That's actually pretty typical for behavioral science scatter plots. Getting p>.95 on a regression line is not something that is obvious from looking at the raw data.
Eyeballing something is useful to get theories that can actually explain the data. Numeric statistics are useful to disprove those.
If you are at an exploratory phase and your plots look a sky map, then you have a bad data representation. On that case you can't even extrapolate a positive correlation into a theory that one value will grow when the other grows on any specific case.
