04

(1) We have that


(2) Let . Then:

Now, since only if , we have that . Thus,


(3) Plugging in , , and into our PDF above, we have that .

06

(a)

(1) Suppose and are independent (since they have the same distribution, they are called independent identically distributed, or IID, random variables). Now suppose that . Notice that if , then and .


(2) For the first condition, we have:

and thus the first condition holds for any .


(3) For the second condition, by independence, we must have . Then we must have . Since , we must have that as the only solution.


(4) Thus, and , which signals that are constants, are the only values that satisfy the given condition.


(b)

(1) Define .

The mean is .

The variance is

Thus, .


(2) Note that . Standardize and use the lookup table.


(c)

(1) Let .


(2) Note that . Standardize and use the lookup table.

07

(a)

Marginal PDF of is:

Then:


(b)

center


(c)

center

08

(1) PDF of :


(2) CDF of :


(3) PDF of :

09

(a)

Case 1: :

center

Case 2: :

center


(b)

center

10

11

(a)

Fill the cells using the respective column sum or row sum.

  • We have , so
  • : We have , so
  • : We have , so
  • : We have , so

(b)

(1) Add up the probabilities in which either or .


(2) Alternatively, you could use the inclusion-exclusion principle using the marginal sums.

12

23

13

(a)

Find the area of the triangle, and find a formula for the PDF.

The area of the triangle is . Therefore the PDF is


(b)

(1) Integrate with respect to to find the marginal PDF for .


(2) Integrate with respect to to find the marginal PDF for .


(c)

(1) Compute the product and compare to .


(2) Consider the case wherein

Therefore, and are not independent.

14

(1) Compute the marginal distribution of by integrating with respect to .


(2) Compute the marginal distribution of by integrating with respect to .


(3) Determine independence by multiplying the marginal pdfs.

Since the product of the marginal PDFs equals the joint PDF, we conclude that and are independent.


(4) Compute the marginal distribution of by integrating with respect to .


(5) Compute the marginal distribution of by integrating with respect to .


(6) Determine independence by multiplying the marginal pdfs.

Therefore, and are not independent.

15

(1) Write the event in terms of .


(2) Write the terms , , and in terms of .


(3) Simplify expression for .