In this video lecture, Professor Naomi Lowe will explain how to make sense of significance. She will discuss errors, effect size, and power. Type I error is the rejection of a true null hypothesis, while a type II error fails to reject a false null hypothesis.
Effect size quantifies the difference between groups. Cohen's D is an effect size that quantifies the difference between two means in terms of standard deviation.
Power is the ability to detect or reject a false null hypothesis. A false null indicates there is a difference between distributions. Power is determined by the sample size.
To calculate power, calculate mean and standard deviation for population two and predict the mean for population one. Determine the raw score cutoff point and use the normal curve table to figure out the probability of obtaining an extreme score.
Sample size, significance level, one or two-tailed tests, and procedure/effect size impact power.
Power can be used a-priori or retrospectively.
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In this video lecture, Professor Naomi Lowe explains how to make sense of significance. She covers errors, effect size, and power.
Length: 29 minutes
Copyright date: ©2010
Prices include public performance rights.
Not available to Home Video and Publisher customers.
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