use these rules to solve the problem above

Lift=" ay = BNET (note: Lift 1 means B \"lifts\" A) @ A=Some outcome (e.g. customer buys peanut butter) e B=Some conditioning event (e.g. customer buys bread). @ P(A)=Probability of outcome A. e@ P(B)=Probability of outcome B. e@ P(A|B)=Probability of outcome A given B (e.g. probability customer buys peanut butter given the customer bought bread) e@ P(ANMB)=Probability of both A and B occurring (e.g. customer buys peanut butter and bread.) Lift formula in words: If the probability of A given B is larger than the probability of A without considering B, then B \"lifts\" the probability of A occurring (i.e. we need Lift1) Practical example: \"If the probability of buying peanut butter increases when we put it next to the bread versus when PB is just randomly placed anywhere in the store, then we can lift PB sales by putting it next to the bread.\