URBS 502—Correlation Assignment

For all of the following cases, don’t just “tell me” that there is a difference—prove that the difference you observed is, in fact, a “significant” difference (at the .05 level)by reporting and explaining an appropriate quantitative (statistical) test.

1. Using the US Census online (http://factfinder.census.gov/home/saff/main.html?_lang=en ), or any other source available to you, develop a table listing two characteristics of the cities in Minnesota (choose two that might reasonably be expected to have some relation to each other—population size and poverty, for example). Does it appear that there is a relationship between them (test this, don’t just inspect the data and reply “yes” or “no”)? Is this relationship stable over time (i.e., what happens if you run the test using different years)? Is it stable across place (i.e., what happens if you run the test for different states)? How might you explain this relationship, or its absence (i.e., what factors might account for it)? What further information would you need to test your explanation?

2. Compare the average per capita income for Minnesota’s 25 largest cities to the average for the nation and for the West North Central Region (MN, SD, ND, IA, WI). Are people in Minnesota cities better off or worse off than the nation as a whole? (Again, test this, don’t just inspect the data.) than the region? Does it make a difference if you distinguish between the Metro and out-State cities? Was the same relation apparent ten years ago? What would account for your findings?

3. Consider the hypotheses that you developed in the unit on research design. Select one or more that can be (1) measured operationally by using Census or other publicly available data series and (2) can be tested using correlation or ANOVA. Develop the data and test your hypothesis. Then test the robustness of your initial test, by repeating it using data from a different time or a different place. What light do the data throw on your hypotheses?

MSU