Contents
What increases the probability of a Type 1 error?
A Type I error is when we reject a true null hypothesis. Lower values of α make it harder to reject the null hypothesis, so choosing lower values for α can reduce the probability of a Type I error. So using lower values of α can increase the probability of a Type II error.
How can we reduce the chances of a type I error false positive?
One of the most common approaches to minimizing the probability of getting a false positive error is to minimize the significance level of a hypothesis test. Since the significance level is chosen by a researcher, the level can be changed. For example, the significance level can be minimized to 1% (0.01).
When to use Type I error in hypothesis testing?
As long as your experimental design is sound, you collect valid data, and the data satisfy the assumptions of the hypothesis test, the Type I error rate equals the significance level that you specify. However, if there is a problem in one of those areas, it can affect the false positive rate.
When is a false positive a type I error?
These false positives are called type I errors. A type I error occurs during hypothesis testing when a null hypothesis is rejected, even though it is accurate and should not be rejected. The null hypothesis assumes no cause and effect relationship between the tested item and the stimuli applied during the test.
Which is the best test for violating an assumption?
There are two tests that you can run that are applicable when the assumption of homogeneity of variances has been violated: (1) Welch or (2) Brown and Forsythe test. Alternatively, you could run a Kruskal-Wallis H Test. For most situations it has been shown that the Welch test is best.
When do you get a type I error?
If something other than the stimuli causes the outcome of the test, it can cause a “false positive” result where it appears the stimuli acted upon the subject, but the outcome was caused by chance. This “false positive,” leading to an incorrect rejection of the null hypothesis, is called a type I error.