# Calculate sample size (or experiment repetition no.) with unknown population

I am running an experiment and I would like what is a good method to calculate how many times I need to run an experiment, in other words, how many data points I will need to collect. The issue is that I do not know my population. Theoretically speaking, I could repeat the measurement many times (assuming no budget or time/budget or other constraints). On the other hand, I know the confidence interval that I'd like to have (95%) and a margin of error of no more than 5%

Assume no prior knowledge about the mean or standard deviation (essentially I will be running this experiment for the 1st time).

Any ideas or suggestions?

• Confidence interval for what?
– Dave
Dec 13, 2019 at 3:03
• For the statistic of interest (e.g. mean) for a metric.
– gplt
Dec 13, 2019 at 7:27
• It may be worth your time to look into power. The statistical power of a hypothesis test is, among other things, related to the number data points (number of subjects in the analysis, for instance). Dec 14, 2019 at 5:49
• Hi Adam, I thought about this but I am not dealing with hypotheses in my case. I am dealing with a continuous variable.
– gplt
Dec 16, 2019 at 19:37

• Hi Peter, yes, that is correct. I looked into power analysis but this approach requires having some sort of hypothesis which I don't have (and want to avoid if possible). What I think is right for my case is the following formula for the margin of error: $$\text{margin of error} = z \frac{\sigma}{\sqrt{n}}$$ where z is the z-score or standard score and which I solve for n and assuming a SD from prior knowledge. Happy to know if there are any alternative or better ways!