en 1: predicts y, x is known as the or variable, and y is known as the variable. Yes or no, is it appropriate to t a straight line to bivariate data that appear to have a linear nship'? (b) Yes or no, is it appropriate to t a straight line to bivariate data that appear to no relationship? (c) Yes or no, is it appropriate to t a straight line to bivariate data that to have a curvilinear relationship? In the context of linear regression, what are residuals? (b) Ideally, researchers try to t a J bivariate data so that the residuals are as as possible. (c) Which residual is e] = -4 or e; = l? (d) To calculate a residual, researchers measure the difference between served y value and In terms of a linear relationship, what does correlation measure? (b) What range of values correlation coefficient take on? (c) Which correlation coefficient depicts a stronger linear nship: r1 : 0.2 or r2 : -0.6? (d) If there is no linear relationship between two variables, the a will be near 11 reference to residuals, explain what a best- tting straight line is. What is another term for the estimate, [30? (b) Explain what it means for 171: 0.5. 'esearcher ts a regression line to rst- year students' SAT scores (predictor variable) and same students' year ending GPAs (response variable). The R value was .964, 121: 0.002, r -55, and p