R Notebook

#a.(i)Data Frame

exam_score= data.frame(
ID = c(1, 2, 3, 4, 5),
name = c("Alice", "Bob", "David", "John", "Jenny"),
age = c(20, 25, 30, 22, 18),
score = c(100, 78, 90, 55, 81)
)
exam_score

a.(ii).Add Rows

new_row = c("6", "shihar", "26", "95")
exam_score = rbind(exam_score, new_row)
exam_score

new_row = c("7", "sara", "25", "97")
exam_score = rbind(exam_score, new_row)
exam_score

###a.(iii) Add column

Income = c(10000, 20000, 30000, 40000, 50000, 60000 , 60000)
exam_score = cbind(exam_score,Income)
exam_score

###b(i).age

age = c(20, 25, 30, 22, 18, 26, 25)
max(age)

## [1] 30

min(age)

## [1] 18

median(age)

## [1] 25

sum(age)

## [1] 166

mean(age)

## [1] 23.71429

sd(age)

## [1] 4.029652

var(age)

## [1] 16.2381

quantile(age)

##   0%  25%  50%  75% 100% 
## 18.0 21.0 25.0 25.5 30.0

b(ii).score

score = c(100, 78, 90, 55, 81, 95, 97)
max(score)

## [1] 100

min(score)

## [1] 55

median(score)

## [1] 90

sum(score)

## [1] 596

mean(score)

## [1] 85.14286

sd(score)

## [1] 15.59304

var(score)

## [1] 243.1429

quantile(score)

##    0%   25%   50%   75%  100% 
##  55.0  79.5  90.0  96.0 100.0

###b(iii).Income

Income = c(10000, 20000, 30000, 40000, 50000, 60000 , 60000)
max(Income)

## [1] 60000

min(Income)

## [1] 10000

median(Income)

## [1] 40000

sum(Income)

## [1] 270000

mean(Income)

## [1] 38571.43

sd(Income)

## [1] 19518

var(Income)

## [1] 380952381

quantile(Income)

##    0%   25%   50%   75%  100% 
## 10000 25000 40000 55000 60000

###C.Correlation ##(i)Age and score

cor(age, score)

## [1] 0.210303

##(ii) Age and Income

cor(age, Income)

## [1] 0.07870842

(iii) Score and Income

cor(score, Income)

## [1] 0.02268729

d. Select rows where score is greater than or equal 80

exam_score[exam_score$score >=80,]

###e.Select rows with the age range of 20 to 30.

exam_score[exam_score$age>=20, ]