February 27, 2014 (completed -- and ordered)
February 24, 2014 (Part II talk schedule shifted a week)
February 10, 2014 (re-spaced the Part I talks, and II too)
January 28, 2014 (Part I talks updated)
January 13, 2014
Stat 600 DH 1075 11:00 Monday Dr. Scott
Here is a tentative schedule and order of topics
for this semester. We have 10 students enrolled.
Please check this file for updates and changes.
I am likely to miss a week or two, so that the
whole schedule will shift easily.
Jan 13 - Introduction (D. Scott)
Jan 20 - MLK Holiday
Jan 27 - Student self-history presentations (3-5 minutes x 11)
(send ppt pptx doc docx pdf file to me beforehand)
Feb 3 - Introduction (D. Scott) -- continuation
Feb 10 - Part I talks (3)
Feb 17 - Part I talks (3)
Feb 24 - Part I talks (3)
Mar 3 - no class (spring break)
Mar 10 - Part I talk (1)
Scott portion
Mar 17 - Part II talks (3)
Mar 24 - Part II talks (3)
Mar 31 - Part II talks (3)
Apr 7 - Part II talks (1)
Apr 14 - TBA
Apr 21 - TBA
I. Feb 10, 17, and 24 (topics at bottom of this file)
We will have 10-15 minute presentations of Stat 280-level
material on the blackboard/whiteboard (3 or 4 each day).
You should assume that the "students" have already learned
all prior material in the book.
(I will assign topics from the list below. You may swap
with another student if you prefer or have a conflict.
Please confirm with me.)
Part I material comes from the 6th edition of "Introduction
to the Practice of Statistics" by David Moore, George McCabe,
and Bruce Craig. Margaret Poon has some desk copies.
(There probably are newer editions. Hopefully we can match
things up.)
Make a copy of your pages and return the book to her. When you
give your presentation, we will be asking questions, just as
you might expect/face if you were actually teaching.
You should strive for clarity (and inspiration) and can work
examples if you wish to use a portion of your time in that manner.
Note that there is a constant danger even for the advanced teacher
to pack in too much material. I recommend you concentrate on as
few points "to bring across" as possible. You should practice
try to get the timing right.
## Page Numbers Topic Presenter
Feb 10
1. 372-381 tests of significance Ryan Warnick
2. 382-389 mean tests, 2-sided Jonathan Stewart
3. 394-398 uses and abuses of tests ( - )
4. 401-409 power and errors ( - )
5. 417-435 t-test for mean Josh Taylor
Feb 17
6. 487-499 inference for proportions Jeong Hwan Kook
7. 525-534 two-way tables ( - )
8. 536-547 chi-squared tests Zeya Wang
9. 559-575 regression basics Nathan Berliner
Feb 24
10. 579-592 regression inference Liangcai (Lucky) Zhang
11. 607-614 multiple regression Donald Rogers
12. 615-624 case study ( - )
13. 637-654 one-way anova Pamela Luna
Mar 10
14. 683-689 two-way anova Katherine Shoemaker
Part II.
We will have ** 3 10-to-15 minute ** 431/532-level topic presentations
using electronic projection. (Think of this as "extra" material you
might wish to talk about as a supplementary topic.
This means a pdf or ppt file format, again on my computer.
The preferred choice is latex using the beamer class. For advanced
mathematics, latex is a requirement, although powerpoint is possible.
(You must use the latex thesis class eventually, so download
TeXShop and make a link to WikiBooks LaTeX and get at it.)
Your presentation should include graphics and
figures: feel free to create them (using R) or scan (or use screen
capture) from books/web (with attribution).
Partial list of topics: (And date of talk if scheduled.)
-----------------------------------------------------------------------------
set.seed(283); order(runif(10)) # 2 9 8 5 6 3 7 4 1 10
Mar 17 - Part II talks (3) Kook / Warnick / Wang
Mar 24 - Part II talks (3) Shoemaker / Stewart / Luna
Mar 31 - Part II talks (3) Taylor / Rogers / Berliner
Apr 7 - Part II talks (1) Zhang
Examples:
- multiple testing problem
- inverse gaussian distribution
- ridge regression Josh Taylor (2/17/14)
- Box-Cox transformations Katherine Shoemaker (2/24)
- bootstrap inference Liangcai Zhang (2/24)
- Chernoff faces
- quantum computing Pamela Luna (2/17/14)
- random number generation by rejection
- selecting priors in Bayesian inference
- robust or M estimation (variant of MLE)
- delta method Zeya Wang (2/27)
- variance stabilization transformations Donald Rogers (2/24)
- histogram as a constrained MLE Jonathan Stewart (2/17)
- Metropolis-Hastings algorithm Ryan Warnick (2/20)
- Order Statistics Nathan Berliner (2/24)
- Gibbs Sampling Jeong Hwan Kook (2/27)
- others
Part III.
"A" Statistics Examination Questions + topics as time allows