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PPOL 506 Policy Report Proposal

For this proposal, you will develop a research question that you can analyze using multivariate regression.

For this project you may use the dataset ACS2016 to write up a short proposal that answers the following questions. You may submit your answers in essay form or in response to each question individually.

1. State your research question. What type of research question is this? Why is it interesting to policymakers today?

2. Describe the dataset you will use to answer your question. What sampling strategy was used for data collection? What population do the data represent? Why is the dataset appropriate for answering your research question?

3. Specify the unit of analysis and number of observations in the dataset. Will you use the entire dataset or a subset of observations for your analysis?

4. Choose 8 continuous variables you could use in your multivariate analysis. Clean these variables. Create a descriptive statistics table (with the cleaned data) that includes the mean, standard deviation, minimum, maximum, and number of observations for each variable. Write a short summary paragraph of your descriptive statistics table that argues why these variables are appropriate choices for your analysis. Note: You may construct new variables out of existing variables in the dataset.

5. Choose 4 categorical or binary variables that you could use in your analysis. Create a codebook for these variables. Write a short summary paragraph of these variables that argues why these variables are appropriate choices for your analysis. You may submit the codebook as a separate document or in a table in your write up. Note: You may construct new variables out of existing variables in the dataset.

6. Write a sample multivariate regression model. Specify your outcome (Y) variable and your explanatory (X) variables. Clearly state your hypotheses for the direction of the effect of each explanatory variable. Note: You do not need to run this model in R; this is just to get you thinking about the model.

Grading Rubric