ADMS 2320 Chapter Notes - Chapter 1-16: Exponential Distribution, Exponential Smoothing, Prediction Interval
3 Mar 2018
School
Department
Course
Professor
Document Summary
Population covariance x( i x y)( i y. P(a or b) = p(a) + p(b) - p(a and b) Cov(x, y) = xy = x( x y)( y. Laws of expected value: e(c) = c, e(x + c) = e(x) + c, e(cx) = ce(x) Laws of expected value and variance of the sum of two variables: e(x + y) = e(x) + e(y, v(x + y) = v(x) + v(y) + 2cov(x, y) Laws of expected value and variance for the sum of more than two variables. Mean and variance of a portfolio of two stocks. 2w v(r2) + 2 1w 2w cov(r1, r2) Mean and variance of a portfolio of k stocks k. Expected value of the sample mean ( xe. Standard error of the sample mean x n. Standard error of the sample proportion p p. Expected value of the difference between two means. Standard error of the difference between two means x.
