Quote:
Originally Posted by AmeliaG
I understand you used a linear model and you conclusively proved correlation. Wasn't that your point, that they correlate?
I'm saying that we don't know if engagement linearly increases views or views linearly increase engagement or if each increases the other for an exponential effect and, if so, which influences the other more. Does that make sense?
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Now I understand your point but I think you are confusing the things I was not trying to prove there was a correlation it was more to know if correlation existed IF it existed define how much correlated each variable are, now the graphs are showing that some variables have bigger correlation than other BUT does not show a cause effect relationship, as they said correlation does not mean causation, meaning yes there is a correlation between variables BUT this does not mean there is causation specifically there is a high correlation between likes and views BUT we can't say that higher number of likes cause higher number of views not that higher number of views cause higher number of likes, we have only established there is a positive correlation between these two variables.... and here comes the real issue with statistics it is not easy to REALLY establish cause and effect relationships.