MATH 251, Probability and Statistics I, Fall 2001, Mon. Nov. 5,  Day 28

Finish Sec. 5.2 (Central Limit Th. and friends)
Examples of Central Limit Theorem in action.

Fuzzy Central Limit Theorem:  Data whose variation is due to many small independent random influences will have an approximately normal distribution.  (Or sometimes its logarithm will instead--the "lognormal" distribution)

Know:  a linear combination of independent normal random variables (p.401) is normal, with the mean and s.d. you can calculate using the algebra of means and variances..

Please  skim through Weibull dist. (pp.406-7) and sec. 5.3 (Control charts)--flavor only.
Confidence intervals (6.1) tend to be hard to grasp conceptually; I urge you to read at least pp. 434-442 in preparation for the next class.

Hand in: 
Linear combinations of independent normal r.v.'s (as p. 401) 
5.38 resistances add
5.39 compare chicks
5.41 muX - muY
5.44 delay avoidance+work methods
5.45 X+Y couples.
Read, discuss 
 5.40 Methods A and B
Optional 
5.42 X+Y+ Z
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