#Importing the data

data(package = .packages(all.available = TRUE))
mydata <- force(USArrests) #Reading the dataset, saved in RD
summary(mydata)
##      Murder          Assault         UrbanPop          Rape      
##  Min.   : 0.800   Min.   : 45.0   Min.   :32.00   Min.   : 7.30  
##  1st Qu.: 4.075   1st Qu.:109.0   1st Qu.:54.50   1st Qu.:15.07  
##  Median : 7.250   Median :159.0   Median :66.00   Median :20.10  
##  Mean   : 7.788   Mean   :170.8   Mean   :65.54   Mean   :21.23  
##  3rd Qu.:11.250   3rd Qu.:249.0   3rd Qu.:77.75   3rd Qu.:26.18  
##  Max.   :17.400   Max.   :337.0   Max.   :91.00   Max.   :46.00
library(psych)
mydata2 <- force(sat.act)

Calculate the descriptive statistics for variables ACT, SATV, SATQ, seperate by gender.

mydata2$gender <- factor(mydata2$gender,
                        levels = c(1, 2),
                        labels = c("M", "F)"))

describeBy(mydata2[, c("ACT", "SATV", "SATQ")],
           group = mydata2$gender)
## 
##  Descriptive statistics by group 
## group: M
##      vars   n   mean     sd median trimmed    mad min max range  skew kurtosis
## ACT     1 247  28.79   5.06     30   29.23   4.45   3  36    33 -1.06     1.89
## SATV    2 247 615.11 114.16    630  622.07 118.61 200 800   600 -0.63     0.13
## SATQ    3 245 635.87 116.02    660  645.53  94.89 300 800   500 -0.72    -0.12
##        se
## ACT  0.32
## SATV 7.26
## SATQ 7.41
## ------------------------------------------------------------ 
## group: F)
##      vars   n   mean     sd median trimmed    mad min max range  skew kurtosis
## ACT     1 453  28.42   4.69     29   28.63   4.45  15  36    21 -0.39    -0.42
## SATV    2 453 610.66 112.31    620  617.91 103.78 200 800   600 -0.65     0.42
## SATQ    3 442 596.00 113.07    600  602.21 133.43 200 800   600 -0.58     0.13
##        se
## ACT  0.22
## SATV 5.28
## SATQ 5.38
by(mydata2[, c("ACT", "SATV", "SATQ")], mydata2$gender, summary)
## mydata2$gender: M
##       ACT             SATV            SATQ      
##  Min.   : 3.00   Min.   :200.0   Min.   :300.0  
##  1st Qu.:25.00   1st Qu.:540.0   1st Qu.:570.0  
##  Median :30.00   Median :630.0   Median :660.0  
##  Mean   :28.79   Mean   :615.1   Mean   :635.9  
##  3rd Qu.:32.50   3rd Qu.:700.0   3rd Qu.:720.0  
##  Max.   :36.00   Max.   :800.0   Max.   :800.0  
##                                  NA's   :2      
## ------------------------------------------------------------ 
## mydata2$gender: F)
##       ACT             SATV            SATQ    
##  Min.   :15.00   Min.   :200.0   Min.   :200  
##  1st Qu.:25.00   1st Qu.:550.0   1st Qu.:500  
##  Median :29.00   Median :620.0   Median :600  
##  Mean   :28.42   Mean   :610.7   Mean   :596  
##  3rd Qu.:32.00   3rd Qu.:700.0   3rd Qu.:683  
##  Max.   :36.00   Max.   :800.0   Max.   :800  
##                                  NA's   :11
mydata2F <- mydata2[mydata2$gender == "F" , ]