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Statistical Significance Vocab

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Simon Fraser University
PSYC 210
Cathy Mc Farland

Chapter 6 Vocabulary 1 Decision errors – incorrect conclusion in hypothesis testing in relation to the real but unknown situation despite doing the correct calculations and steps Type I error – alpha () – rejecting the null hypothesis when in fact it is true; getting a statistically significant result when in fact the research hypothesis is not true Type II error – beta () – failing to reject the null hypothesis when in fact it is false; failing to get a statistically significant result when in fact the research hypothesis is true -----------------------ECISIONERRORS --------------------------- Real Situation (in practice, unknown) Null Hypothesis True Research Hypothesis True Research hypothesis Conclusion Using Type I error -  Correct decision Hypothesis-Testing supported (reject null) Study is inconclusive (do not Correct decision Type II error -  Procedure reject null) Effect size ( ) – in studies involving means of one or two groups, measure of difference (lack of overlap) between populations; the usual standardized effect size measure increases with greater differences between means and decreases with greater standard deviations in the population, but isn’t affected by sample size; the difference between the population means divided by the population’s standard deviation Effect size conventions – standard rules about what to consider
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