STAT151 Lecture Notes - Lecture 19: Confidence Interval, Statistic, Standard Deviation

• School: University of Alberta
• Department: Statistics
• Course: STAT151
• Professor: Omar Rivasplata

Document Summary

Recall that the sampling distribuion model of is centred at p, with standard deviaion. Since we don"t know p, we can"t ind the true standard deviaion of the sampling distribuion model, so we need to ind the standard error: Note that whenever we esimate the standard deviaion of a sampling distribuion, we will call it a standard error (se) We can look at this from ^p "s point of view. There"s a 95% chance that p is no more than 2 ses away from ^p. So, if we reach out 2 ses, we are 95% sure that p will be in that interval. In other words, if we reach out 2 ses in either direcion of ^p , we can be 95% conident that this interval contains the true proporion. Formally, what we mean is that 95% of samples of this size will produce conidence intervals that capture the true proporion o.