43 lines
1.4 KiB
Markdown
43 lines
1.4 KiB
Markdown
---
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id:
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aliases: []
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tags: []
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title: Statistical Significance
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---
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# Statistical Significance
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[Statistical significance - Wikipedia](https://en.wikipedia.org/wiki/Statistical_significance)
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In statistical hypothesis testing,
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a result has statistical significance
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when a result at least as "extreme"
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would be very infrequent if the null hypothesis were true.
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More precisely,
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a study's defined **significance level**, denoted by $\alpha$,
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is the probability of the study rejecting the null hypothesis,
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given that the null hypothesis is true;
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and the p-value of a result, $p$,
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is the probability of obtaining a result at least as extreme,
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given that the null hypothesis is true.
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The result is said to be statistically significant,
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by the standards of the study, when $p \leq \alpha$
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The significance level for a study
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is chosen before data collection,
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and is typically set to 5% or much lower--
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depending on the field of study.
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The [**null hypothesis**](https://en.wikipedia.org/wiki/Null_hypothesis)
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(often denoted $H_{0}$)
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is the claim that the effect being studied does not exist,
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or that no relationship exists
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between two sets of data or variables being analyzed.
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If the null hypothesis is true,
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any experimentally observed effect is due to chance alone.
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In research,
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the researcher develops an [**alternative hypothesis**](https://en.wikipedia.org/wiki/Alternative_hypothesis)
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(often denoted $H_{A}$ or $H_{1}$)
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which claims that an effect or relationship _does_ exist.
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