Statistics Lectures - 19: Effect Size, Power, Statistical vs. Practical Significance

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.

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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.

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Statistics Lecture Series - Table Of Contents

• Descriptive Statistics
• Probability
• Correlation
• Inferential Statistics

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