5. What kind of factorial design -- exclusively between-subjects factors, exclusively within- subjects factors, or mixed-design -- do you have if subjects are divided into the categories male and female and then assigned to study for either 20 minutes or 60 minutes? The researcher measured how well students performed on a quiz. [*] 6. Eight rats were presented with 10 light-tone pairings. For eight other rats, the light was paired with a ball-bearing 10 times. For both groups, the researchers analyzed how much time the rats spent with their noses in the feeder when the light was on; 10 scores from each rat were used in the statistical analysis. What kind ofANOVA should be used to analyze the results of this experiment? [*] Unit 5 (Chpt 5) 1. When x predicts y, x is known as the or variable, and y is known as the variable. 2. (a) Yes or no, is it appropriate to fit a straight line to bivariate data that appear to have a linear relationship? (b) Yes or no, is it appropriate to fit a straight line to bivariate data that appear to have no relationship? (0) Yes or no, is it appropriate to fit a straight line to bivariate data that appear to have a curvilinear relationship? 3. (a) In the context of linear regression, what are residuals? (b) Ideally, researchers try to fit a line to bivariate data so that the residuals are as as possible. (c) Which residual is larger: e1 = -4 or e2 = 1? (d) To calculate a residual, researchers measure the difference between an observed y value and 4. (a) In terms of a linear relationship, what does correlation measure? (b) What range of values can a correlation coefficient take on? (0) Which correlation coefficient depicts a stronger linear relationship: r1 = 0.2 or r2 = -0.6? (d) If there is no linear relationship between two variables, the r value will be near 5. With reference to residuals, explain what a best-fitting straight line is. 6. (a) What is another term for the estimate, b0? (b) Explain what it means for b1 = 0.5. 7. A researcher ts a regression line to first-year students' SAT scores (predictor variable) and these same students' year-ending GPAs (response variable). The R value was .964, b1 = 0.002, t = 13.655, and p