I'm concerned that I may not be conceptualizing/applying multiple regression correctly; I would greatly appreciate some guidance.
Lets say that I'm trying to understand how to get a TV audience to watch more of my TV show.
In other words, I'm trying to influence my audience's motivation to watch.
A multiple linear regression has shown me that overall enjoyment of the show accounts for ~60% of the variance in the audience's motivation to keep watching. So it seems that if I increase the overall enjoyment, that will hopefully increase motivation to watch.
So how do I increase overall enjoyment? I then computed another multiple regression, which showed that a single good joke in an episode accounts for ~70% of the episode's overall enjoyment rating from the audience.
However, in my original regression, the regressor of 'single good joke' did not account for any of the variance in audience motivation.
So I have a sort of A>>B>>C situation; single good joke >> overall enjoyment >> increase motivation
Is it prudent to suggest that we should focus on producing one good joke per episode in order to increase enjoyment, and therefore increase audience motivation? I'm concerned because 'good joke' does not directly account for 'motivation' variance, so I'm not sure if I'm being ignorant of the logic of regression.
Any tips are appreciated. Thanks!
single_good_joke
variable is jointly significant with some other variable, for example (just a guess). $\endgroup$