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I'm trying to design an experiment to look at the effect three variables have on output quality in the production of resorbable screws and am having trouble working out any kind of power analysis to determine how many samples for each group of experiments I will need, and also how many steps I need to do for each of the variables.

Outline: I have three inputs which I can control, and I have a minumum and maximum value for each of these inputs which can be determined before the main experiments begin. I need to know how many permutations I will need to do to get statistically valid results (for example, if I have a minimum and maximum temperature, I could break that temperature range and do experiments at 10 equally spaced temperatures within that range, same for the other 2 variables... the problem is that I would then have 1,000 permutations to do experiments on, so I want to know how to determine the minimum number of samples I need to do for each of the 3 input variables to get statistically relevant data while having the minimum number of experiments).

Similarly, I need to know how to determine the minimum number of repeat samples I will need to for each permutation in order to ensure that I have statistically valid results without having to do thousands of experiments (if possible).



If you think you can help and want to see what I have so far, let me know and I can PM or post you more details. I have access to GPower, SPSS and matlab if anyone has any skills in using those

You don't need to give me the answers, just point me in the right direction to how to figure it out

Stupid stats module...