TA office hours: Tuesdays 5:30-6:30 pm in Eck 131, except
exam week, when office hours are Tuesday 1:00-3:00.
Review session: Fridays 4-5pm in Eckhart 203 (not in week 1)
Per Mykland's office hour will vary, usually on Monday,
in Eckhart 128. Week 1: Monday 10/3, 1 pm, Week 2: Monday 10/10, 1 pm,
Week 3: Monday 10/17, 1 pm (cancelled). The Week 4 office hour is also
cancelled. Week 5: Monday 10/31, 1 pm. Week 6: Monday 11/7, 1 pm.
Week 7: canceled. Week 8: Monday 11/21, 1 pm. Week 9: Monday 11/28, 1
pm. Week 10: Monday 12/5, 1 pm.
Midterm: Wed Nov 9, Final: Wed Dec 7 (6-9 pm). Room: Kent 107
Extended office hours before the midterm: TA office hour on
Tuesday is two hours: 5:30-7:30 pm in Eck 131. As usual Per has office
hour Monday 1-2 in Eck 128.
Extended office hours before the final: TA office hour on
Tuesday is two hours: 1-3 pm in Eck 131. As usual Per has office
hour Monday 1-2 in Eck 128.
Class is each Wednesday 6-9 pm, except 10/19 and 11/23 (the day
before Thanksgiving). There will be class on Friday 11/4 and 11/18,
also 6-9 pm.
The following rules apply to HW: you are welcome and encouraged
to cooperate, or to work in a group. However: HW has to be turned in
separately for each person, and an effort should be made to make
HWs for people in the same group as different as possible. One way to do this
is to discuss the problems, but not compose a joint solution.
All members of a group need to declare their group on each HW.
Collaboration with undeclared other students may constitute a breach
of academic rules, and is a serious matter.
The following rules apply to midterm/final: you are allowed
one ``cheat sheet'' (8 1/2 x 11 inches, one sided, hand written, not
reproduced by copy machine or electronically). For the final,
the cheat sheet can be two sided.
Otherwise, the exam
is closed book. You are not allowed (and will not
need) any calculator.
Midterm syllabus: Lectures 1-5, HW 1-5, Chapters
1-4 in Shreve I. You will not be asked to do any coding in R or Splus.
Final syllabus:click
here
If basic probability becomes a problem:.
A good description is the first four chapters of
John Rice's Mathematical Statistics and Data Analysis (2nd ed., Duxbury
Press). This is the textbook in Stat 24400, and can be found at the
University Bookstore.
An even more basic book, extremely well written, is
Statistics by D. Freedman, R. Pisani, and R. Purves (3rd ed,
Norton). This is the textbook in Stat 20000, and can be found at the
University Bookstore.
So long as we are in the finite state space setting: proofs for conditional
expectations and Radon-Nikodym derivatives should be done by
reformulating the problem in terms of conditioning on sets in
partitions.
