Independent trials, dependent condition

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Discussion Overview

The discussion revolves around a probability problem involving the average test scores of two randomly selected students from a normal distribution. Participants explore how to calculate the probability that the average score exceeds a certain threshold, k, using concepts from probability theory and the properties of normal distributions.

Discussion Character

  • Exploratory
  • Mathematical reasoning

Main Points Raised

  • One participant introduces the problem and seeks guidance on how to approach it, specifically asking about the probability that the average of two test scores exceeds a threshold.
  • Another participant suggests defining a new random variable Y as the sum of the two test scores and calculating the probability P(Y > 2k), noting that if the individual scores are normally distributed, their sum will also be normally distributed.
  • A later reply confirms the approach and inquires about the mean and standard deviation of the new variable Y, proposing that the mean is the sum of the means and the standard deviation is the root mean square of the individual standard deviations.

Areas of Agreement / Disagreement

Participants generally agree on the approach to defining the new random variable and the implications of the Central Limit Theorem, but there is no consensus on the specifics of the calculations or the interpretation of the results.

Contextual Notes

The discussion does not resolve the mathematical steps involved in calculating the probability or the implications of the assumptions made about the distributions.

caffeine
A friend gave me this problem; it's been years since I've taken probability, and I'm really rusty. I'm curious how to solve it.

Suppose you have a normal pdf with mean mu and stdev sigma that represents the distribution of test scores.

What's the probability that two randomly selected students will have an average higher than k?

So if I let X1 and X2 be the test scores of two randomly selected students, and if they have values of k1 and k2, then I want to know the probability that:

k1 + k2 > 2k

or

P(X1 + X2 > 2k)

I'm stumped. How does one approach a problem like that?

Thanks!
 
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You need to define a new random variable Y = X1 + X2, then calculate P(Y > 2k). If each X is normally distributed, then Y is, too. Proof. (Even if X's were non-normal, The Central Limit Theorem states that the sum of N independent identical random variables approaches the normal distribution as N goes to infinity.)
 
EnumaElish said:
You need to define a new random variable Y = X1 + X2, then calculate P(Y > 2k). If each X is normally distributed, then Y is, too. Proof. (Even if X's were non-normal, The Central Limit Theorem states that the sum of N independent identical random variables approaches the normal distribution as N goes to infinity.)

OK, thanks. Is it correct that the mean of the distribution for Y is the sum of the averages (so mu' = mu + mu) and the stdev of the distribution for Y is the RMS sum of the deviations (so sigma' = sqrt{\sigma^2 + \sigma^2} = \sqrt{2}\sigma?

Thanks! I can't believe how much I've forgotten
 

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