- Know the assumptions / properties of Pearson's Linear Correlation Coefficient. (7 points)
- Know the assumptions / properties of the contingency tables. (6 points)
- Know the assumptions / properties of multinomial experiements. (6 points)
- Know the guidelines for using the regression equation. (5 points)
- Look at a scatterplot and identify the linear correlation as strong negative, moderate negative, none, moderate positive, or strong positive. (2 points)
- Know what happens to the linear correlation coefficient when the data is manipulated. Two parts. (4 points)
- Know what happens to the test statistic of a multinomial experiment when the data is manipulated. Two parts (4 points)
- Find the expected frequencies for a contingency table. (4 points).
- Look at a multiple regression output. (6 points)
- Pick the three most significant independent variables (The ones with the smallest p-values or largest t-values [called t statistics on the output]).
- Pick the three least significant independent variables (The ones with the largest p-values or smallest t-values [called t statistics on the output]).
- Work a contingency table problem using the conting program on the calculator. (9 points)
- Find the test statistic (using the calculator).
- The critical value (use the Chi-square table).
- Fill in the blanks to finish the conclusion.
- Work a chi-square goodness of fit problem using your TI calculator. (12 points)
- Find the test statistic (using the calculator)
- Look up the critical value (in the Chi-square table)
- Write the decision.
- Fill in the blanks to complete the conclusion.
- Work a linear regression problem using your TI calculator. (9 points)
- Find the linear correlation coefficient
- Test to see if there is significant linear correlation (use Table A6 to find the critical value)
- Write the regression equation (Remember, if you fail to reject in step 2, then the regression equation is y-hat equals y-bar).
- A linear regression problem was performed on a computer and the output is given. The output contains the constant (from the regression equation), the standard error of the y estimate (ignore), the value of r-squared, the number of observations, the degrees of freedom, the x-coefficient (from the regression equation) and the standard error of the coefficient (ignore). Given this information, find ... (25 points)
- The coefficient of determination (2 points)
- The value of the linear correlation coefficient (2 points)
- The sample size (2 points)
- Test to see if there is significant linear correlation using Table A6. (9 points)
- Write the critical value
- Write the test statistic
- Identify the type of linear correlation as significant negative, none, or significant negative.
- Write the equation of the regression line. (3 points)
- Estimate the dependent variable for a given value of the independent variable. (3 points)
- Given the total variation, find ... (4 points)
- The variation explained by the regression equation
- The variation unexplained by the regression equation.

- Problems 1 - 10 must be worked individually.
- Problems 11 - 13 may be worked in groups of up to size 3.