- Return notes to student
- Anyone figure out how to get JMP to do a trimmed mean?
- Read chapter 1 of Myers Read sections 2.1-3, 2.9

- Y = beta
_{0}+ beta_{1}X_{1}+ ... + beta_{p}X_{p}+ epsilon - Goals
- prediction
- Causation (see talk this afternoon: 4:30 Paul Holland 111 Annenburg. A "big gun.")
- The betas might actually be interesting themselves

- We will focus on how to tell if your regression is statistically legitimate
- Leave you to decide if it makes any sceintific sense

Basic structure

- Simple means only 1 x variable (called independent variables, but I rarely use that termonology.)
- slope and intercept/centercept

- minimize sum (y - y-hat)
^{2}minimize sum (y - b

_{0}+ b_{1}X)^{2}Now define c = b

_{0}+ Y-bar - b_{1}X-bar is the deviation from the centercept. - b
_{1}= S_{xy}/S_{xx} - c = 0
- b
_{0}= Y-bar - b_{1}X-bar

- residuals = (y - y-hat) shouldn't be predicatable from X
- Residuals should have zero mean
- So residuals should be uncorrelated with X
- E(Y - b
_{0}- b_{1}) = 0 - Cov(Y - b
_{0}- b_{1}X,X) = 0

- E(estimate) = true paramenter (unbiased)
- Var(slope) = sigma
^{2}/S_{xx} - Var(centercept) = sigma
^{2}/n - Var(intercept) = sigma
^{2}(1/n + x-bar^{2}//S_{xx})

- Display (A lage chain of liquor stores would like to konw how much display space in its stores to devote to a new wine. Management believes that most products generate about $50 in sales per linear shelf-foot per month.)
- Tukey's bulging rule by hand and by picture

Last modified: Thu Jan 25 08:31:40 2001

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