Answer:
There is a 6.18% probability that her average score is more than 230.
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 ![\frac{\sigma}{\sqrt{n}}](https://tex.z-dn.net/?f=%5Cfrac%7B%5Csigma%7D%7B%5Csqrt%7Bn%7D%7D)
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:
![Z = \frac{X - \mu}{\sigma}](https://tex.z-dn.net/?f=Z%20%3D%20%5Cfrac%7BX%20-%20%5Cmu%7D%7B%5Csigma%7D)
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:
Her average score is 225, with a standard deviation of 13. This means that
.
If during a typical week Susan bowls 16 games, what is the probability that her average score is more than 230?
This is 1 subtracted by the pvalue of Z when
.
By the Central Limit Theorem, we have ![s = \frac{\sigma}{\sqrt{n}} = \frac{13}{4} = 3.25](https://tex.z-dn.net/?f=s%20%3D%20%5Cfrac%7B%5Csigma%7D%7B%5Csqrt%7Bn%7D%7D%20%3D%20%5Cfrac%7B13%7D%7B4%7D%20%3D%203.25)
![Z = \frac{X - \mu}{s}](https://tex.z-dn.net/?f=Z%20%3D%20%5Cfrac%7BX%20-%20%5Cmu%7D%7Bs%7D)
![Z = \frac{230 - 225}{3.25}](https://tex.z-dn.net/?f=Z%20%3D%20%5Cfrac%7B230%20-%20225%7D%7B3.25%7D)
![Z = 1.54](https://tex.z-dn.net/?f=Z%20%3D%201.54)
has a pvalue of 0.9382. This means that there is a 1-0.9382 = 0.0618 = 6.18% probability that her average score is more than 230.