# What conclusion can I get when the variable is influenced by other but there isn't any correlation?

I am doing an analytic exploratory analysis.

If the target is a continuous variable and the attributes are all categorical (discrete values), in order to know if exist any influence on the target from the each attribute I am doing the ANOVA-test like this:

fvalue, pvalue = stats.f_oneway(df[y], df[x])
pvalue < 0.5


If that condition is true, there is a dependency between variables.

For all variables I get true dependency with ANOVA, but the values of the correlation are between -0.1 and 0.2.

What kind of conclusion can I do with this?

Can I say for example that if in the variables with negative correlation, I get new values in order to make that correlation a high positive value, then the target will get a higher value?

Any ideas?