| 1. | This by definition would also increase the number of Type II errors.
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| 2. | Increasing the sample size decreases the risk of a type II error.
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| 3. | Decreasing the probability of a type II error is very important.
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| 4. | A test's probability of making a type II error is denoted by ?.
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| 5. | A sensitive test will have fewer Type II errors.
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| 6. | A type II error is a false negative, not seeing an effect where one exists.
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| 7. | Negation of the null hypothesis causes type I and type II errors to switch roles.
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| 8. | All statistical hypothesis tests have a probability of making type I and type II errors.
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| 9. | What we actually call type I or type II error depends directly on the null hypothesis.
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| 10. | Our article at Type I and type II errors may or may not help to clarify this.
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