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Please help! If you could explain your reasoning too, I would greatly appreciate it!

Which statement best explains conditional probability and independence?

 

A) When two separate events, A and B, are independent, P(B|A)=P(A and B)P(A)=P(A)⋅P(B)P(A)=P(B). This means that the occurrence of event B first did not affect the probability of event A occurring next.

 

B) When two separate events, A and B, are independent, P(B|A)=P(A and B)P(A)=P(A)⋅P(B)P(A)=P(B). This means that the occurrence of event A first affected the probability of event B occurring next.

 

C) When two separate events, A and B, are independent, P(B|A)=P(A and B)P(A)=P(A)⋅P(B)P(A)=P(B). This means that the occurrence of event B first affected the probability of event A occurring next.

 

D) When two separate events, A and B, are independent, P(B|A)=P(A and B)P(A)=P(A)⋅P(B)P(A)=P(B). This means that the occurrence of event A first did not affect the probability of event B occurring next.

 
 May 3, 2021

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