Example

mydata  <- data.frame("ID"= c(1, 2, 3, 4),
                       "Age" = c(20, 22, 18, 24), 
                       "Gender"= c("M", "F", "M", "M"))

print(mydata)

##   ID Age Gender
## 1  1  20      M
## 2  2  22      F
## 3  3  18      M
## 4  4  24      M

mean(mydata$Age)

## [1] 21

sd(mydata$Age)

## [1] 2.581989

The avg age of students is 21 years.

mydata$Height <- c(180, 170, 176, 177)
mydata$Weight <- c(76, 60, 72, 73)

Creating new dataframe, which includes only Age and Height.

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

From mydata2 remove the third row.

mydata3 <- mydata2[-3,]

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

##       Age           Height          Weight     
##  Min.   :18.0   Min.   :170.0   Min.   :60.00  
##  1st Qu.:19.5   1st Qu.:174.5   1st Qu.:69.00  
##  Median :21.0   Median :176.5   Median :72.50  
##  Mean   :21.0   Mean   :175.8   Mean   :70.25  
##  3rd Qu.:22.5   3rd Qu.:177.8   3rd Qu.:73.75  
##  Max.   :24.0   Max.   :180.0   Max.   :76.00

#install.packages("pastecs")

library(pastecs)
round(stat.desc(mydata[, c(-1,-3)]),2)

##                Age Height Weight
## nbr.val       4.00   4.00   4.00
## nbr.null      0.00   0.00   0.00
## nbr.na        0.00   0.00   0.00
## min          18.00 170.00  60.00
## max          24.00 180.00  76.00
## range         6.00  10.00  16.00
## sum          84.00 703.00 281.00
## median       21.00 176.50  72.50
## mean         21.00 175.75  70.25
## SE.mean       1.29   2.10   3.52
## CI.mean.0.95  4.11   6.67  11.20
## var           6.67  17.58  49.58
## std.dev       2.58   4.19   7.04
## coef.var      0.12   0.02   0.10

mydata_M <- mydata[mydata$Gender == "M", ]

mydata_M <- mydata[mydata$Gender== "M" & mydata >= 20, ]