Answer:
0.62% probability that a random sample of 16 bulbs will have an average life of less than 775 hours.
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)
Normal probability distribution.
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:
![\mu = 800, \sigma = 40, n = 16, s = \frac{40}{\sqrt{16}} = 10](https://tex.z-dn.net/?f=%5Cmu%20%3D%20800%2C%20%5Csigma%20%3D%2040%2C%20n%20%3D%2016%2C%20s%20%3D%20%5Cfrac%7B40%7D%7B%5Csqrt%7B16%7D%7D%20%3D%2010)
Find the probability that a random sample of 16 bulbs will have an average life of less than 775 hours.
This probability is the pvalue of Z when
. So
![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{775 - 800}{10}](https://tex.z-dn.net/?f=Z%20%3D%20%5Cfrac%7B775%20-%20800%7D%7B10%7D)
![Z = -2.5](https://tex.z-dn.net/?f=Z%20%3D%20-2.5)
has a pvalue of 0.0062. So there is a 0.62% probability that a random sample of 16 bulbs will have an average life of less than 775 hours.