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Unformatted text preview: Introduction to Hypothesis Testing Agenda • Review Probability Project • Discussion the Hypothesis Testing Algorithm • Onesample 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. Onetailed and Twotailed Tests • Onetailed Tests • Twotailed 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...
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 Fall '11
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 Null hypothesis, Statistical hypothesis testing, Statistical significance, alternative hypotheses

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