A multiple-regression analysis is run to examine third variables as a follow-up to the study indicating that boys with unusual names are more likely to commit crimes. Unusual names, ethnic backgrounds, and geographical regions are all included as predictor variables. Even after controlling for all these variables, unusual names still predict criminal activity. Which of the following explains why this study doesn't establish causation?
There may be some other third variable. T/F

the answer will be the last one

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

this may not be at all, but i use the same website you're using for school, and if i'm stuck doing one of these i try to look for it on the section.

step-by-step explanation: the answer is 27. first multiply .32 by 25 which equals 8. then add 8 to 25 which gives you 33. then you subtract that from 6 since she gave 6 to her brother.

,, add !