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