There are no word limits and the answers should be in HTML file.

• Your project will consist of 3 parts:

1. Data: (3 points) Describe how the observations in the sample are collected, and the implications of this data collection method on the scope of inference (generalizability / causality). Note that youwill need to look into documentation on the BRFSS to answer this question. See http://www.cdc.gov/brfss/ as well as the "More information on the data" section below.
2. Research questions: (11 points) Come up with at least three research questions that you want to answer using these data. You should phrase your research questions in a way that matches up with the scope of inference your dataset allows for. Make sure that at least two of these questions involve at least three variables. You are welcomed to create new variables based on existing ones. With each question include a brief discussion as to why this question is of interest to you and/or your audience.
3. EDA: (30 points) Perform exploratory data analysis (EDA) that addresses each of the three research questions you outlined above. Your EDA should contain numerical summaries and visualizations. Each R output and plot should be accompanied by a brief interpretation.

• In addition to these parts, there are also 6 points allocated to overall organization and readability of your project. Total points add up to 50 points. See the assessment rubric for more details on how your peers will evaluate your work.

• Your submission should be a single HTML file that results from knitting your Rmd file. This document should contain all your code, R output and plots, and your narrative. You must use the Rmd template provided in the project instructions.

• Review criteria

1. Do you understand the research question?
2. Is it clear how data can be used to answer this research question as its phrased?
3. Scope of inference - generalizability: Is the data collection explained clearly? Did the writer correctly identify the population of interest? Did the writer correctly decide whether the findings from this analysis can be generalized to that population, or, if not, a subsection of that population? Is their explanation satisfactory to make this decision? Are potential sources of bias discussed, and if so, is the discussion satisfactory?
4. Scope of inference - causality: Did the writer identify correctly whether these data can be used to establish causal links between the variables of interest. Is the explanation satisfactory?
5. Are the research questions well defined and is it clear why they are of interest to the author / audience? Are appropriate numbers of variables used in each research question?
6. Are appropriate summary statistics calculated, and are they explained/interpreted in context of the data and the research question?
7. Are appropriate visualizations included, and are they explained/interpreted in context of the data and the research question?
8. Did the writer address what the findings from the exploratory analysis suggest about the research question?