Application 7: Bivariate analysis

This assignment should include at least three BIVARIATE tests

Following is an outline for this week's assignment. Your submission should be written in paragraph form as it might appear in a final report. Outline form is not acceptable for your submission.

1. Purpose of the project (what you are trying to discover).

2. A very brief description of the (or each, if you are using more than one) dependent variable (including level of measurement and an appropriate measure of central tendency)

3. A very brief description of each independent variable (including level of measurement and an appropriate measure of central tendency)

4. A description of how you expect these two variables to be related to each other in a causal relationship and why (provide your reasoning for why your independent variable might cause your dependent variable, if possible, how and why the independent variable could be expected to occur before the dependent variable, etc.)

5. Name each bivariate test you used and say that you used it. Provide a sentence about why.

6. Provide the results from each test and provide the technical interpretation.

7. Provide the substantive interpretation of each test.

8. Describe caveats to your conclusions, including why you might want to include other variables.

Example writeup:

The purpose of this analysis is to determine whether or not marital status has an impact on homeownership status. Homeownership status is derived from the Spanish Fork citizen satisfaction survey, which reads "Please indicate your homeownership status" with the options "own" and "rent/lease" and "other" as options. Those who indicated that they own their home were coded as 1 and those who indicated one of the other two options were coded as 0. In our sample, 32 percent of survey respondents indicated that they own their own home. Marital status is derived from a question on the same survey, which reads "please indicate your marital status." Options included "married," "single," "divorced," and "widowed." Those who indicated that they were married were coded 1 and all others were coded 0.

We expect marital status to have a stabilizing effect on the desire and ability to own a home. Therefore, we expect a positive correlation between being married and owning a home. We expect that many Spanish Fork residents do not purchase homes until after they marry, and that marriage makes them more interested in home ownership.

It appears that marriage does, in fact, impact homeownership status. Because both variables, marrital status and homeownership status, are binary, we performed a two-group proportion test to determine whether or not there is a correlation between marital status and homeownership. The test suggests that there is a positive correlation between marital status and homeownership. On average, about 6.3 percent more married people indicated that they owned their own home than did non-married people (chi-square = ENTER VALUE, p<0.001 for a two-tailed test).

These results suggest support for our hypothesis about marriage and homeownership, but there may be other factors at play. For example, people are more likely to be married as they age, and are also more likely to be employed and to have more income. It may be that the marriage variable is really capturing these other variables in the bivariate analysis.