Statistics Lectures - 19: Effect Size, Power, Statistical vs. Practical Significance
A series of free Statistics Lectures with lessons, examples & solutions in videos.
This is page nineteen of the series of free video lessons, “Statistics Lectures”. These lectures discuss effect size, power, statistical versus practical significance and independent and dependent samples.
Related Pages
17: t-Distribution & Confidence Intervals 2
18: Hypothesis Testing 1
20: One Sample z-Test & One Sample t-Test
21: Various Types Of Samples t-Test
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Statistics - Lecture 55: Effect Size
The effect size is a measure of the strength of an effect.
After running a statistical analysis, if you reject the null hypothesis it then makes sense to calculate
the effect size to determine the strength of the effect.
Statistics - Lecture 56: Power
Power is the probability of correctly rejecting the null hypothesis.
Beta is the probability of incorrectly rejecting the null hypothesis.
Statistics - Lecture 57: Statistical Vs. Practical Significance
To reject the null hypothesis is to say that you have found Statistical Significance.
Statistics - Lecture 58: Independent And Dependent Samples
One-Sample Methods:
- One sample z-test
- One sample z-test for Proportions
- One sample t-test In these tests, one sample was being compared to the population.
Two-Sample Methods:
- Samples are compared to other samples.
Samples are independent if members of one sample are unrelated to members of the other sample.
Samples are dependent if the members are related.
Statistics Lecture Series - Table Of Contents
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