Example

R Markdown

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 average age is 21.

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

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

from mydata2, remove column 2

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

###Descriptive statistics the younegst pesron was 18

#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_M1 <- mydata[ mydata$Gender=="M" & mydata$Age>=20, ]