33:136:386 Lecture Notes - Lecture 13: Ti-89 Series, Standard Deviation, Weighted Arithmetic Mean

• School: Rutgers University
• Department: Business Analytics and Information Technology
• Course: 33:136:386
• Professor: Ely, Romulo

Document Summary

3/28/17 lecture week 9 (part 2) Bayesian analysis: additional info used to alter marginal probability: if a & b and third event c, conditionally dependent on a & b, p(a|c) = (p(c|a)p(a))/(p(c|a)p(a) + p(c|b)p(b)) Variance measure of dispersion: v^2 = sum[xi = e(x)]^2 * p(xi, square the difference between each value and expected value. Multiply resulting amounts by probabilities of each value, then sum them all: standard deviation is the square root of the variance. Example 2 with variance : [x0 2. 15]^2*p(x0) + [x1 2. 15]^2*p(x1) + .