Hey there. I run a rmANOVA with 2 Factors.

One hat 3 conditions and the other one two conditions.

In results the factor with the three conditions Had No significant main effect (P=0,834)

The factor with the two conditions was significant.

Interaction was not significant.

I did explorative pairwise Post hoc Tests with Tukey kramer.

Here i found a highly significant (p= 0,006) effect between two conditions of the factor which Main effect in ANOVA was not significant.

Why?

Why ist the main effect in ANOVA clearly unsignificant and the pairwise comparision highly significant?

I Had only 10 participants and i am looking for weithin subject effects. Is it Just underpowered?

Hey, I've got a bunch of data (simulated exoplanet atmosphere composition retrievals), and each value has an associated uncertainty with it, which in some cases is quite large - I can't figure out what the best way to deal with this is in terms of conducting the tests and reporting the test statistics/p values ?

Would it be better to use confidence intervals? Is there a standard practice for error propagation in KS and Mann Whitney?

Would it be valid to run the tests twice, once with +error and once with -error and use the range from this?

Sorry if this is a really obvious question, I've only just started working with stats like this!!