This is my first code in markdown
mydata <- data.frame("ID"=c(1,2,3), "Age"=c(30,40,20), "Gender"=c("F","M","M"))print(mydata)## ID Age Gender
## 1 1 30 F
## 2 2 40 M
## 3 3 20 Mmydata[1,2]<-28print(mydata)## ID Age Gender
## 1 1 28 F
## 2 2 40 M
## 3 3 20 Mmydata2 <- mydata[,-3]print(mydata2)## ID Age
## 1 1 28
## 2 2 40
## 3 3 20Same as mydata[c(1,2),]
mydata3 <- mydata[-3,]print(mydata3)## ID Age Gender
## 1 1 28 F
## 2 2 40 Mmydata$Height <- c(178, 170, 190)
print(mydata)## ID Age Gender Height
## 1 1 28 F 178
## 2 2 40 M 170
## 3 3 20 M 190mydata$Height1 <- mydata$Height + 2
print(mydata)## ID Age Gender Height Height1
## 1 1 28 F 178 180
## 2 2 40 M 170 172
## 3 3 20 M 190 192summary(mydata)## ID Age Gender Height
## Min. :1.0 Min. :20.00 Length:3 Min. :170.0
## 1st Qu.:1.5 1st Qu.:24.00 Class :character 1st Qu.:174.0
## Median :2.0 Median :28.00 Mode :character Median :178.0
## Mean :2.0 Mean :29.33 Mean :179.3
## 3rd Qu.:2.5 3rd Qu.:34.00 3rd Qu.:184.0
## Max. :3.0 Max. :40.00 Max. :190.0
## Height1
## Min. :172.0
## 1st Qu.:176.0
## Median :180.0
## Mean :181.3
## 3rd Qu.:186.0
## Max. :192.0summary(mydata[,-3])## ID Age Height Height1
## Min. :1.0 Min. :20.00 Min. :170.0 Min. :172.0
## 1st Qu.:1.5 1st Qu.:24.00 1st Qu.:174.0 1st Qu.:176.0
## Median :2.0 Median :28.00 Median :178.0 Median :180.0
## Mean :2.0 Mean :29.33 Mean :179.3 Mean :181.3
## 3rd Qu.:2.5 3rd Qu.:34.00 3rd Qu.:184.0 3rd Qu.:186.0
## Max. :3.0 Max. :40.00 Max. :190.0 Max. :192.0mean(mydata$Age)## [1] 29.33333sd(mydata$Height1)## [1] 10.06645#install.packages("psych")
library(psych)
describe(mydata)## vars n mean sd median trimmed mad min max range skew kurtosis
## ID 1 3 2.00 1.00 2 2.00 1.48 1 3 2 0.00 -2.33
## Age 2 3 29.33 10.07 28 29.33 11.86 20 40 20 0.13 -2.33
## Gender* 3 3 1.67 0.58 2 1.67 0.00 1 2 1 -0.38 -2.33
## Height 4 3 179.33 10.07 178 179.33 11.86 170 190 20 0.13 -2.33
## Height1 5 3 181.33 10.07 180 181.33 11.86 172 192 20 0.13 -2.33
## se
## ID 0.58
## Age 5.81
## Gender* 0.33
## Height 5.81
## Height1 5.81#install.packages("pastecs")
library(pastecs)
stat.desc(mydata)## ID Age Gender Height Height1
## nbr.val 3.0000000 3.0000000 NA 3.0000000 3.00000000
## nbr.null 0.0000000 0.0000000 NA 0.0000000 0.00000000
## nbr.na 0.0000000 0.0000000 NA 0.0000000 0.00000000
## min 1.0000000 20.0000000 NA 170.0000000 172.00000000
## max 3.0000000 40.0000000 NA 190.0000000 192.00000000
## range 2.0000000 20.0000000 NA 20.0000000 20.00000000
## sum 6.0000000 88.0000000 NA 538.0000000 544.00000000
## median 2.0000000 28.0000000 NA 178.0000000 180.00000000
## mean 2.0000000 29.3333333 NA 179.3333333 181.33333333
## SE.mean 0.5773503 5.8118653 NA 5.8118653 5.81186526
## CI.mean.0.95 2.4841377 25.0064379 NA 25.0064379 25.00643792
## var 1.0000000 101.3333333 NA 101.3333333 101.33333333
## std.dev 1.0000000 10.0664459 NA 10.0664459 10.06644591
## coef.var 0.5000000 0.3431743 NA 0.0561326 0.05551349round(stat.desc(mydata), 2)## ID Age Gender Height Height1
## nbr.val 3.00 3.00 NA 3.00 3.00
## nbr.null 0.00 0.00 NA 0.00 0.00
## nbr.na 0.00 0.00 NA 0.00 0.00
## min 1.00 20.00 NA 170.00 172.00
## max 3.00 40.00 NA 190.00 192.00
## range 2.00 20.00 NA 20.00 20.00
## sum 6.00 88.00 NA 538.00 544.00
## median 2.00 28.00 NA 178.00 180.00
## mean 2.00 29.33 NA 179.33 181.33
## SE.mean 0.58 5.81 NA 5.81 5.81
## CI.mean.0.95 2.48 25.01 NA 25.01 25.01
## var 1.00 101.33 NA 101.33 101.33
## std.dev 1.00 10.07 NA 10.07 10.07
## coef.var 0.50 0.34 NA 0.06 0.06round(stat.desc(mydata[,c(-1,-3)], 2))## Age Height Height1
## median 28 178 180
## mean 29 179 181
## SE.mean 6 6 6
## CI.mean.0.95 25 25 25
## var 101 101 101
## std.dev 10 10 10
## coef.var 0 0 0