A manufacturer knows that their items have a normally distributed length, with a mean of 7.4 inches, and standard deviation of 0.8 inches. If 18 items are chosen at random, what is the probability that their mean length is less than 7.9 inches? P ( ¯ x < 7.9 ) =

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Answer:

P ( ¯ x < 7.9 ) = 0.9960

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 normally distributed samples are solved using the z-score formula.

In a set with mean [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], the zscore of a measure X is given by:

[tex]Z = \frac{X - \mu}{\sigma}[/tex]

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.

Central Limit Theorem

The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean [tex]\mu[/tex] and standard deviation [tex]s = \frac{\sigma}{\sqrt{n}}[/tex].

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

In this problem, we have that:

[tex]\mu = 7.4, \sigma = 0.8, n = 18, s = \frac{0.8}{\sqrt{18}} = 0.1886[/tex]

If 18 items are chosen at random, what is the probability that their mean length is less than 7.9 inches?

This is the pvalue of Z when X = 7.9.

[tex]Z = \frac{X - \mu}{\sigma}[/tex]

By the Central Limit Theorem

[tex]Z = \frac{X - \mu}{s}[/tex]

[tex]Z = \frac{7.9 - 7.4}{0.1886}[/tex]

[tex]Z = 2.65[/tex]

[tex]Z = 2.65[/tex] has a pvalue of 0.9960

P ( ¯ x < 7.9 ) = 0.9960