Type I and II errors (2 of 2)
Next section: One- and two-tailed
A Type I error, on the other hand, is an error in every sense of the word.
A conclusion is drawn that the null hypothesis is false when, in fact,
it is true. Therefore, Type I errors are generally considered more serious
than Type II errors. The probability of a Type I error (α)
is called the significance level
and is set by
the experimenter. There is a tradeoff between Type I and Type II errors.
The more an experimenter protects himself or herself against Type I errors
by choosing a low level, the greater the chance of a Type II error. Requiring
very strong evidence to reject the null hypothesis makes it very unlikely
that a true null hypothesis will be rejected. However, it increases the
chance that a false null hypothesis will not be rejected, thus lowering
The Type I error rate is almost always
set at .05 or at .01, the latter being more conservative since it requires
stronger evidence to reject the null hypothesis at the .01 level then
at the .05 level.
Next section: One- and two-tailed tests.