Type I and Type II Errors Flashcards
what is a type one error ?
a false positive - you reject the null hypothesis when you shouldn’t
what is a type two error ?
false negative - you reject the experimental hypothesis when you should reject the null hypothesis
why is a 1% significance level usually avoided ?
it is too stringent (increases the chance of not rejecting the null hypothesis, which is in fact false - type II error)
how can you remember whether it is a type II error ?
if the p-value is too sma_ll it is a type_II error
why is a 10% significance generally avoided ?
it is too lenient - it increases the chance of rejecting a null hypothesis which was in fact true - type I error)
what significance level do psychologists usually use ?
a 5% significance level - because this is a good compromise between making a type I and type II error
