Q1) We are given here that:
P( pizza ) = 0.8,
P( salad) = 0.7,
P( salad and pizza ) = 0.6
Using law of additivity of probability, we have here:
P( salad or pizza) = P(salad) + P(pizza) - P( salad and pizza ) =
0.8 + 0.7 - 0.6 = 0.9
Therefore 0.9 is the required probability here.
Q2) We are given here that:
P( pizza ) = 0.8,
P( salad or soup) = 0.7,
Now we are given here that 60% of the customers ordered pizza after
they ordered salad or soup, therefore, we are given the conditional
probability here as:
P( pizza | salad or soup) = 0.6
Using Bayes theorem here, we get here:
P( pizza and salad or soup) = P( pizza | salad or soup)P( salad or
soup) = 0.6*0.7 = 0.42
Therefore 0.42 is the required probability here.
Q3) a) Probability that the first ball is red and second is
green is computed here as:
= P(red)P(green given that first ball was red)
= (3/9)*(4/8)
= 1/6
= 0.1667
Therefore 0.1667 is the required probability here.
b) As we are drawing with replacement here, the probability here
is computed as:
= P(red)P(green)
= (3/9)*(4/9)
= 0.1481
Therefore 0.1481 is the required probability here.
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