Processing math: 100%

You can also download a PDF copy of this study guide.

  1. Understand what might be reasonable null and alternative hypotheses for a given problem (note that for alternative hypotheses there may be more than one “right answer” since we have a choice between one-sided and two-sided hypotheses/tests).

  2. Understand the roles of the null and alternative hypotheses in a statistical test.

  3. Be able to correctly compute the appropriate test statistic (i.e., z or t) for a statistical test.

  4. Understand the definition of a p-value — it is a probability, but a probability of what?

  5. Understand how to compute a p-value based on a z or t test statstic.

  6. Understand the decision rule for whether or not to reject a null hypothesis.

  7. Understand what is meant by statistically significant and how it relates to the decision made be a statistical test.

  8. Understand how to conduct a statistical test concerning μ using a confidence interval.

  9. Understand simple versus composite hypotheses.

  10. How do we conduct a statistical test with a composite null hypothesis?

  11. Understand how to conduct a sign test — mainly how do we compute the p-value for the test?

  12. What are type I and type II errors?

  13. What is the probability of making a type I error (assuming the null hypothesis is true)?

  14. How does increasing/decreasing the significance level affect the probabilities of type I and type II errors (assuming such an error is possible)?

  15. What is meant by the power of a statistical test?

  16. What can be done to increase the power of a statistical test?

  17. As usual, be comfortable with notation (e.g., H0, Ha, μ, p, ˉx, s, n, ˆp, z, t, α).

Formulas/expressions you should understand when and how to use.

z=ˆppp(1p)/n t=ˉxμs/n np15,   n(1p)15