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This document contains a set of short-form practice problems for a linear algebra final exam. The problems emphasize the use of set notation and cover various topics typically found in a linear algebra course, such as vector spaces, linear transformations, and matrix operations. Ideal for students looking to review key concepts and sharpen their skills before the final exam. Created by [Author Name], Year [e.g., Fall 2024], for [Professor Name or Course Number].
Typology: Exams
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This practice set is an amalgamation of former final exam questions offered over the last several semesters. Use this worksheet as an example of the types of questions and level of difficulty that you can expect on the exam.
Note that this worksheet emphasizes the material post-midterm 2, though all course content will be featured on the final exam. Don’t forget to study our midterm 1 and midterm 2 practice material as well.
(a) You send a printing job that will go to one of the printers at random. What is the probability that you will encounter a paper jam? (b) You send a printing job to a random printer and encounter a paper jam. What is the probability that you picked the least reliable printer? What is the probability that you picked the most reliable printer? (c) If you send another printing job to the same printer that jammed in part (b), what is the probability that it will jam again?
f (x, y) =
4 xy , 0 ≤ x ≤ 1 , 0 ≤ y ≤ 1 0 , elsewhere
(a) What is the probability that X + Y < 1? (b) Find the marginal density function for Y.
(a) What is the probability that the first green eyed person is fourth in line? (b) What is the probability that we have at most 2 green eyed people in the group? (c) What is the probability that most of the people in the group have green eyes? (d) If we photograph a group of 7 people every day, how many days would we expect to need until we find a group that includes at least one green eyed person?
(a) Let θ 1 =
X 1 + Xn 2
Compute the bias of θ 1 as an estimator for μ. Is θ 1 an unbiased estimator? (b) Let
θ 2 =
X 1 +···+Xn− 1 n− 1 +^ Xn n
Is θ 2 an unbiased estimator for μ? (c) Let θ 3 = θ 1 + kθ 2. Find the value of k for which θ 3 is an unbiased estimator for μ.
p(x, y) =
xy^2 15
, x = 1, 2 , y = 0, 1 , 2.
(a) Find the marginal pmfs pX (x) and pY (y). (b) Are X and Y independent? Why or why not? (c) Determine the means μX and μY. (d) Determine the covariance Cov(X, Y ).
f (x, θ) = (θ + 1)xθ, for 0 < x < 1 and θ > − 1.
Find the MLE for θ. Recall that (^) dxd (ax) = ax^ · ln a, for any positive real number a.
(a) If the forester samples n = 9 trees, find the probability that the sample mean will be more than 2 square inches above the population mean. (b) Suppose the forester would like the sample mean to be within 1 square inch of the population mean, with probability .90. How many trees must he measure in order to ensure this degree of accuracy?