Answer:
a) There is a 19.74% probability that an 18-year-old man selected at random is between 71 and 73 inches tall.
b) There is a 76.98% probability that the mean height x is between 71 and 73 inches.
Step-by-step explanation:
The Central Limit Theorem estabilishes that, for a random variable X, with mean and standard deviation , a large sample size can be approximated to a normal distribution with mean and standard deviation .
Problems of normally distributed samples can be solved using the z-score formula.
In a set with mean and standard deviation , the zscore 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 pvalue, we get the probability that the value of the measure is greater than X.
In this problem, we have that:
Mean of 72 inches and standard deviation 4 inches. This means that .
(a) what is the probability that an 18-year-old man selected at random is between 71 and 73 inches tall?
This probability is the pvalue of Z when and the pvalue of Z when .
X = 73
has a pvalue of 0.5987
X = 71
has a pvalue of 0.4013
This mean that there is a 0.5987-0.4013 = 0.1974 = 19.74% probability that an 18-year-old man selected at random is between 71 and 73 inches tall.
b) if a random sample of twenty-three 18-year-old men is selected, what is the probability that the mean height x is between 71 and 73 inches?
Now we use the Central Limit Theorem, so:
.
has a pvalue of 0.8849
X = 71
has a pvalue of 0.1151
This means that there is a 0.8849 - 0.1151 = 0.7698 = 76.98% probability that the mean height x is between 71 and 73 inches.