Advice on same sizes vs population.

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To determine the appropriate sample size for a survey with a known population, a margin of error of 5%, and 95% confidence, the variability of the population must be considered. While statistical theory suggests that population size may not significantly impact sample size, it is crucial to avoid under-sampling, which can lead to random results. The standard deviation formula, which involves the probability of a positive response, indicates that sample size requirements vary depending on the estimated proportion. Hyper-geometric distribution is relevant for small sample sizes, but the underlying equations for larger samples are essential for accurate calculations. Understanding these principles will help in selecting an adequate sample size for reliable survey results.
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Hello,

I have a survey where there will be a known population and a number of people sampled from within the survey population.

What I'd like to know is what sample size I should use to receive a certain margin of error which will be set at a constant 5% with 95% confidence.

I would like to consider this with the size of the population in mind. I understand that statistical theory sometimes indicates that the size is not relevant, but the variability is what determines the sample size.

I'm not sure if that is relevant as the true proportion is not known and is estimated based on the survey results.

What I'm trying to avoid is taking a sample which is too small and could therefore be more random than expected by formula which don't consider the population size.

I was thinking that a hyper-geometric distribution might be useful but then I realized that only applies for small sample sizes ? Is this correct ?

I have seen tables where they say what sample size you should use for a given population, margin of error and confidence level but I want to know what is the underlying equation.

I tried ripping off the java script from a few calculators but I'm still not sure exactly the theory is behind it.

Thanks.
 
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The general idea (assuming a simple yes - no for your survey) is the standard deviation ~ √(p(1-p)/n) where p is the probability of yes and n is the sample size. If p ~ 1/2 you would need a certain size n, but for p near 0 or near 1 you would need a much larger sample.
 
I was reading a Bachelor thesis on Peano Arithmetic (PA). PA has the following axioms (not including the induction schema): $$\begin{align} & (A1) ~~~~ \forall x \neg (x + 1 = 0) \nonumber \\ & (A2) ~~~~ \forall xy (x + 1 =y + 1 \to x = y) \nonumber \\ & (A3) ~~~~ \forall x (x + 0 = x) \nonumber \\ & (A4) ~~~~ \forall xy (x + (y +1) = (x + y ) + 1) \nonumber \\ & (A5) ~~~~ \forall x (x \cdot 0 = 0) \nonumber \\ & (A6) ~~~~ \forall xy (x \cdot (y + 1) = (x \cdot y) + x) \nonumber...

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