Hi,

To find the sample size for a population epigenetic study, kindly see the follwoing link:

http://www.bristol.ac.uk/caite/geocode/newcastleshortcourse/powerandsamplesize.pdf

http://www.bristol.ac.uk/caite/geocode/newcastleshortcourse/designingepigeneticepidemiology.pdf

https://books.google.com.sa/books?id=RRqn4lKEWyoC&pg=PA29&lpg=PA29&dq=sample+size+for+a+population+epigenetic+study&source=bl&ots=bdUpkpyVnZ&sig=v1Sc0Zo2J_wHo4U7zBQYIjwAgCo&hl=en&sa=X&ei=lBZGVcD5FsivU7zFgvgO&redir_esc=y#v=onepage&q=sample%20size%20for%20a%20population%20epigenetic%20study&f=false

http://link.springer.com/chapter/10.1007/978-94-007-2495-2_3#page-1

Hi,

To find the sample size for a population epigenetic study, kindly see the follwoing link:

http://www.bristol.ac.uk/caite/geocode/newcastleshortcourse/powerandsamplesize.pdf

http://www.bristol.ac.uk/caite/geocode/newcastleshortcourse/designingepigeneticepidemiology.pdf

https://books.google.com.sa/books?id=RRqn4lKEWyoC&pg=PA29&lpg=PA29&dq=sample+size+for+a+population+epigenetic+study&source=bl&ots=bdUpkpyVnZ&sig=v1Sc0Zo2J_wHo4U7zBQYIjwAgCo&hl=en&sa=X&ei=lBZGVcD5FsivU7zFgvgO&redir_esc=y#v=onepage&q=sample%20size%20for%20a%20population%20epigenetic%20study&f=false

http://link.springer.com/chapter/10.1007/978-94-007-2495-2_3#page-1

Erin, I think that when you are working with lab animals, you can plan the sample size, but when you work with natural populations you just pick as much as you can, the more the better. In your case you already have a sample, so the question is in statistical methods you plan to use, and how you will discuss the results. You may treat your result as correct if you have evidence for it, or you may say that you just observe a trend, which needs to be proved using bigger sample.

Sample size from finite population can be estimate by :

n= N / ( 1+ N * e^2 ) 

and from infinite population by :

n= ( Z^2 * S^2) / E^2

where : Z  ( 1.96 for 0.05 and 2.58 for 0.01 )

S = standard deviation from previous studies or pilot  study

E = significant level 

Also, you can use software to calculate sample size ( SPSS , Minitab , Gpower )

I hope that be useful for you 

@Khalid

So if I put in the numbers using N as the population size and e=E=0.05, Z=1.96, I will assign S=4, then n=24586 for the infinite population. Yet for the finite population I get a sample size that converges to 400 at a population size of about 1,000,000,000. While it is axiomatic that no population is really infinite, it seems odd that there is such a large difference between these answers.

Dear Timothy

You suggest that the infinite = finite population , that is not always true , you can not suggest the population of one species of fish in the sea , or bacteria in certain location . So, there are two different terms infinite and finite population .

Sample size from finite population as mention to equation can be estimated also by special Tables ( cross population size with significant level ) and will get sample size near by of equation .

The infinite population equation derived from interval estimation of population mean :   X bar ± Z . ( S/√n )

Where Z. ( S/ √n) represent the Error of the mean = E

E=  Z. ( S/ √n)

√n . E = Z . S

√n = ( Z . S ) / E

n = Z^2 . S^2 / E^2

Dear Khalid,

Not exactly equal. I had assumed that the formula for sample size for the finite population would asymptotically approach the sample size estimate for the infinite population. When I put some arbitrary numbers into the formulae, I discovered that they were not even close to each other.

I note that the formula for the finite population appears to be independent of the variance in the population.

In order to answer this question/problem, several remarks have to be studied.

1. General remarks:

Research studies are usually carried out on sample of subjects rather than whole populations. The most challenging aspect of fieldwork is drawing a random sample from the target population to which the results of the study would be generalized. The key to a good sample is that it has to be typical of the population from which it is drawn. When the information from a sample is not typical of that in the population in a systematic way, we say that error has occurred. In actual practice, the task is so difficult that several types of errors, i.e. sampling error, non-sampling error, Response error, Processing error,…

In addition, the most important error is the Sampling error, which is statistically defined as the error caused by observing a sample instead of the whole population. The underlying principle that must be followed if we are to have any hope of making inferences from a sample to a population is that the sample be representative of that population. A key way of achieving this is through the use of “randomization”. There several types of random samples, Some of which are: Simple Random Sampling, Stratified Random Sampling, Double-stage Random Sampling... Moreover, the most important sample is the simple random sample which is a sample selected in such a way that every possible sample of the same size is equally likely to be chosen. In order to reduce the sampling error, the simple random sample technique and a large sample size have to be developed.

2. Specific remarks:

The following factors are highly affected the sample size and need to be identified:

• Population Size,
• Margin of Error,

· Confidence Level (level of significance) and

• Standard of Deviation.

Then, the sample size can be estimated by,

Necessary Sample Size = (z-score or t-value)2 * StdDev*(1-StdDev) / (margin of error)2 .