- Four scatter plots are shown. Match the scatter plot with the value of the correlation coefficient.
- Chi-squared goodness of fit test
- The observed frequencies and claimed proportions are given, find the expected frequencies.
- Give the number of degrees of freedom.
- Know the null and alternative hypotheses.
- The test statistic and p-value are given; determine if the test statistic lies in the critical region.
- Give the decision and conclusion.

- Correlation and regression - the regression equation is given.
- Complete the table of coefficients
- Give a conclusion about the y-intercept or slope
- Complete the ANOVA table
- Find the sample size based on the ANOVA table
- Find the value of the coefficient of determination, r
^{2} - Find the standard error of the estimate, s
_{e}

- Correlation and regression - the summary statistics, correlation coefficient and p-value are given
- Give a conclusion
- Write the coordinates of the centroid
- Find the slope of the regression equation
- Write the equation of the regression line
- Estimate a value of the response variable for the specified value of the predictor variable
- Complete the ANOVA table. This table is completely blank to begin with.

- Multiple Regression
- Complete the table of coefficients
- Rank the predictor variables in order from best predictor to worst predictor
- Write the null and alternative hypothesis for one of the rows in the coefficient table.
- Give a conclusion based on the table of coefficient p-values.
- Decide which one variable you would keep or eliminate from the model if you had to.
- Complete the ANOVA table.
- Determine the sample size based on the ANOVA table.
- Write the null and alternative hypothesis for the ANOVA table.
- Find the value of R
^{2}and adjusted-R^{2}from the ANOVA table.

- Rank the multiple regression models from best to worst based on the appropriate
values. The R
^{2}, adjusted-R^{2}, and number of predictor variables is given. - Identify the type of linear correlation based on the value of r and the p-value.
- Test for independence
/ contingency table
- Write the null hypothesis
- Find the expected frequency for one of the cells in the table
- Determine the degrees of freedom
- The critical value and test statistic are given; give the decision and conclusion.

- One way analysis of variance
- Write the null and alternative hypothesis.
- Complete the ANOVA table
- Give a conclusion
- Find the pooled variance
- Find the variance of the response variable

- Two-way analysis of variance
- Complete the two-way ANOVA table
- Know the three null and alternative hypotheses being tested with the table
- Give a conclusion based on results from the table.

- You will definitely want a calculator.
- You will not need Minitab. The computers will be off during the exam.
- You were given handouts similar to questions 4, 5, and 6. Problem 4 is similar to the "Sample Regression Worksheet" and questions 5 and 6 are similar to the "Multiple Regression Worksheet".
- You may create a sheet of notes to use for this test. Details about what can be on the notesheet follow.

You may use a sheet of notes on this exam. Here are the guidelines for the notesheet.

- You may use one side of an 8.5" x 11" piece of paper. You may use a smaller sized paper if you desire. You may not write on the back of the paper.
- The notesheet must be handwritten and an original (not duplicate) document.
- You may not photocopy, scan, fax, or otherwise duplicate someone else's notesheet. it is okay if you want to get together, study, and create a notesheet, but each person's notesheet must be an original, handwritten document.
- If I can not tell that your notesheet is an original document, I will not allow it. Consider using pencil or colored pens for portions of the notesheet.
- The notesheet must have your name on it. I will collect the notesheets with the exams. You will get them back with the graded test.
- The notesheet may not have examples on it.
- The notesheet may have notes, explanations, ANOVA tables with an explanation of how to find specific entries, but it may not contain examples with specific numeric values. For example, "the total df is one less than the sample size" or "df(total) = n-1" is okay, but "if n = 20, then total df = 20 - 1 = 19" is not. You may have "SS / df = MS," but not "SS(Regression) = 351, df(Regression) = 3, MS(Regession) = 351 / 3 = 117"

# | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | Total |
---|---|---|---|---|---|---|---|---|---|---|---|

Pts | 4 | 9 | 15 | 9 | 20 | 3 | 3 | 11 | 10 | 16 | 100 |