QTM 100 Lecture Notes - Lecture 13: Central Limit Theorem, Confidence Interval, Statistical Parameter

• School: Emory University
• Department: Quantitative Theory & Methods
• Course: QTM 100
• Professor: Ho Kim

Document Summary

Clicker: a 95% confidence interval for the true proportion of us citizens who are opposed to issuing traffic tickets from traffic cameras is (0. 57, 0. 63) based on a sample of 1000 individuals. Confidence interval for a population proportion: check assumptions, calculate the standard error of p: se= square root p (1 p )/n, identify z for your specified level of confidence, calculate the interval: p z se. If not, your data may not be representative of the population of interest, and your sample statistics could be biased: the observations are independent. This happens when either the underlying population is approximately normally distributed or the sample size large enough for the central limit theorem to apply. If not, cis produced by this method are not valid: calculate the standard error of x: se= s/ n, identify t for your specified level of confidence (df = n 1).