Descriptive Statistics And Frequency Tables Basics

1. Reading the data

# reading the data
data(mtcars)
colnames(mtcars)

##  [1] "mpg"  "cyl"  "disp" "hp"   "drat" "wt"   "qsec" "vs"   "am"   "gear"
## [11] "carb"

attach(mtcars)
View(mtcars)

summary(mtcars$mpg)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   10.40   15.43   19.20   20.09   22.80   33.90

PART 1

2. Descriptive Statistics By Groups

2a. describe()

library(psych)
describe(mpg)

##    vars  n  mean   sd median trimmed  mad  min  max range skew kurtosis   se
## X1    1 32 20.09 6.03   19.2    19.7 5.41 10.4 33.9  23.5 0.61    -0.37 1.07

2b. describeBy()

library(psych)
describeBy(mpg, cyl)

## 
##  Descriptive statistics by group 
## group: 4
##    vars  n  mean   sd median trimmed  mad  min  max range skew kurtosis   se
## X1    1 11 26.66 4.51     26   26.44 6.52 21.4 33.9  12.5 0.26    -1.65 1.36
## ------------------------------------------------------------ 
## group: 6
##    vars n  mean   sd median trimmed  mad  min  max range  skew kurtosis   se
## X1    1 7 19.74 1.45   19.7   19.74 1.93 17.8 21.4   3.6 -0.16    -1.91 0.55
## ------------------------------------------------------------ 
## group: 8
##    vars  n mean   sd median trimmed  mad  min  max range  skew kurtosis   se
## X1    1 14 15.1 2.56   15.2   15.15 1.56 10.4 19.2   8.8 -0.36    -0.57 0.68

2c. tapply()

tapply(mpg, am, mean)

##        0        1 
## 17.14737 24.39231

tapply(mpg, cyl, mean)

##        4        6        8 
## 26.66364 19.74286 15.10000

PART 2

3. Frequency Tables for One Variable

3a. table()

t0 = table(cyl)
t0

## cyl
##  4  6  8 
## 11  7 14

3b. prop.table()

p0 = prop.table(t0)
p0

## cyl
##       4       6       8 
## 0.34375 0.21875 0.43750

3c. round()

round(p0*100,2)

## cyl
##     4     6     8 
## 34.38 21.88 43.75

t2 = table(cyl,am)
t2

##    am
## cyl  0  1
##   4  3  8
##   6  4  3
##   8 12  2