1) How might the selection of a given tail test impact the Type I or II error, if any?
2) If the problem itself is not yet stated how might a researcher know which type of -tail test to use?
3) Might there be instances where a test is looking for a section of the area under the curve and not just the extreme ends?
1) How might the selection of a given -tail test impact the Type I or II error, if any?
Choosing an alpha level is tricky because it sets the level at which we will reject the null hypothesis. And there is a chance that the higher this value is, the greater the chance that we will falsely reject a true Ho.
To give you an analogy, in a court of law, we assume people are innocent (the null hypothesis) until proven guilty.
A Type I error would be finding an innocent man guilty.
A Type II error would be letting a guilty man go free.
By decreasing our error or alpha level, we will increase the chance of a …
The solution of a tail test is analyzed in the following solution.