Exercise 6-Correlation & Regression

Points: 10 points

Correlation and regression are designed to measure the direction and strength of relationships between two variables measured at the interval level. Use the syntax provided to answer the following questions

Part 1—California results

1. How would you concisely describe the relationship of the variable RawImm4 with its best demographic (age, education and income) predictor?
2. What percent of the variation in RawImm4 is due to this variable?
3. What percent of the variation in the measure RawImm4 is explained by variation in Democrat5?
4. How much more of the variation in RawImm4 is explained by Democrat7 than is explained by Democrat5?
5. What is the correlation between education and political interest?
6. What is the correlation between education and income?
7. What percent of the variation in Income is explained by education.
8. Write out the equation for the regression of RawImm4 on Democrat5?
9. How significant is the slope in this equation?
10. How well does this equation fit the data?

Part 2—Texas results

1. How would you succinctly describe the relationship of each of the dependent variables ImmIncl and ImmExcl with their best demographic (age, education and income) predictor?
2. What percent of the variation in each of the measures ImmIncl and ImmExcl is explained by variation in Democrat5?
3. What is the correlation between education and political interest?
4. What is the correlation between education and income?
5. Write out the equation for the regression of ImmIncl on Democrat5.
6. Write out the equation for the regression of ImmExcl on Democrat5.
7. How significant is the slope in each equation?
8. How well does each equation fit the data?
9. How much more or less effective is Democrat5 in explaining Inclusive attitudes toward immigration in Texas than it is in California?
10. Why might one reasonably say that education is more effective in building social capital in California than it is in Texas?