part14 - Public Health 6450 Fall 2011 Lynn Eberly and Andy...

Info iconThis preview shows pages 1–7. Sign up to view the full content.

View Full Document Right Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: Public Health 6450 Fall 2011 Lynn Eberly and Andy Mugglin Division of Biostatistics School of Public Health University of Minnesota ph6450@biostat.umn.edu Part 14 Review CIs for the Difference of Two Proportions from the Binomial Setting Hypothesis Tests for the Difference of Two Proportions Arising from the Binomial Setting Turning Point Evaluation Evaluation of Turning Point Technology Eberly and Mugglin PubH 6450 Fall 2011 Part 14 2 / 25 Review CIs for the Difference of Two Proportions from the Binomial Setting Hypothesis Tests for the Difference of Two Proportions Arising from the Binomial Setting Where are we going? Previously: I One-sample hypothesis testing and CIs for H : p = p (Chapter 8.1) Current topic: I Two-sample hypothesis testing and CIs for H : p 1- p 2 = p (Chapter 8.2) Next topic: I Other approaches for comparing proportions that arise from the Binomial setting (not in M,M&C) Eberly and Mugglin PubH 6450 Fall 2011 Part 14 3 / 25 Review CIs for the Difference of Two Proportions from the Binomial Setting Hypothesis Tests for the Difference of Two Proportions Arising from the Binomial Setting CLT-based CI and test for a Binomial proportion For a binomial variable X , when n p 15 and n (1- p ) 15, a 100 C % confidence interval for the proportion of successes p is p z * r p (1- p ) n . For testing a proportion, when np 10 and n (1- p ) 10, with H : p = p , we use the z-statistic based on p = X / n : z = ( p- p ) q p (1- p ) n . Eberly and Mugglin PubH 6450 Fall 2011 Part 14 4 / 25 Review CIs for the Difference of Two Proportions from the Binomial Setting Hypothesis Tests for the Difference of Two Proportions Arising from the Binomial Setting CLT-based CIs Plus Four CIs Structure of CIs for two-sample problems Our two-sample CI and test statistic formulas also have the same common structure as the one-sample formulas: estimate (quantile)(std.error) test statistic = estimate - null value std.error except here estimate is a difference between two groups and std.error is the standard error of that difference, just as we saw in Part 12 for testing the difference of population means. Next well consider these same structures for the difference of proportions. Eberly and Mugglin PubH 6450 Fall 2011 Part 14 5 / 25 Review CIs for the Difference of Two Proportions from the Binomial Setting Hypothesis Tests for the Difference of Two Proportions Arising from the Binomial Setting CLT-based CIs Plus Four CIs Assumptions in two-sample proportion problems The goal of inference here is to compare a proportion across two groups. We assume: I The first group is drawn as a simple random sample of size n 1 from one population. Their number of successes X 1 B ( n 1 , p 1 ), so p 1 = X 1 / n 1 ....
View Full Document

This note was uploaded on 11/21/2011 for the course PUBH 6450 taught by Professor Andymugglin during the Fall '10 term at Minnesota.

Page1 / 25

part14 - Public Health 6450 Fall 2011 Lynn Eberly and Andy...

This preview shows document pages 1 - 7. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online