Yoonie is a personnel manager in a large corporation. Each month she must review 16 of the employees. From past experience, she has found that the reviews take her approximately four hours each to do with a population standard deviation of 1.2 hours. Let X be the random variable representing the time it takes her to complete one review. Assume X is normally distributed. Let X be the random variable representing the mean time to complete the 16 reviews. Assume that the 16 reviews represent a random set of reviews. Complete the distributions.
A. Find the probability that the mean of a month’s reviews will take Yoonie from 3.5 to 4.25 hrs.
B. P(_____) = _______.
C. Find the 95th percentile for the mean time to complete one month's reviews.
D.The 95th Percentile =________.

Respuesta :

Answer:

a) [tex]P(3.5 \leq X \leq 4.25) = 0.7492[/tex]

b) The 95th percentile is 4.4935 hours.

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 [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.

The reviews take her approximately four hours each to do with a population standard deviation of 1.2 hours.

This means that [tex]\mu = 4, \sigma = 1.2[/tex]

16 reviews.

This means that [tex]n = 16, s = \frac{1.2}{\sqrt{16}} = 0.3[/tex]

A. Find the probability that the mean of a month’s reviews will take Yoonie from 3.5 to 4.25 hrs.

This is the pvalue of Z when X = 4.25 subtracted by the pvalue of Z when X = 3.5. So

X = 4.25

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

By the Central Limit Theorem

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

[tex]Z = \frac{4.25 - 4}{0.3}[/tex]

[tex]Z = 0.83[/tex]

[tex]Z = 0.83[/tex] has a pvalue of 0.7967

X = 3.5

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

[tex]Z = \frac{3.5 - 4}{0.3}[/tex]

[tex]Z = -1.67[/tex]

[tex]Z = -1.67[/tex] has a pvalue of 0.0475

0.7967 - 0.0475 = 0.7492

So

[tex]P(3.5 \leq X \leq 4.25) = 0.7492[/tex]

C. Find the 95th percentile for the mean time to complete one month's reviews.

This is X when Z has a pvalue of 0.95, so X when Z = 1.645.

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

[tex]1.645 = \frac{X - 4}{0.3}[/tex]

[tex]X - 4 = 0.3*1.645[/tex]

[tex]X = 4.4935[/tex]

The 95th percentile is 4.4935 hours.