Answer:
The interval containing the middle-most 76% of sample means is between 56.24 and 63.76.
Step-by-step 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
, 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
, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean
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.