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 |
About the class:
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
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