What is the Probability of Hereditary Conditions in a Gaussian Distribution?

AI Thread Summary
The discussion centers on using Gaussian distribution to calculate the probability of hereditary conditions in eggs, with 5% of eggs affected. Participants emphasize the importance of understanding the binomial distribution as the underlying model, as each egg either has or does not have the condition. Key calculations involve determining the mean (μ) and standard deviation (σ) using the formulas μ = Np and σ = √(Npq). The conversation highlights the need to approximate the binomial distribution with a Gaussian distribution for larger sample sizes. Overall, the thread aims to clarify the steps necessary to solve the probability problem effectively.
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Homework Statement


Please help!

I'm new to Gaussian and I've been on this problem for hours, I can't crack it at all (no pun intended) can anyone provide a detailed walk through the answers?

On average 5% of eggs contain a hereditary condition. Use Gaussian distribution to find the probability thatIn a box of ten eggs none carry the hereditary condition
Batch of 500 there are 20 that carry the hereditary condition
In a batch of 10000 there are LESS than 1000 faulty!

Homework Equations


I can't use equation tool on this ancient phone

The Attempt at a Solution


Completely stumped
 
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Some of the problem uses the binomial distribution. Parts of the problem are most easily calculated simply using the binomial without even approximating it by a Gaussian. The last part is most readily done by approximating the binomial to a Gaussian with same ## \mu ## and ## \sigma ##. You should know that ## \sigma ## for a binomial is ## \sigma=\sqrt{Npq} ##.
 
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conrad dunk said:

Homework Statement


Please help!

I'm new to Gaussian and I've been on this problem for hours, I can't crack it at all (no pun intended) can anyone provide a detailed walk through the answers?

On average 5% of eggs contain a hereditary condition. Use Gaussian distribution to find the probability thatIn a box of ten eggs none carry the hereditary condition
Batch of 500 there are 20 that carry the hereditary condition
In a batch of 10000 there are LESS than 1000 faulty!

Homework Equations


I can't use equation tool on this ancient phone

The Attempt at a Solution


Completely stumped

What, exactly, do you know about the Gaussian distribution? Where are you stuck?

Do you know what mean and variance represent? Do you know how to find the appropriate mean and variance in this problem? Do you know how to transform a problem with arbitrary mean and variance to an equivalent problem with mean = 0 and variance = 1? Do you know what needs to be done after that?
 
I need to find the variance and mean and standard deviation from the Gaussian distribution
 
conrad dunk said:
I need to find the variance and mean and standard deviation from the Gaussian distribution

No, you don't. You have it backwards. You need to find the appropriate mean and variance; THEN you can figure out what is the correct Gaussian distribution for this problem.
 
How do I find that from the supplied data? Sorry I'm really stuck
 
conrad dunk said:
How do I find that from the supplied data? Sorry I'm really stuck
Post #2 from @Charles Link is a very strong hint. The underlying distribution is a binomial distribution -- an egg either has the hereditary defect or it doesn't, and the problem here is to approximate this binomial distribution with a normal (or Gaussian) distribution. The p (= ##\mu##) that Charles link mentions is pretty much given in the problem, and he has given an formula for finding ##\sigma##.
 
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Mark44 said:
Post #2 from @Charles Link is a very strong hint. The underlying distribution is a binomial distribution -- an egg either has the hereditary defect or it doesn't, and the problem here is to approximate this binomial distribution with a normal (or Gaussian) distribution. The p (= ##\mu##) that Charles link mentions is pretty much given in the problem, and he has given an formula for finding ##\sigma##.
Yes, I agree. One minor correction ## \mu=Np ##.
 
Charles Link said:
Yes, I agree. One minor correction ## \mu=Np ##.
Right you are. I taught statistics a number of times, some years ago, but this one slipped my mind.
 
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