Probability
Math 336
Brad Hartlaub
Fall 2016
Daily Agendas
- August 26
- August 29
- August 31
- Sept. 2 - Problem Session
- Sept. 5
- Sept. 7
- Sept. 9 - Problem Session
- Sept. 12
- Sept. 14
- Sept. 16 - Problem Session
- Sept. 19
- Sept. 21
- Sept. 23 - Problem Session
- Sept. 26 - Problem Session
- Sept. 28
- Sept. 30
- Oct. 3 - Problem Session/Review for Exam
- Oct. 5 - Exam #1
- Oct. 10 - Uniform and Normal Dist; Transformation of Variables Technique #2
- Oct. 12
- Oct. 14 - Problem Session (HW #5 and HW#6)
- Oct. 17 - Continue with Exponential and Gamma distributions
- Oct. 19
- Oct. 21
- Oct. 24 - Problem Session
- Oct. 26 - Problem Session
- Oct. 28
- Oct. 31 - Problem Session
- Nov. 2
- Nov. 4 - Complete covariance and correlation properties
- Nov. 7 - Problem Session
- Nov. 9 - Problem Session
- Nov. 11
- Nov. 14
- Nov. 16 - Problem Session/Review for the Exam
- Nov. 18 - Exam #2
- Nov. 28 - Proof of the CLT
- Nov. 30 - Probability generating functions and lab time for projects
- Dec. 2 - Lab time for projects
- Dec. 5 - Project Presentations
- Mary Liz Brady and Caroline Daugherty - Inverse Transformations and Simulation
- Boning Shi and Tudor Stoian - Student's t distribution
- Dec. 7 - Project Presentations
- Derek Foret and Oliver VandenBerg - Bayesian Estimation and Inference
- Alexander Powell, Ethan Shapiro, and Nico Danner - Beta distribution and estimation for NBA shooting
- Dec. 9 - Project Presentataions
- Carrie Stevens and Josh Abrams - Pareto Distribution and Applications
- Cameron Feenstra and David Resnekov - Markov Chains
Homework Assignments
- HW#1 - Due on Friday, Sept. 2
- HW#2 - Due on Friday, Sept. 9
- HW #3 - Due on Monday, Sept. 19
- HW #4 - Due on Friday, Sept. 23
- HW #5 - PS on Monday, Oct. 3; Theoretical Exercises are due on Oct. 14
- HW #6 - Due on Friday, Oct. 14
- HW #7 - Due on Monday, Oct. 24
- HW #8 - Due on Monday, Oct. 31
- HW #9 - Due on Monday, Nov. 7; Problem 22 and Exercises 10, 35, 45, and 48 will be collected on Friday, Nov. 11
- HW #10 - Due on Wednesday, Nov. 16
Exam Samples
- See P:\data\math\hartlaub\probability
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