The closer the linear correlation coefficient between two observations x and y is to 1, the more evidence one has to claim that x causes y

False. (Very!)

Step-by-step explanation:

Linear correlation carries no information about causation between two random variables. The closer the linear correlation coefficient to 1, the stronger the correlation between x and y, that is all. Correlation is a term reflecting a "degree of association" (or, cooccurrence, or co-incidence, if you will) but never of causality. There are many examples of correlations being misinterpreted as causal relationships. Particularly in popular reporting on outcomes of various medical studies.