vault backup: 2024-02-02 12:42:57
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- A qualitative variable of interest summarized by percentages
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- Can use a box with tickets of 1s and zeros to represent the population
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If an observed value is too many SEs away from the expected value, it is hard to explain by chance.
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### Null Hypotheses
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| Term | Description |
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| ---- | ---- |
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| Null Hypothesis | This is a statement about a *parameter*. It's a statement about equality. The chance of getting *x* is *y%*. |
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| Null Hypothesis | This is a statement about a *parameter*. It's a statement about equality. The chance of getting *x* is *y%*. A null hypothesis isn't proven true, you either prove it wrong (reject it), or don't (fail to reject). |
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| Alternative/Research Hypothesis | What the researcher is out to prove, a statement of inequality. (Less than, greater than, not equal to). |
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| One-tailed test | Use when the alternative hypothesis says that the % of 1s is *less than* or *greater than* expected. It's one sided. |
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| Two tailed test | When something is not equal to the expected. |
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| One-tailed test | Use when the alternative hypothesis says that the % of 1s is *less than* or *greater than* expected. It's one sided, because the area of importance on a distribution only has one side, and extends all the way outwards, away from the normal curve. |
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| Two tailed test | Use when something is *not equal* to the expected. It's called a two tailed test because the area of significance has two sides |
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## z tests for averages
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This test will look very similar to a z test for percentages
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You
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## P Value
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The chance of observing at least a sample statistic, or something more extreme, if the null hypothesis is true.
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If the p-value is less than *5*%, reject the null hypothesis.
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