 30 30 30 30 30 40 40 40 50 50 50 50
data_3
## [1] 1 2 2 3 3 3 3 3 4 4 4 5 5 6 6 NA NA NA NA
data_31
## [1] 1 2 2 3 3 3 3 3 4 4 4 5 5 6 6
## attr(,"na.action")
## [1] 16 17 18 19
## attr(,"class")
## [1] "omit"
library(psych)
## Warning: package 'psych' was built under R version 4.5.3
describe(data_11)
## vars n mean sd median trimmed mad min max range skew kurtosis se
## X1 1 19 9.58 5.2 10 9.59 5.93 1 18 17 -0.04 -1.32 1.19
describe(data_21)
## vars n mean sd median trimmed mad min max range skew kurtosis se
## X1 1 19 31.58 13.44 30 31.76 14.83 10 50 40 -0.14 -1.13 3.08
describe(data_31)
## vars n mean sd median trimmed mad min max range skew kurtosis se
## X1 1 15 3.6 1.45 3 3.62 1.48 1 6 5 0.14 -1.01 0.38
library(psych)
describe(data_11)
## vars n mean sd median trimmed mad min max range skew kurtosis se
## X1 1 19 9.58 5.2 10 9.59 5.93 1 18 17 -0.04 -1.32 1.19
describe(data_21)
## vars n mean sd median trimmed mad min max range skew kurtosis se
## X1 1 19 31.58 13.44 30 31.76 14.83 10 50 40 -0.14 -1.13 3.08
describe(data_31)
## vars n mean sd median trimmed mad min max range skew kurtosis se
## X1 1 15 3.6 1.45 3 3.62 1.48 1 6 5 0.14 -1.01 0.38
library(pastecs)
## Warning: package 'pastecs' was built under R version 4.5.2
stat.desc(data_11)
## nbr.val nbr.null nbr.na min max range
## 19.0000000 0.0000000 0.0000000 1.0000000 18.0000000 17.0000000
## sum median mean SE.mean CI.mean.0.95 var
## 182.0000000 10.0000000 9.5789474 1.1928535 2.5060921 27.0350877
## std.dev coef.var
## 5.1995276 0.5428078
stat.desc(data_21)
## nbr.val nbr.null nbr.na min max range
## 19.0000000 0.0000000 0.0000000 10.0000000 50.0000000 40.0000000
## sum median mean SE.mean CI.mean.0.95 var
## 600.0000000 30.0000000 31.5789474 3.0839291 6.4790946 180.7017544
## std.dev coef.var
## 13.4425353 0.4256803
stat.desc(data_31)
## x
## nbr.val 15.0000000
## nbr.null 0.0000000
## nbr.na 0.0000000
## min 1.0000000
## max 6.0000000
## range 5.0000000
## sum 54.0000000
## median 3.0000000
## mean 3.6000000
## SE.mean 0.3754363
## CI.mean.0.95 0.8052307
## var 2.1142857
## std.dev 1.4540584
## coef.var 0.4039051