Fall 2019: STA 4321 / 5325
Lecture: 8:30am - 9:20am on Monday, Wednesday, and Friday in TUR L011
Instructor: Aaron Molstad (amolstad@ufl.edu), 202 Griffin-Floyd
Office hours: Monday, Wednesday from 9:45 - 10:45am, Tuesday from 9:25 - 10:25am
Teaching assistant: Xiaoda Qu (quxiaoda@ufl.edu), 234 Griffin-Floyd
TA office hours: Tuesday, Thursday from 10:25 - 11:25am
Syllabus: [pdf]
Note that you must be logged into your UFL eLearning account to access course notes.
| |
Lecture |
|
Topics (suggested reading) |
|
| |
1 (8/21) |
|
Syllabus, basic set theory |
|
| |
2 (8/23) |
|
Basic set theory, sample spaces and events, probability (2.1 - 2.5) [notes] |
|
| |
3 (8/26) |
|
Probability, counting, permutations (2.6) [notes] |
|
| |
4 (8/28) |
|
Counting rules, examples [notes] |
|
| |
5 (8/30) |
|
Conditional probability, independence (2.7 - 2.8) [notes] |
|
Homework 1 (due Friday, September 6th): [pdf][examples][solutions]
| |
6 (9/6) |
|
Inclusion-exclusion, law of total probability (2.8, 2.10) [notes] |
|
| |
7 (9/9) |
|
Bayes rule, “Monty Hall” problem [notes] |
|
Homework 2 (due Wednesday, September 11th): [pdf][solutions]
| |
8 (9/11) |
|
Random variables, probability mass functions (2.11, 3.1, 3.2) [notes] |
|
| |
9 (9/13) |
|
Properties of distribution functions, expected value, variance (3.3) [notes] |
|
| |
10 (9/16) |
|
Expected value, variance, Chebyshev’s theorem (3.3) [notes] |
|
Homework 3 (due Wednesday, September 18th): [pdf][solutions]
| |
11 (9/18) |
|
Bernoulli random variables, Binomial random variables (3.4) [notes] |
|
| |
12 (9/20) |
|
Geometric distribution (3.5) [notes] |
|
Practice Problems 1: [pdf][solutions]
Practice Exam 1: [pdf][solutions]
Exam 1 (on 9/27) will cover Lectures 1-11: [complete notes]
| |
13 (9/23) |
|
Geometric and negative binomial distributions (3.5, 3.6) [notes] |
|
| |
14 (9/30) |
|
Examples, Poisson distribution (3.8) [notes] |
|
| |
15 (10/2) |
|
Hypergeometric distribution (3.8, 3.7) [notes] |
|
| |
16 (10/7) |
|
Continuous random variables [notes] |
|
Summary of discrete random variables: [pdf]
Homework 4 (due Wednesday, October 9th): [pdf][solutions]
| |
17 (10/9) |
|
Properties of probability density functions (4.2) [notes] |
|
| |
18 (10/11) |
|
Expected value and variance (4.3) [notes] |
|
| |
19 (10/14) |
|
Uniform random variables (4.4) [notes] |
|
Homework 5 (due Wednesday, October 16th): [pdf][solutions]
| |
20 (10/16) |
|
Exponential distribution [notes] |
|
| |
21 (10/18) |
|
Gamma distribution, Normal distribution (4.5, 4.6) [notes] |
|
| |
22 (10/21) |
|
Normal distribution, examples (4.5) [notes] |
|
Homework 6 (due Wednesday, October 23rd): [pdf][solutions]
| |
23 (10/23) |
|
Beta distribution, moment generating function (4.7, 3.9) [notes] |
|
| |
24 (10/25) |
|
Moment generating function, examples (3.9) [notes] |
|
Homework 7 (due Wednesday, October 30th): [pdf][solutions]
Exam 2 (on 11/4) will cover Lectures 12 - 24: [notes]
Practice Exam 2: [pdf][solutions]
| |
25 (10/27) |
|
Joint distribution of discrete random variables [notes] |
|
| |
26 (10/29) |
|
Joint distribution of continuous random variables[notes] |
|
| |
00 (10/31) |
|
Exam #2 Review |
|
| |
00 (11/4) |
|
Exam #2 [solutions] |
|
| |
27 (11/6) |
|
Independent random variables [notes] |
|
| |
28 (11/8) |
|
Probabilities involving two random variables [notes] |
|
| |
29 (11/13) |
|
Expected value of functions of two random variables [notes] |
|
| |
30 (11/15) |
|
Covariance and correlation [notes] |
|
Homework 8 (due Monday, November 18th): [pdf][solutions]
| |
31 (11/18) |
|
Covariance and correlation, conditional expectations [notes] |
|
| |
32.a (11/20) |
|
Conditional expectations, MGFs under independence [notes] |
|
| |
32.b (11/22) |
|
Functions of random variables, transformations |
|
| |
33 (11/25) |
|
Transformations, transformations using MGFs [note] |
|
| |
00 (12/2) |
|
Exam #3 Review |
|
| |
00 (12/4) |
|
Exam #3 |
|
Homework 9 (due Monday, November 25th): [pdf] [solutions]
Practice Exam 3: [pdf][solutions]
Exam 3 (on 12/4) will cover Lectures 24 - 33: [notes]