STAT 2507 Lecture Notes - Lecture 8: Bias Of An Estimator, Interval Estimation, Point Estimation

• School: Carleton University
• Department: Statistics
• Course: STAT 2507
• Professor: Zahra Montazeri

Document Summary

Statistical inference: estimation -> estimator: x| (sample mean) hypothesis testing. E(x|) = new you can have more than 1 unbias choose a method that is less spread the closest to new(mean) is better this is called minimum variance margin of error: +- 1. 96 x standard error (se) (standard deviation of estimator) 1. n = 50, x| = 56. 4, s^2 = 2. 6 point estimate: is x| = 56. 4 margin error: +- 1. 96 s/root(n) = +- 1. 96 root(2. 6)/root(5) 1-alpha, 1-alpha(100%) confidence coefficient point estimator +- za/2 x standard error the z is for large sample (1-alpha)100% large ci for new point estimator +- za/2 se. X| +- za/2 sigma/root(n) z is the percentage of coverage of the z value itself such that it covers the right side (left side 95%) 1. n = 30, x| = 0. 145, s = 0. 0051, 90% ci, alpha = 10%, a/2 = 5%