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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?