CH-10 PPT - Testing hypotheses about proportions Tests of...

Info iconThis preview shows pages 1–9. 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

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: Testing hypotheses about proportions Tests of significance § The reasoning of significance tests § Stating hypotheses § The P-value § Statistical significance § Tests for a population proportion § Confidence intervals to test hypotheses Reasoning of Significance Tests Example: A coin is toss 500 times. It lands heads 275 times, which is a bit more than we expect. Is the coin fair or not? • Is the somewhat higher number of heads due to chance variation? • Is it evidence that the coin is not fair? x Stating Hypotheses Situation: We observe some effect and we have two explanations for it: 1) the effect is due to chance variation 2) the effect is due to something significant How to decide? Statement 1) = null hypothesis H 0 (the coin is fair) x The null hypothesis is a very specific statement about a parameter of the population(s). It is labeled H 0 and states “status quo”, previous knowledge, “no effect”, “the observed difference is due to chance”. It is the one which we want to reject. The alternative hypothesis is a more general statement about a parameter of the population(s) that is the opposite of the null hypothesis. It is labeled Ha and is the one we try to prove. Coin tossing example: H 0 : p = 1/2 ( p is the probability that the coin lands heads) Ha : p ≠ 1/2 ( p is either larger or smaller) Analogy with a criminal trial • H 0 : the defendant is innocent If sufficient evidence is presented, the jury will reject this hypothesis and conclude that • H a : the defendant is guilty One-sided and two-sided tests • A two-tail or two-sided test of the population proportion has these null and alternative hypotheses: H 0 : p = p 0 [a specific proportion] Ha : p p 0 • A one-tail or one-sided test of a population proportion has these null and alternative hypotheses: H 0 : p = p 0 [a specific proportion] Ha : p < p 0 OR The P-value Example-cont’d: A coin is tossed 500 times. It lands heads 275 times. H 0 : p = 1/2 vs. Ha : p ≠ 1/2 What is the chance of observing something like what we observed if H 0 is true?...
View Full Document

This note was uploaded on 11/05/2011 for the course BMGT 220 taught by Professor Bulmash during the Spring '08 term at Maryland.

Page1 / 26

CH-10 PPT - Testing hypotheses about proportions Tests of...

This preview shows document pages 1 - 9. Sign up to view the full document.

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