# Percentile Rank

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In a normal distribution with mean 30 and variance 25, at what percentile rank does a score of 42 fall?

Among twenty-five articles, nine are defective, six having only minor defects and three having major defects. Determine the probability that an article selected at random has major defects given that it has defects.

In a normal distribution with mean 3 and variance 49, what are the upper and lower limit scores for the middle 50% of the data?

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This solution assists in determining probability and the upper and lower limit scores.

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In a normal distribution with mean 30 and variance 25, at what percentile rank does a score of 42 fall?

Solution:

Let X be the random variable. Then X~N(30, 25). We can compute that the probability of X greater than 42 is

Pr(X>42)=Pr((X-30)/5>12/5)

=0.0082

So, Pr(X<42)=1-Pr(X>42)=0.9918

Note: if X~N(30,25), then (X-30)/5~N(0,1), the standard normal ...

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- BSc , Wuhan Univ. China
- MA, Shandong Univ.

###### Recent Feedback

- "Your solution, looks excellent. I recognize things from previous chapters. I have seen the standard deviation formula you used to get 5.154. I do understand the Central Limit Theorem needs the sample size (n) to be greater than 30, we have 100. I do understand the sample mean(s) of the population will follow a normal distribution, and that CLT states the sample mean of population is the population (mean), we have 143.74. But when and WHY do we use the standard deviation formula where you got 5.154. WHEN & Why use standard deviation of the sample mean. I don't understand, why don't we simply use the "100" I understand that standard deviation is the square root of variance. I do understand that the variance is the square of the differences of each sample data value minus the mean. But somehow, why not use 100, why use standard deviation of sample mean? Please help explain."
- "excellent work"
- "Thank you so much for all of your help!!! I will be posting another assignment. Please let me know (once posted), if the credits I'm offering is enough or you ! Thanks again!"
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