Stat 402A - Statistical Design and Analysis of Experiments (Agriculture and Biology)

Stat 402A - Spring 2008

Statistical Design and Analysis of Experiments, emphasizing Agriculture and Biology

Philip Dixon

Last updates:
- May 3: added office hours during finals week (see quick notes)
- May 3: posted my answers and comments on midterm 2.
- May 3: added citations for two "practical advice" papers to the end of the current readings page.
- May 3: For fun, you might enjoy Michael Friendly's gallery of good and bad graphs .
- May 1: posted apple1.txt and apple2.txt for the final exam
- April 30: posted hw 12 answers. These are draft and may be revised to fix typos and respond to commonly occuring mistakes.
- April 30: I may not have announced that hw 11 answers were available. They are.
- April 30: Posted final exam and two of the three associated data sets ( insulin.txt and stream.txt. The data sets for problem 1 (apple1 and apple2) will be posted tomorrow.
Quick Notes:
- The final exam is due Friday, May 9, by 5 pm.
  Turn it in to 3405 Agronomy (under the door if I'm not there) or the box in the Agronomy main office (2101 Agron).
  Office hours during finals week
  Monday: 2-3 pm, 3405 Agron. (I may be a bit late if a 1pm meeting in Wilson runs long
  Tuesday: 2-3 pm, 1436 Wilson
  Wednesday: 2-4 pm, 3405 Agron.
  Thursday: working with a visitor all day
  Friday: PhD oral exam followed by a PhD defense
  I will answer e-mails whenever I can, especially Thursday and Friday.
Information:

Reading Assignments (usually .pdf files, requiring Acrobat Reader):

Current and upcoming lecturesThese are 'assigned'. They provide another presentation or perspective on lecture details. I expect you to read (or skim, if suggested) these.
All assigned readings A compilation of assigned readings for all weeks.
Optional readings This list contains additional papers closely connected to lecture material. You may find one of these helpful if the assigned reading doesn't make sense.
References to additional material This is a list of papers on topics tangential to lecture material. These are for your benefit if you are interested in a topic. You are not expected to read these.

Homework:

Data sets, programs, and other handouts

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