I got a call the other day from a high school science teacher asking about the
following:
She is testing different brands of yogurt for acid neutralization by acidophilus
bacteria. Her students have measured the pH of yogurt then poured in a known amount of
acid and began measuring pH in intervals of 1 minute for 5 minutes. She has six
replicates for each of the types of yogurt for a total of 12 time series. She wants to
test if the mean concentration of acid is different in the two groups by taking the
initial pH value - final pH value for each replicate getting a total of six
differences per group then finds a mean of differences for each set. Finally, she
wants to take the means from each set of differences and do a hypothesis test mu1=mu2
using a t-test but can't figure out the degrees of freedom of the test and frankly I
am not quite sure either. Her idea is to take 12-2 degrees but others have said it
should be 6-1 degrees. I wonder if others out there can shed light on three issues:
1) Is the t-test approach she is using on solid statistical footing, and if so how
many degrees of freedom is to be used for the t-test?
2) If the t-test approach is not legitimate what type of statistical test can be used
to test the mu1=mu2 hypothesis? (keep in mind that these are high school students)
3) Is there a 'better' way to proceed with the analysis in the future for these types
of experiments?
If you want to answer could you please forward the response to my e-mail address and I
can forward them to her.
Thanks,
GP
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