STAT 541: Design Of Experiments
Statistics 541: Design Of Experiments
- No book for the rest of the semester
Design Of Experiments
Do students give higher evaluations in the morning?
Suppose we are interested in whether students give higher class
evaluations in the morning than in the afternoon. (Theory is based on
anectodotal studies.) How can we test this claim?
- Exp 1: Abba teaches morning classes for next 10 years. Bob
teaches afternoon classes for next 10 years. n=30, m=30.
- Exp 2: Abba does 5 years in morning (while Bob does 5 years in
afternoon) then then switches with Bob. n = 30, m =30.
- Alternative theory: n = 2, m = 2. (Maybe Bob is completely
tiard after his noon bike ride and hence doesn't teach well in
- Exp 3: Abba teaches both morning and afternoon classes each
semester. So does Bob, Charles, Dean, Edward, Fred, George.
Look at bob_afternoon - bob_morning and abba_afternoon -
abba_morning. One sample: n = 7.
- Alternative theory: morning students grade easier than
- Aside: do we care?
- Under this theory we would still choose to teach in the
- BUT, the deparmtnet can't do it on mass since that will
drive the afternoon students to the morning.
- Exp 4: Randomly assign students to classes. Solves all
problems but practical ones! (Ethics, scheduling conflects,
adminstration not liking it.) n = 1000s. m = 1000s.
- So what are the control variables of the deparment? When
classes are taught.
- Exp 5: Run only morning classes for 5 years, then run only
afternoon classes for 5 years. See difference.
- Alternative theory: Students are getting grumpier/easier with
- Exp 6: Randomly decide each semester to run only morning
classes or only afternoon classes. See difference. For 10
years we would get an n=10, m=10.
Handout on DOE
- Key items in design
- H0, H1 as science
- Xs, Ys
- what is a "row"?
- randomization, controls, data collection
- H0, H1 as statistics
- bad things: missing data, costs, time, interium analysis
- Some examples
- plan, model, key statistical question
- Rogaine vs. Gro-againe
- Science: prevention of balding
- what to measure?
- units of analysis. Parts of heads, or whole heads?
- randomization/data collection
- statistical hypothesis (beats rogaine, equal to or
- Missing data. Bored with poor results, moving out of
Sample size calculations
- signficance, power, sample size, signal/noise are key
- Goal: determine sample size from other items
- One sample problem
- Alpha says how far away x-bar has to be to be
- Beta for some delta says how far away x-bar has to be
from interesting point
- n determines ratio of two scales
- Ah, now the details begin
Last modified: Thu Mar 29 08:53:36 2001