Assignment 1

#Question 1 #a no

gene1="ACGTACGT"
gene2="ACG"

#b no

combined_gene = paste(gene1, gene2)
print(combined_gene)

[1] "ACGTACGT ACG"

combined_gene = paste(gene1, gene2, sep ="")
print(combined_gene)

[1] "ACGTACGTACG"

#c no #Substring

gene1="ACGTACGT"

sub = substr(gene1, 2, 5)
sub

[1] "CGTA"

#d no #Pattern matching

gene1="ACGTACGT"

gene2="ACG"

grepl(gene2, gene1)

[1] TRUE

occ  = gregexpr(gene2, gene1)
occ

[[1]]
[1] 1 5
attr(,"match.length")
[1] 3 3
attr(,"index.type")
[1] "chars"
attr(,"useBytes")
[1] TRUE

#Question 2 #Arithmatic Operation

a=100
b=21

#Addition
res_add = a+b
print(a+b)

[1] 121

#Substract
res_sub = a-b
print(a-b)

[1] 79

#Multiplication
res_mult = a*b
print(a*b)

[1] 2100

#Division
res_div = a/b
print(a/b)

[1] 4.761905

#Power
res_pow = a**b
res_pow2 = a^b
print(a**b)

[1] 1e+42

print(a^b)

[1] 1e+42

#Modulo
res_mod = a %% b
print(a %% b)

[1] 16

#Question 3 #Vector #Create

scores = c( 100, 90, 50, 20, 30, 88, 66, 75, 71, 91, 0, 45, 61 )
print(scores)

 [1] 100  90  50  20  30  88  66  75  71  91   0  45  61

# Define the grading system
grading_system <- list(
  "A+" = list("min" = 80, "max" = 100),
  "A"  = list("min" = 70, "max" = 79),
  "A-" = list("min" = 60, "max" = 69),
  "B"  = list("min" = 50, "max" = 59),
  "C"  = list("min" = 40, "max" = 49),
  "D"  = list("min" = 33, "max" = 39),
  "F"  = list("min" = 0, "max" = 32)
)

# Function to calculate the letter grade
calculate_letter_grade <- function(score) {
  for (key in names(grading_system)) {
    min_score <- grading_system[[key]]$min
    max_score <- grading_system[[key]]$max
  
    if (score >= min_score && score <= max_score) {
      return(key)
    }
  }
  
  return("Invalid Score")
}

# Example scores
scores <- c( 100, 90, 50, 20, 30, 88, 66, 75, 71, 91, 0, 45, 61 )

# Calculate the letter grade for each score
for (score in scores) {
  letter_grade <- calculate_letter_grade(score)
  cat("Score:", score, "Letter Grade:", letter_grade, "\n")
}

Score: 100 Letter Grade: A+ 
Score: 90 Letter Grade: A+ 
Score: 50 Letter Grade: B 
Score: 20 Letter Grade: F 
Score: 30 Letter Grade: F 
Score: 88 Letter Grade: A+ 
Score: 66 Letter Grade: A- 
Score: 75 Letter Grade: A 
Score: 71 Letter Grade: A 
Score: 91 Letter Grade: A+ 
Score: 0 Letter Grade: F 
Score: 45 Letter Grade: C 
Score: 61 Letter Grade: A- 

#Age vector

age = c(20, 25, 28, 30, 35, 45, 50, 55, 60, 61, 66, 71, 75 )
print(age)

 [1] 20 25 28 30 35 45 50 55 60 61 66 71 75

#Correlation

age = c(20, 25, 28, 30, 35, 45, 50, 55, 60, 61, 66, 71, 75 )
print(age)

 [1] 20 25 28 30 35 45 50 55 60 61 66 71 75

scores = c(100, 90, 50, 20, 30, 88, 66, 75, 71, 91, 0, 45, 61 )
print(scores)

 [1] 100  90  50  20  30  88  66  75  71  91   0  45  61

cor(age, scores)

[1] -0.1958803

#Correlation nature is weak nagative correlation

scores[3:10]

[1] 50 20 30 88 66 75 71 91

age[3:10]

[1] 28 30 35 45 50 55 60 61

scores1 = c(50, 20, 30, 88, 66, 75, 71, 91 )
age1 = c(28, 30, 35, 45, 50, 55, 60, 61 )
cor(scores1,age1)

[1] 0.7954052

#Correlation nature is strong positive correlation