1. For what kind of variable is Pearson's r useful for measuring the relationships? How would you interpret a Pearson's r of .85 between the number of years of work and the amount of salary? (Hint: think about the direction and the strength of the relationship between variables) (20 pts)

2. Why is linearity important in regression analysis?

3. You are a program manager for a welfare agency and want to know if a relationship exists between the length of time that people receive welfare (in months) and their education (total years). Both variables are continuous. The Table below is the hypothetical output from your simple regression model. Interpret the results.

Table 1. Simple Regression Output R R-square SEE 0.002 0.000 1.125 Dependent variable: Unemployment duration Coefficients Unstandardized coefficients Model b SE T Sig Constant 0.6710 0.034 19.63 0.000 Education 0.0015 0.033 0.045 0.965 Note: SEE= standard error of the estimate; SE = standard error; Sig.= significanceTable: Departmental Performances and Resource Inputs Department ID Performance score Expenditures per employee ($) 90 80440 2 80 118340 95 65766 4 100 86368 100 70810 100 142857 71 65393 co 91 85469 100 87940 10 82 74280 11 86 97577 12 76 73846 13 75 64833