One of my hypotheses is that Variable A and B predict Variable C, so I want to perfom regression analyses. My questions for this example:
1) Should I perform two separate simple linear regressions or a multiple regression with both A and B as predictors? What is the difference? (A and B do not correlate with each other).
2) Scatterplots for the associations of Variable C with A and B respectively look pretty random.
Correlations accordingly are also not significant. If I already now this, does it still make sense to do regression analyses? Besides linear regression, would another type of regression model be better to use? What should I report in my paper in that case?