There is nothing like a statistical proof.

Eventually, it is all about plausibility. Is it plausible that (possible) differences between the experiments won't obscure (possibly) relevant aspects of the data?

If you are more specific about your particular data and experiment you mihgt hope for more specific answers ;)

There is nothing like a statistical proof.

Eventually, it is all about plausibility. Is it plausible that (possible) differences between the experiments won't obscure (possibly) relevant aspects of the data?

If you are more specific about your particular data and experiment you mihgt hope for more specific answers ;)

I would recommend using a repeated measures one way ANOVA provided that your data satisfies the test's assumptions or its robust exceptions. Otherwise, use a Friedman's ANOVA. You should run a test for sphericity (Mauchly). If it is significant then there are corrections to the ANOVA (Greenhouse-Geisser and Huynh-Feldt).

Furthermore, the philosophy of null hypothesis statistical testing is to make a decision at a certain level of confidence, rather than prove anything. For example, scientists have not proved the existence of the Higgs boson but they have very strong evidence that it exists.

You can use student t test, anova test or chy square test. It depends on what factors do you want to compare. 

Dear Perez! you can use Fisher Least Significance Defference (LSD) test for comparison. Thanks Ephrem

Dear Peter.

Thanks, for your information.

You can provide more information on this type of testing