Test 5 Review

Test Reviews:

These Test Reviews are not intended to replace doing the classwork and doing the homework These are not lists of objectives for the chapters nor are they complete lists of the topics. The textbook and homework provide those. These Test Reviews focus on topics and problems that students in previous semesters have been somewhat more likely to make mistakes on than the rest of the material.

It is pointless to even read these questions until you have read the chapters and done the homework. After that, you might want to write out answers to the questions (maybe conferring with other students in your class) and then bring the questions and your answers to the instructor or a tutor so that they can help you with any misunderstandings you have.

Test 5:

This test focuses on the material covered on Tests 3 and 4 and the new material in Chapters 22 and 23. Look over the reviews for Tests 3 and 4 as well as this review. Be sure that your notes address all the types of problems on Tests 3 and 4 as well as the new material.

  1. For the chi-square test of independence, do you know how to write the hypotheses? Also, it is VERY important not to mix up which is the null hypothesis and which is the alternative hypothesis. That will cost you a lot of points on the test if you do it incorrectly.
  2. If your data is in percentages rather than actual numbers of observations, can you do a chi-squared test on it in that form?
  3. Be sure that you copy the formula for the chi-squared statistic correctly, with only the numerator squared.
  4. You shouldn't round off expected values to the nearest integer. Leave a decimal place or two. Expected values are averages.
  5. The chi-squared test of independence in a two-by-two two-way table is equivalent to the two-sided test comparing two proportions we learned in Chapter 20. However, there is no comparable equivalent to the one-sided test. Don't interpret the result of the chi-squared test as if it is equivalent to the one-sided test.
  6. On a regression problem from this chapter, you will not be asked to compute the sample means, standard deviations, the correlation coefficient, or the regression coefficients, nor will you be asked to compute several different residuals (maybe one). However, you might be asked to do anything else we covered in Chapters 4 and 5. Review all of that.
  7. How do you determine from the statement of the problem which is the response variable? What does that mean for the scatterplot and what does it mean for the regression equation?
  8. Write (differently) the population regression model and the sample regression equation.
  9. Explain the difference between y-hat and mu-sub-y.
  10. Explain the difference between a confidence interval for mu-sub-y and a prediction interval for y. Make clear which is longer and why.
  11. Form and interpret a confidence interval for the slope coefficient.
  12. Explain what the usual hypothesis test for beta means. (whether there is or isn't a linear relationship.)
  13. Does the p-value on the MINITAB printout for the usual hypothesis test for beta represent a two-sided test or a one-sided test? How can you find the p-value for the other one?
  14. Explain what the usual hypothesis test for the population correlation coefficient means. (whether there is or isn't a linear relationship) Does the p-value on the MINITAB printout for the usual hypothesis test for the population correlation coefficient represent a two-sided test or a one-sided test? How can you find the p-value for the other one?
  15. Make a residual plot versus any other variable specified and interpret it.
  16. Make a histogram of the residuals and interpret it.
  17. Pick a regression problem from the text and use MINITAB to do it. As you're doing it, use the the program to predict y for a particular x-value. Also make the two main residual plots we discussed in this course (residuals versus the explanatory variable and a histogram of the residuals.) Now, take the output from that regression command and subcommand and explain everything that we have covered in this course.

This was last updated on December 1, 2011 . Mary Parker, mparker@austincc.edu