One of the peculiarities of statistics is that sampling error is not dependent on the size of the population from which the sample is drawn. Sampling error decreases relatively little after the 30th sample. However, if it is known beforehand that a population consists of more than one subpopulation, it may be necessary to "stratify" the sample to ensure that each of the subpopulations is sampled. For example, if you wish to sample a species that includes two subspecies, you may need to take a sample of 30 from each subspecies. Of course, if you wish to measure traits that are rare in a population, you may have to increase your sample size beyond 30 to take that rarity into account.
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Reasonable sample size depends largely on what it is you are measuring. A simple mean can be determined accurately with a sample of 30 or more. A diversity index, which is based on number of species and the numbers of representatives of each should be made on samples of at least 100; 400 is better.
In student research, it is always demanded that students should provide a calculation on how they arrived at the sample size. But what happens when the total population is not known to the researcher for a qualitative study.
In such cases, sample studies are done. Mean and standard deviation of each sample is computed. If the distribution of these sample means is a normal distribution, the mean of the sample means grand mean etc. could be computed using standard statistical techniques.
the sample size determination for unknown population?
for exaple some body wants to do research and he wants to determine the sample size because the population size is not known
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