11:40 am - 12:55 pm, TR, LeConte College 206
Instructor: Dr. Karl Gregory
Instructor office: LeConte College 216C
Instructor office hours: Just stop by
Teaching assistant: Yizeng Li, yizeng [at] email.sc.edu
TA office: 209
TA office hours: Monday, 14:00 - 16:00
Course syllabus
| Lecture slides | Annotated | Topics | Corresponding section(s) of Casella and Berger |
|---|---|---|---|
| Lec_01.pdf | Lec_01_annotated.pdf Thur, Aug 25 video Tues, Aug 30 video (1/2) |
Set theory and basics of probability theory | 1.2 - 1.2.2 |
| Lec_02.pdf | Lec_02_annotated.pdf Tues, Aug 30 video (2/2) | Counting rules | 1.2.3 |
| Lec_03.pdf | Lec_03_annotated.pdf Thur, Sep 1 video |
Conditional probability and independence | 1.3 |
| Lec_04.pdf | Lec_04_annotated.pdf Tues, Sep 6 video |
Random variables | 1.4 - 1.6 |
| Lec_05.pdf | Lec_05_annotated.pdf | Expected value, variance, moment generating functions | 2.2 - 2.3, 3.6 |
| Lec_06.pdf | Lec_06_annotated.pdf | Suite of ought-to-know probability distributions, exponential families | 3.1 - 3.4 |
| Lec_07.pdf | Lec_07_annotated.pdf | Transformations of a random variable, location-scale families | 2.1, 3.5 |
| End Exam I Material | |||
| Lec_08.pdf | Lec_08_annotated.pdf | Joint and marginal distributions | 4.1 |
| Lec_09.pdf | Lec_09_annotated.pdf | Conditional distributions, independence | 4.2 |
| Lec_10.pdf | Lec_10_annotated.pdf | Bivariate transformations, multivariate, sums of independent rvs | 4.3, 4.6 |
| Lec_11.pdf | Lec_11_annotated.pdf | Covariance and correlation, inequalities, hierarchical models | 4.4, 4.5, 4.7 |
| Lec_12.pdf | Lec_12_annotated.pdf | Random samples, statistics, Normal pivotal quantities, non-central distributions | 5.1, 5.2, 5.3 |
| End Exam II Material | |||
| Lec_13.pdf | Lec_13_annotated.pdf Tues, Nov 1 video |
Order statistics | 5.4 |
| Lec_14.pdf | Lec_14_annotated.pdf | Convergence in probability, WLLN | 5.5.1 |
| Lec_15.pdf | Lec_15_annotated.pdf | Convergence in distribution, CLT, Slutsky's, delta method | 5.5.3, 5.5.4 |
| distribution summary sheet.pdf |
| Homework | Topics | Due | Solutions |
|---|---|---|---|
| hw_01.pdf | Set theory, probability axioms, counting | Tuesday, Sep 6th | hw_01_sol.pdf |
| hw_02.pdf | Basic probability, conditional probability, Bayes' rule, cdfs, pdfs, pmfs | Thursday, Sep 15th | hw_02_sol.pdf |
| hw_03.pdf | Expected value, variance, mgfs | Thursday, Sep 22nd | hw_03_sol.pdf |
| hw_04.pdf | Transformations of a random variable, mgfs, quantile functions | Tuesday, Oct 4th | hw_04_sol.pdf |
| hw_05.pdf | Joint and marginal distributions, conditional distributions, independence | Tuesday, Oct 18th | hw_05_sol.pdf |
| hw_06.pdf | Bivariate transformations, sums of independent rvs | Tuesday, Oct 25th | hw_06_sol.pdf |
| hw_07.pdf | Covariance, hierarchical models, inequalities | Tuesday, Nov 1st | hw_07_sol.pdf |
| hw_08.pdf | Random samples, Normal-population pivot quantities | Tuesday, Nov 15th | hw_08_sol.pdf |
| hw_09.pdf | Order statistics, convergence in probability | Tuesday, Nov 22nd | hw_09_sol.pdf |
| hw_10.pdf | Convergence in distribution, central limit theorem, Slutzky's, delta method | Thursday, Dec 1st ☃️ | hw_10_sol.pdf |
| Exams | Solutions |
|---|---|
| Exam_I.pdf | Exam_I_sol.pdf |
| Exam_II.pdf | Exam_II_sol.pdf |
| Final_Exam.pdf | Final_Exam_sol.pdf |
| Exams from fa 2021 | Solutions |
|---|---|
| Exam_I.pdf | Exam_I_sol.pdf |
| Exam_II.pdf | Exam_II_sol.pdf |
| Final_Exam.pdf | Final_Exam_sol.pdf |