### Theory of Statistics

 ``` course_number: STAT242 department: Statistics instructor: Marten Wegkamp course_ID: 20106 course_meeting_times: MWF 9.30-10.20 class_location: WLH 207 aka: stat242b/math242b/stat542b course_description: here ```

### Statistics 242b

Instructor: Marten Wegkamp
Office location: 24 Hillhouse Avenue
Office hours:
Phone: 432-0638
email: marten.wegkamp@yale.edu

Stats 242b (MWF 9.30-10.20) We will discuss the basic principles of mathematical statistics, such as sampling distributions, estimation, hypothesis testing, confidence intervals, regression etc.

Grades will be based on weekly homeworks, a midterm and a final exam.

After Statistics 241a, and  concurrently with or after Mathematics 222b or 225a or b, or equivalents. Statistics 200lb recommended.

TA: Laura McKinney

Textbooks:
John Rice Mathematical statistics and data analysis Duxburry Press 1995, 2nd edition ISBN 0-534-20934-3

#### Schedule:

week 1 (1/11 - 1/15): Survey sampling (chapter 7) Estimation of the population total, accuracy, normal approximation, confidence intervals.

week 2 (1/18 - 1/22): Survey sampling (chapter 7) Ratio estimators, stratification and allocation.

week 3 (1/25 - 1/29): Parameter estimation (chapter 8) Statistical models, methods of estimation.

week 4 (2/1 - 2/5): Parameter estimation (chapter 8) Statistical properties of estimators, information inequality

week 5 (2/8 - 2/12): Parameter estimation (chapter 8) Large sample theory, confidence intervals, sufficiency

week 6 (2/15 - 2/19): Testing hypothesis (chapter 9) Neyman Pearson lemma, most powerful tests.

week 7 (2/22 - 2/26): Testing hypothesis (chapter 9) Confidence intervals, p-values.

week 8 (3/1 - 3/5): Testing hypothesis (chapter 9) Likelihood ratio tests

MIDTERM

week 9 (3/22 - 3/26): Two sample problems (chapter 11)

week 10 (3/29 - 4/2): Analysis of variance (chapter 12)

week 11 (4/5 - 4/9):  Analysis of categorical data (chapter 13)

week 12 (4/12 - 4/16): Linear least squares (chapter 14) Simple linear regression

week 13 (4/19 - 2/23): Linear least squares (chapter 14) Matrix approach to linear least squares.

Exams:
Final exam: 4 May 1999, 9.00 am