Following the confusion (on my part) here, and as suggested, I am presenting my question in a neutral way below:
Problem: I am looking at the relationship between "product research" (variable A) and "product purchase" (variable B). 'Product' means any consumer goods (e.g. toys, clothes etc.).
A and B are composite scores (i.e. made up of responses to several questions). The compositie scores for A corresponds to a five point scale (going from no research to a lot of research), while scores for B also corresponds to a five point scale (going from decision not to buy to always buy). I need to better describe my scale labels, but they are based on a five point Likert scale.
I am treating my composite scores as interval level data. I have checked the scatterplot and there is a linear relationship between A and B.
A selection of my data set is as follows:
Variable A - Product Research: 2.98 2.98 3.12 3.14 3.16 3.32 3.19 3.21 3.32 3.34 3.46 3.55 3.72 3.76 3.96 4.03 4.14 1.21 1.65 1.78 1.72 1.08 1.04 1.98
Variable B - Product Purchase: 3.54 2.53 2.52 3.14 3.09 3.34 2.57 3.11 2.99 2.89 3.45 3.39 3.26 3.77 3.68 3.86 4.03 1.22 1.34 1.68 1.65 1.09 1.32 2.09
Question 1 How should I calculate if a relationship exists betwen product research and product purchase?
Question 2 How do I find out if certain demographic characteristics such as gender and age influence the relationship between product research and product purchase?
Note: My focus is on the overall relationship between product research and product purchase and how this relationship is shaped by demographic characteritics.
In other words, I am NOT interested in the difference between males and females on its own; rather on the difference (if any) between the relationship of A and B for males and females. (unsure if this is the same thing but to me, there is a subtle difference)