Title explains it all. I want to know which test is the most appropriate to track weight loss / weight gain on a weekly basis in order to create a confidence interval, to see if my expected rate of loss/gain is in that confidence interval. It makes it easier to see if I'm stalling and have to adjust calories.

Some extra info:

  • Measurements will be taken each morning, so no bias (although water weight can be a bitch)
    • Although there are 7 days in a week, I can't take a measurement every morning. Some weeks will have 7 out of 7, other 6 out of 7, ...

I'm not sure if the T-Test is the most reliable for this because the measurements are not independent. I'm also not sure about normality since it's only a sample size of maximum 7. Any idea which test is the most appropriate?

Thanks for reading


You likely need a paired t-test here, which is appropriate when you have paired (dependent) data (e.g., before/after some new drug was administered, before/after some new diet regimen). t-tests are appropriate for small samples, so I believe this will suit you well.

  • $\begingroup$ Thanks for the answer! It's just that I'm using this personally and it's sometimes not possible to have 7 out of 7 measurements every week (work, ...). How would you compare for example week one (with 6 samples) with week two (with 5 samples)? $\endgroup$ – Anon Sep 19 '17 at 19:50
  • $\begingroup$ @Anon The paired t-test requires the same number of samples for each group. For situations like 5 samples in one week and 6 samples in the other, perhaps Friedman's (non-parametric) test for repeated measures (ANOVA) would be most appropriate... but ANOVA is for more than 2 groups. $\endgroup$ – compbiostats Sep 19 '17 at 19:53
  • $\begingroup$ I guess I will have to start experimenting with that. Thanks! $\endgroup$ – Anon Sep 19 '17 at 20:01

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