The regression R2 is a measure of: A. whether or not ESS > TSS. B. the square of the determinant of R. C. whether or not X causes Y. D. the goodness of fit of your regression line.

imma say 16%. sorry if its wrong. i'm doing the same stuff right now

step-by-step explanation:

85.560%

step-by-step explanation:

conditional probability is defined as:

p(a|b) = p(a∩b) / p(b)

in other words, the probability that a occurs, given that b has occurred = the probability that both a and b occur / the probability that b occurs.

in this example:

p(turns 64 | turns 44) = p(turns 64 & turns 44) / p(turns 44).

if someone turns 64, they must have already turned 44, so:

p(turns 64 | turns 44) = p(turns 64) / p(turns 44)

on page 42, we see that of the original 100,000, 94944 turn 44, and 81234 turn 64.   therefore:

p(turns 64 | turns 44) = 81234 / 94944

p(turns 64 | turns 44) = 0.85560

- (2, -7)

- lines r and s and lines t and u must be parallel