lecture+19 - Introduction to Hypothesis Testing Agenda •...

Info iconThis preview shows pages 1–10. 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

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: Introduction to Hypothesis Testing Agenda • Review Probability Project • Discussion the Hypothesis Testing Algorithm • One-sample hypothesis testing example Introduction to Hypothesis Testing Hypothesis Testing – researchers are able to structure problems in such a way that the researcher can use statistical evidence to test various theories about phenomena Research Hypothesis: a statement of what the researcher believes will be the outcome of an experiment or a study. Example: I believe that incorporation of Hawkes’ Learning System will improve performance of students above the current mean of 70% Types of Hypotheses (1 of 3) Types of Hypotheses (2 of 3) Statistical Hypotheses: a more formal structure derived from the research hypothesis; composed of two parts. a) Null hypothesis (Ho) – null hypothesis is probable; the historical view is assumed true b) Alternative (Ha) – a new theory is assumed true c) Example: Ho: p <= .70 Ha: p>.70 Types of Hypotheses (3 of 3) Substantive Hypotheses: a statistically significant difference does not imply or mean a material, substantive difference. Example: Let’s assume I took a sample of 10,000,000 students to assess this problem. Let’s assume that I find a statistically significant difference with an estimate p = . 702. While statistically significant, the finding has little practical relevance. Let’s Null and Alternative Hypotheses • The Null and Alternative Hypotheses are mutually exclusive. – Only one of them can be true. • The Null and Alternative Hypotheses are collectively exhaustive. • The Null Hypothesis is assumed to be true. • Equality is always in the null! • The burden of proof falls on the alternative hypothesis. One-tailed and Two-tailed Tests • One-tailed Tests • Two-tailed Test 40 : 40 : < ≥ μ μ a H H 18 . : 18 . : ≤ π π a H H 12 : 12 : ≠ = μ μ a H H The equality condition must ALWAYS be in the null hypothesis! 1. Establish hypotheses: state the null and...
View Full Document

This document was uploaded on 10/26/2011 for the course MASS COMMU 4303 at Texas State.

Page1 / 23

lecture+19 - Introduction to Hypothesis Testing Agenda •...

This preview shows document pages 1 - 10. Sign up to view the full document.

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