Example

mydata<-data.frame("ID"=c(1,2,3,4),
                   "AGE"=c(10,11,18,20),
                   "Gender"=c("M","M","F","M"))

print(mydata)

##   ID AGE Gender
## 1  1  10      M
## 2  2  11      M
## 3  3  18      F
## 4  4  20      M

mean(mydata$AGE)

## [1] 14.75

sd(mydata$AGE)

## [1] 4.99166

The average age of students is 14,75 years.

mydata$height<-c(100,119,120,130)
mydata$weight<-c(40,50,45,44)

mydata$BMI<-mydata$weight/mydata$height
print(mydata)

##   ID AGE Gender height weight       BMI
## 1  1  10      M    100     40 0.4000000
## 2  2  11      M    119     50 0.4201681
## 3  3  18      F    120     45 0.3750000
## 4  4  20      M    130     44 0.3384615

mydata2<-mydata[ ,c(2,4)]
mydata3<-mydata2[-3, ]

summary(mydata[ ,c(-1,-3)])

##       AGE            height          weight           BMI        
##  Min.   :10.00   Min.   :100.0   Min.   :40.00   Min.   :0.3385  
##  1st Qu.:10.75   1st Qu.:114.2   1st Qu.:43.00   1st Qu.:0.3659  
##  Median :14.50   Median :119.5   Median :44.50   Median :0.3875  
##  Mean   :14.75   Mean   :117.2   Mean   :44.75   Mean   :0.3834  
##  3rd Qu.:18.50   3rd Qu.:122.5   3rd Qu.:46.25   3rd Qu.:0.4050  
##  Max.   :20.00   Max.   :130.0   Max.   :50.00   Max.   :0.4202

#install.packages("pastecs")
library(pastecs)
round(stat.desc(mydata[ ,c(-1,-3)]))

##              AGE height weight BMI
## nbr.val        4      4      4   4
## nbr.null       0      0      0   0
## nbr.na         0      0      0   0
## min           10    100     40   0
## max           20    130     50   0
## range         10     30     10   0
## sum           59    469    179   2
## median        14    120     44   0
## mean          15    117     45   0
## SE.mean        2      6      2   0
## CI.mean.0.95   8     20      7   0
## var           25    157     17   0
## std.dev        5     13      4   0
## coef.var       0      0      0   0

mydataM<-mydata[mydata$Gender=="M"&mydata$AGE>12, ]