| 21. | The same is not true of M-estimators and the type I error rate can be substantially above the nominal level.
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| 22. | In practice, post hoc analyses are usually concerned with finding patterns and / or relationships between type I error rate.
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| 23. | The usual results for linear combinations of Type I Error Rate, the rate of falsely rejecting a true null hypothesis.
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| 24. | In this case, a Type I error would result in falsely detecting background brain activity as activity related to the task.
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| 25. | The type I error rate or "'significance level "'is the probability of rejecting the null hypothesis given that it is true.
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| 26. | Usually a type I error leads one to conclude that a supposed effect or relationship exists when in fact it doesn't.
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| 27. | Any statistical analysis involving multiple hypotheses is subject to inflation of the type I error rate if appropriate measures are not taken.
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| 28. | Bear F . Braumoeller further explores the vulnerability of the QCA family of techniques to both type I error and multiple inference.
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| 29. | A type I error occurs when detecting an effect ( adding water to toothpaste protects against cavities ) that is not present.
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| 30. | Before the test is actually performed, the maximum acceptable probability of a Type I error ( " ? " ) is determined.
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