Question

Explain the difference between statistical and practical significance.

Explain the difference between the null and alternative hypotheses.

When should a one-tailed test be used? What are the disadvantages to using a one-tailed test?

When should you use a two-tailed test?

Define a Type I error. In the behavioral sciences, what is the likelihood of a Type I error?

Define a Type II error. In the behavioral sciences, what is the likelihood of a Type II error?

Answer 1

1. the statistical significance relates to whether an effect exists whereas practical significance refers to the magnitude of the effect

2. null hypothesis is a hypothesis that says there is no statistical significance between the two variables and  is usually the hypothesis a researcher will try to disprove . An alternative hypothesis is one that states there is a statistically significant relationship between two variables.

3. A one-tailed test is where you are only interested in one direction. If a mean is x and you might want to know if a set of results is more than x or less than x. The disadvantage of one-tailed tests is that is has no statistical power to detect an effect in the other direction.

4.A two-tailed test is appropriate if you want to determine if there is any difference between the groups you are comparing.

5.In statistical hypothesis testing a type I error is the rejection of a true null hypothesis (a.k.a "false positive" false  conclusion), while a type II error is the non-rejection of a false null hypothesis ( "false negative" conclusion).