Time and location:
Lecture: MWF 12:00pm - 12:50pm, KAP 148.Important Dates:
Course Content:
I plan to cover most of Chapters 6-11, plus possibly some material from the later chapters. Topics will include: properties of the normal distribution (including a review of the Central Limit Theorem); random sampling and estimation of
population parameters; confidence intervals; method of moments; maximum likelihood estimates; Cramer-Rao lower bound; testing hypotheses; likelihood ratio tests and goodness of fit; probability plots; discriptive methods for summarizing data; comparing two samples, parametric and
non-parametric methods.
Grading and Examination Policies
40% of the grade will be based on two midterm exams (20% each), 40% will be based on the final exam, 20% will be based on homework assignments/quizs.
The (one hour) midterm exams will be given in regular class time. The 2nd midterm exam will cover the material after the 1st exam. The final exam will be comprehensive, with an emphasis on the material covered since the second Midterm. The exam problems will be in the same style as the examples in lectures and/or homework problems. All exams are closed books, but you are allowed to bring one sheet of formulas. Calculators are allowed.
Homework problems will be assigned in lectures, and will be collected in discussion class once a week. The homework is aimed to help you prepare for the exams. You are encouraged to discuss the problems with your classmates, and to ask me or TA for help. But everybody should write your solutions independently.
Feedback and Questions
It is extremely important for me to get feedback and questions, both inside and outside class. You are very welcome to visit me during my office hours, and/or make appointments to see me at other time.