How to interpret scatterplot to test linearity b/w covariate and DV? I'm doing an ANCOVA on a fictitious dataset of math test results (DV) by group (n1 = 50 online training; n2 = 50 no training) with previous math ability as a (covariate) to see if there is a difference between students who did an online training or not on their test performance.
I already tested the following previous assumptions: homogeneity of variances, balanced design (equal samples of 50), and ANOVA to see if there is a difference b/w groups and test scores (w/out accounting for covariate) and there is.
I'm testing linearity b/w covariate and dependent with the following scatterplot:

I'm not sure if my interpretation is correct, but I see that they do interact, and that not all observations fall within the linear model. Does this mean the assumption is violated?
I tested for homogeneity of regression slopes, and found no statistically significant interaction between groups and covariate:

How do I continue with my analysis? How can I be sure if there is linearity or not?

Based off the scatterplot, I don't see any severe departures from linearity. The case would be different if it looked something like the data below, which has obvious issues of nonlinear data:

I'd say with all other assumptions checked, there is no major issue with your output here so long as there isn't anything else bizarre going on with your test data. This is a video which shows how to check assumptions in SPSS ANCOVAs btw.
