set.seed(123)

# Simulating scores using rnorm() function
classA_scores <- rnorm(25, mean = 75, sd = 10)
classB_scores <- rnorm(25, mean = 80, sd = 15)

# Null Hypothesis (H0): The mean mathematics exam score of students from class A is equal to the mean mathematics exam score of students from class B. In other words, there's no difference in the average performance of the two classes on the mathematics exam. Mathematically, we can denote it as (μ1 = μ2), where μ1 represents the mean score for class A and μ2 represents the mean score for class B.

# Alternative Hypothesis (H1): The mean mathematics exam score of students from class A is not equal to the mean mathematics exam score of students from class B. In other words, there is a significant difference in the average performance of the two classes on the mathematics exam. Mathematically, we can denote it as (μ1 ≠ μ2), where μ1 represents the mean score for class A and μ2 represents the mean score for class B.

# using t-test for hypothesis testing
result <- t.test(classA_scores, classB_scores)

# using the print fumction to display information stored in the "result" variable
print(result)