Advice on same sizes vs population.

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SUMMARY

This discussion focuses on determining the appropriate sample size for a survey with a known population, aiming for a 5% margin of error at a 95% confidence level. The participant emphasizes the importance of considering population size and variability in sample size calculations. They express uncertainty about the relevance of hyper-geometric distribution for larger sample sizes and seek clarity on the underlying equations used in sample size determination. The discussion highlights the formula for standard deviation in relation to sample size, specifically noting that variability in the true proportion significantly influences the required sample size.

PREREQUISITES
  • Understanding of statistical concepts such as margin of error and confidence level.
  • Familiarity with sample size determination formulas.
  • Knowledge of hyper-geometric distribution and its applications.
  • Basic proficiency in statistical software or tools for calculations.
NEXT STEPS
  • Research the formula for sample size calculation in surveys, specifically for finite populations.
  • Explore the implications of variability on sample size requirements in statistical analysis.
  • Learn about the application of hyper-geometric distribution in sampling scenarios.
  • Investigate statistical software options for calculating sample sizes, such as R or Python libraries.
USEFUL FOR

Statisticians, survey researchers, data analysts, and anyone involved in designing surveys who require precise sample size calculations for accurate results.

RufusDawes
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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.
 

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