- No book for the rest of the semester

- 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 the afternoon.)
- 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
afternoon students.
- Aside: do we care?
- Under this theory we would still choose to teach in the morning.
- 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 time.
- 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.

- Key items in design
- H0, H1 as science
- Xs, Ys
- what is a "row"?
- randomization, controls, data collection
- models
- H0, H1 as statistics
- n
- bad things: missing data, costs, time, interium analysis for stopping

- 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 different than?)
- Missing data. Bored with poor results, moving out of area, etc.

- signficance, power, sample size, signal/noise are key properties
- Goal: determine sample size from other items
- One sample problem
- Alpha says how far away x-bar has to be to be significant
- 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

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