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Which statement best explains conditional probability and independence? O When two separate events, A and B, are independent, the probability of either event occurring is the same. Therefore, P(A) = P(B) and P(A|B) = P(A). When two separate events, A and B, are independent, P(A|B) = P(B). This means that the probability that event A occurred first has no effect on the probability of event B occurring next. When two separate events, A and B, are independent, the probability of either event occurring is the same. Therefore, P(A) = P(B) and P(A|B) = P(B). == When two separate events, A and B, are independent, P(A|B) = P(A). This means that the probability that event B occurred first has no effect on the probability of event A occurring next.

Which statement best explains conditional probability and independence? O When two separate events, A and B, are independent, the probability of either event occurring is the same. Therefore, P(A) = P(B) and P(A|B) = P(A). When two separate events, A and B, are independent, P(A|B) = P(B). This means that the probability that event A occurred first has no effect on the probability of event B occurring next. When two separate events, A and B, are independent, the probability of either event occurring is the same. Therefore, P(A) = P(B) and P(A|B) = P(B). == When two separate events, A and B, are independent, P(A|B) = P(A). This means that the probability that event B occurred first has no effect on the probability of event A occurring next.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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help please answer in text form with proper workings and explanation for each and every part and steps with concept and introduction no AI no copy paste remember answer must be in proper format with all working
Which statement best explains conditional probability and independence? O When two separate events, A and B, are independent, the probability of either event occurring is the same. Therefore, P(A) = P(B) and P(A|B) = P(A). When two separate events, A and B, are independent, P(A|B) = P(B). This means that the probability that event A occurred first has no effect on the probability of event B occurring next. When two separate events, A and B, are independent, the probability of either event occurring is the same. Therefore, P(A) = P(B) and P(A|B) = P(B). == When two separate events, A and B, are independent, P(A|B) = P(A). This means that the probability that event B occurred first has no effect on the probability of event A occurring next.
Transcribed Image Text:Which statement best explains conditional probability and independence? O When two separate events, A and B, are independent, the probability of either event occurring is the same. Therefore, P(A) = P(B) and P(A|B) = P(A). When two separate events, A and B, are independent, P(A|B) = P(B). This means that the probability that event A occurred first has no effect on the probability of event B occurring next. When two separate events, A and B, are independent, the probability of either event occurring is the same. Therefore, P(A) = P(B) and P(A|B) = P(B). == When two separate events, A and B, are independent, P(A|B) = P(A). This means that the probability that event B occurred first has no effect on the probability of event A occurring next.
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