Answer:
The interval containing the middle-most 76% of sample means is between 56.24 and 63.76.
Explanation:
To solve this question, we need to understand the normal probability distribution and the central limit theorem.
Normal Probability Distribution 
Problems of normal distributions can be solved using the z-score formula. 
In a set with mean 
 and standard deviation
 and standard deviation 
 , the z-score of a measure X is given by:
, the z-score of a measure X is given by: 
 
 
The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the p-value, we get the probability that the value of the measure is greater than X. 
Central Limit Theorem 
The Central Limit Theorem establishes that, for a normally distributed random variable X, with mean 
 and standard deviation
 and standard deviation 
 , the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean
, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean 
 and standard deviation
 and standard deviation 
 .
. 
For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30. 
A distribution of values is normal with a mean of 60 and a standard deviation of 16.
This means that 

Samples of size 25:
This means that 

Find the interval containing the middle-most 76% of sample means.
Between the 50 - (76/2) = 12th percentile and the 50 + (76/2) = 88th percentile.
12th percentile:
X when Z has a p-value of 0.12, so X when Z = -1.175.

By the Central Limit Theorem




88th percentile:




The interval containing the middle-most 76% of sample means is between 56.24 and 63.76.