Link(s):
Weekly postings:
| Posted on/by | Reading | Homework problems | Due date | Basic problems |
| 2/19 | Handout "Estimation based on IID data". Textbook reading: Definition 5.1.1, Theorem 5.1.1 and Definition 5.1.2. | Some of Problems 1-3 (16 points; extra points will not be counted) | 3/4 | Problems 1,2 |
| 2/26 | Handouts "Maximum likelihood estimation" and "Method of moments estimators". Textbook reading: Theorem 6.1.1, Definition 6.1.1, Example 6.1.2, Example 6.1.3 | Some of Problems 4-8 (15 points; extra points will not be counted) | 3/11 | Problems 6-8 |
| 3/5 | Handout "Evaluation of estimation accuracy". Textbook reading: Definition 4.1.3, Theorem 6.1.2, Definition 7.1.1 | Some of Problems 9-10 (16 points; extra points will not be counted) | 3/18 | Problem 9 and Problem 10(c)-(f) |
| 3/12 | Handouts "Numerical optimization using R" and "Sufficient statistics and factorization theorem". Textbook reading: Section 7.2 (after Theorem 7.2.1). | Some of Problems 11-14 (16 points; extra points will not be counted) | 3/25 | Problems 14, 11(c), 13(a) |
| 3/19 | Handouts "Sufficient statistics and factorization theorem" and "Minimum variance unbiased estimators" (till Example 1). Textbook reading: Theorem 7.3.1, Theorem 7.3.2, Definition 7.4.1 | Some of Problems 15-17 (8 points; extra points will not be counted) | 4/1 | Problems 15, 16 |
| 3/26 | Handout "Minimum variance unbiased estimators". Textbook reading: Section 7.4, Theorem 7.9.1 | Some of Problems 18-22 (16 points; extra points will not be counted) | 4/8 | Problem 21 and Problem 20(a)(b) |
| 4/2 | Handouts "Minimum variance unbiased estimators" (Fact 3) and "Minimum sufficient statistics and order statistics" (till Example 1) | Some of Problems 23-24 (4 points; extra points will not be counted) | 4/22 | Problem 23 |
| 4/9 | Handout "Minimum sufficient statistics and order statistics" | Some of Problems 25-26 (8 points; extra points will not be counted) | 4/29 | Problem 26(c) |
| 4/23 | Handout "Confidence intervals" | Some of Problems 27-30 (16 points; extra points will not be counted) | 5/6 | Problems 27,28,30 |
| 4/30 | Handout "Central limit theorem and approximate confidence intervals" (till Example 3) Textbook reading: Theorem 5.1.1, Theorem 5.1.4, Theorem 5.2.2, Theorem 5.2.5, Theorem 5.2.10, Theorem 5.3.1 | Some of Problems 31-34 (16 points; extra points will not be counted) | 5/13 | Problems 32-34 |
| 5/7 | Handouts "Central limit theorem and approximate confidence intervals" and "Hypothesis Testing" | Some of Problems 35-37 (12 points; extra points will not be counted) | 5/20 | Problem 35 |
| 5/14 | Handout "Hypothesis Testing" (Example 5 will be discussed next time) | Some of Problems 38-39 (4 points; extra points will not be counted) | 5/27 | Problem 39(a) |
| 5/21 | Handout "Central limit theorem and approximate confidence intervals" (Fact 4) | None | None | |
| 5/28 | Handouts "Hypothesis Testing" and "Goodness of fit tests". Textbook reading: Section 4.7 (till Example 4.7.2) | Some of Problems 40-44 (8 points; extra points will not be counted) | 6/3 | Problem 41 |