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#### lp026713389

Hello everyone,

I'll try and be as organized as I can in this post, as it is my first. I am currently a senior student in industrial engineering, doing my co-op graduation project in acceptance sampling.

I am developing a

1. While reading about which distribution to use while developing my plan, I got confused about what exactly are the criteria to choose the hypergeometric or the binomial approx. to the hypergeometric. Hypergeometric is typically used for small/finite lots, however some literature mentions that the binomial approx. is accurate as well, if N (population size) is at least 10 times greater than n (sample size).

The problem here is, I am actually trying to determine which distribution to use IN ORDER TO get n (whether by calculation or tables). But the above condition assumes that I already know n (which I am trying to determine). It seems a bit illogical to me, that the condition assumes I have a value which I need to get by a choice I will make based on that condition. Any help here?

2. Is there any other condition based on which I can choose whether I can use the binomial approximation or not? For example instead of having to do with n, I am looking for a condition like "If N (population/lot size) is >= a certain value, the binomial approx. can be used." That would make a lot more sense to me than the condition depending on n (sample size, which I am trying to get!)

3. If the hypergeometric distribution is to be used, I can't find any concrete methods to calculate the sample size I should take based on the size of the lot received. For the binomial distribution/approximation though, I found the Larson nomogram, ANSI Z1.4 tables, etc., which gives n and c (but is not based on N). I couldn't find any method to get the required sample size depending on the lot size for the hypergeometric distribution though.

4. Even if there was some method to calculate/obtain n depending on N using the

5. Also, just a general question, what distributions are the MIL-STD-105E and ANSI Z1.4 standards based on?

I am really confused here and the clock is ticking! Any help is appreciated.

Please cite your sources when possible

Thanks!

I'll try and be as organized as I can in this post, as it is my first. I am currently a senior student in industrial engineering, doing my co-op graduation project in acceptance sampling.

I am developing a

**type A sampling plan for attributes**(with type A OC curve) to sample an isolated lot, not a process. What I have so far, are AQL which I have obtained from a real producer, and RQL which I have obtained from a consumer who works with that same producer. I work with the consumer, but I want to implement both values in my plan (when drawing the OC curve). I have been reading a lot of literature about the topic lately, however a lot of things in what I've read don't seem to add up for me. Here are a few:1. While reading about which distribution to use while developing my plan, I got confused about what exactly are the criteria to choose the hypergeometric or the binomial approx. to the hypergeometric. Hypergeometric is typically used for small/finite lots, however some literature mentions that the binomial approx. is accurate as well, if N (population size) is at least 10 times greater than n (sample size).

The problem here is, I am actually trying to determine which distribution to use IN ORDER TO get n (whether by calculation or tables). But the above condition assumes that I already know n (which I am trying to determine). It seems a bit illogical to me, that the condition assumes I have a value which I need to get by a choice I will make based on that condition. Any help here?

2. Is there any other condition based on which I can choose whether I can use the binomial approximation or not? For example instead of having to do with n, I am looking for a condition like "If N (population/lot size) is >= a certain value, the binomial approx. can be used." That would make a lot more sense to me than the condition depending on n (sample size, which I am trying to get!)

3. If the hypergeometric distribution is to be used, I can't find any concrete methods to calculate the sample size I should take based on the size of the lot received. For the binomial distribution/approximation though, I found the Larson nomogram, ANSI Z1.4 tables, etc., which gives n and c (but is not based on N). I couldn't find any method to get the required sample size depending on the lot size for the hypergeometric distribution though.

4. Even if there was some method to calculate/obtain n depending on N using the

**hypergeometric**distribution, how do I get c (acceptance number) in order to sentence the lot?! Again, for binomial, c can be obtained from the nomogram, standard tables, etc.5. Also, just a general question, what distributions are the MIL-STD-105E and ANSI Z1.4 standards based on?

I am really confused here and the clock is ticking! Any help is appreciated.

Please cite your sources when possible

Thanks!

**Edit: I have just put the AQL and RQL into Minitab, which are 2.8 & 6% respectively in my case. With alpha and beta of 0.05 and 0.1 respectively, and ticking the use hypergeometric distribution for isolated lots, I got n=194, and c=8. How did Minitab arrive at these values?**
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