Stats Notes

Lesson 7 One sample to population T tests One-Sample Significant Difference Tests A great deal of inferential statistics is about using procedures to help us infer that a difference does or does not exist between two situations. Knowing whether two things are different allows us to make reliable, valid decisions about that information. How different does a result need to be before we can call it significant (or important)? Another way to ask this question is …

…are these two types called? 3. What are the two assumptions of a t-test? 4. What is the difference between a null and alternative hypothesis? 5. What is the formula for the degrees of freedom for a one-sample t-test? 6. When you have made a Type I error, what has happened? 7. When you have made a Type II error, what has happened? 8. What are the factors that affect power and which of these factors do you have control over?