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.

true

step-by-step explanation:

a.) list the factors of 40.

1/2/4/5/8/10/20/40

b.) list the factors of 40 that represent the number of cans that could be on each shelf.

5

c.) how many different arrangements of cans are possible?

just one because if you put more on one shelf you will go way over 40 and the cabinet will probably break.

d.) what are the possible arrangements of the cans?

put 5 cans on each self to reach 40 cans in total.

e.) which arrangement uses all the shelves?

5 because you can put 5 cans on each shelf, and since there are 8 shelfs you are equally going to get 40 cans.