Step-by-step explanation
From the statement, we know that the population of scores of a test follow a normal distribution with:
• mean μ = 60,
,
• standard deviation σ = 20.
We want to compute the probability of obtaining a sample mean greater than M = 65 for different values of the size of the sample n.
First, the z-score for the sample mean with size n is given by:

Where σₛ = σ/√n is the standard deviation of the sample.
The probability of obtaining a sample mean X greater than M, is given by:

Where the probability P(Z > z) is obtained from a table for z-scores.
(a) Sample with n = 16 students
We compute the z-score with n = 16:

Using a table for z-scores, we get:

(b) Sample with n = 25 students
We compute the z-score with n = 25:

Using a table for z-scores, we get:

(c) Sample with n = 100 students
We compute the z-score with n = 100:

Using a table for z-scores, we get:

Answer
a. P(X > M = 65, n = 16) = 0.15866
b. P(X > M = 65, n = 25) = 0.10565
c. P(X > M = 65, n = 100) = 0.0062097