Chapter 10: Inference with the t - Distribution

1. Name 3 shared features between the normal and the t-distribution. 2. When do we use the t-distribution? 3. What is the difference between a Z-score and a t-score? 4. What is an unbiased estimate of a parameter? 5. How does a t-distribution differ in shape from the normal distribution? 6. Define degrees of freedom and explain how they affect the shape of the t-distribution. 7. Identify the formula for setting up the confidence interval for the population mean in a t-distribution. 8. Identify the formula for setting up the confidence interval for the difference between independent population means in a t-distribution. 9. Provide the 2 formulas used to find the standard error of the difference between independent population means. What formulas would we use to find the degrees of freedom when n1 = n2 and n1 n2. 10. Present the following data in the proper notation: With 99% confidence, the mean difference between males and females on a test of creativity lies between -3.67 and -0.96. ________________________________________. 11. List the basic assumptions when making inferences about population parameters in the t-distribution. 12. Define homogeneity of variance. 13. What can we assume when subjects have been randomly assigned to each group in an experiment? 14. How does a within-subjects design influence between-subjects variability? 15. What is a matched groups design? 16. From a mathematical standpoint, what happens to the standard error when there is little variability between subjects? What happens to the t-value? 17. What are some advantages and disadvantages of using dependent groups designs? 18. Describe the direct difference method. What is the formula for finding degrees of freedom? 19. Name 3 steps you can take to produce a powerful test. 20. Identify the steps that you would take in choosing an appropriate test of significance.