Due date: Tuesday 3/31, 11:59pm
Conditional distribution
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Link to originalFrom conditional to joint, and back again
Suppose we have the following data about random variables and :
(a) Find the joint distribution .
(b) Find .
Solution
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Link to originalCashews in a can
A nut company markets cans of mixed nuts containing almonds, cashews, and peanuts. Suppose the net weight of each can is exactly , but the weight contribution of each type of nut is random. Let be the weight of almonds in a selected can and the weight of cashews. The joint PDF of and is given below:
Suppose that the weight of cashews in a particular can is . Calculate the probability that the weight of almonds in this can is more than .
Solution
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Link to originalNew and returning customers
A sales representative will randomly select and call 2 customers. The representative’s goal is to get each customer to complete a satisfaction survey. Each of these customers is categorized as “new” or “returning.” 70% of customers are new and 30% are returning. Let be the number of new customers that are called.
(a) Construct the PMF of , .
The probability of any new customer completing the survey is 0.15, and the probability of any returning customer completing the survey is 0.20. (Customers operate independently.) Let be the number of new customers that complete the survey.
(b) Construct , , and . (You should construct 3 separate PMFs.)
(c) Construct the joint PMF of and .
Solution
Conditional expectation
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Link to originalConditional distribution and expectation from joint PDF
Suppose that and have the following joint PDF:
Notice that the range of possibilities for depends on the value of .
First, show that . Then compute:
(a) (b) (c) (d)
Solution