Do men and women think differently about their body weight? To address this question, you will be using data from the Behavioral Risk Factor Surveillance System (BRFSS). The Behavioral Risk Factor Surveillance System (BRFSS) is an annual telephone survey of 350,000 people in the United States collected by the Centers for Disease Control and Prevention (CDC). As its name implies, the BRFSS is designed to identify risk factors in the adult population and report emerging health trends. For example, respondents are asked about diet and weekly physical activity, HIV/AIDS status, possible tobacco use, and level of healthcare coverage.
The cdc dataset contains data from a random sample of 20,000 respondents to the BRFSS survey conducted in 2000, on the following nine variables:
– genhlth: general health status, with categories excellent, very good, good, fair, and poor
– exerany: recorded as 1 if the respondent exercised in the past month and 0 otherwise
– hlthplan: recorded as 1 if the respondent has some form of health coverage and 0 otherwise
– smoke100: recorded as 1 if the respondent has smoked at least 100 cigarettes in their entire life and 0 otherwise
– height: height in inches
– weight: weight in pounds
– wtdesire: desired weight in pounds
– age: age in years
– gender: gender, recorded as m for male and f for female
To load the cdc dataset, run the following command: source("http://www. openintro. org/stat/data/cdc. R")
This problem is structured in a way that reflects how statistics typically arises in a realistic sce- nario; start with a substantive question and associated data, then use the tools of statistics to ex- amine what insights the data may provide. As happens in practice, the question does not specify exactly what to do with the data. There will be multiple perfectly reasonable ways to approach the problem and present conclusions. Focus on crafting a coherent solution that is clear, well-written, and supported by the data.
1 This will be your first opportunity to integrate thinking about how to approach a problem, con- ducting an analysis, and formally reporting your interpretation of the results.
The submission for this problem set will follow the general format of a scientific paper: a written report organized into sections and an appendix of figures and relevant R output. Limit your written report to a maximum of 3 pages; the appendix may be as long as necessary.
– Introduction (15 pts). Introduce the question context and any scientific hypotheses. Connect the research question with the data analysis approach; how does the specific approach im- plemented address the research question?
– Methods (25 pts). Outline the statistical analysis methods along with details pertaining to analysis set-up.
– Rather than analyze the complete dataset, use a subset of the data. Draw a random sample of size 300 from cdc, using the last four digits of your HUID in set. seed( ).
– Specify which variables are used in the analysis, with a brief explanation of your choices (including any variables that you might have created).
– Specify the statistical techniques used.
– /,statethe (statistical) null and alternative hypotheses, significance level α, and/or the level of the confidence intervals.
– Results (40 pts). Report the descriptive and analytic results. All supporting figures and output should be in the appendix.
– Descriptive results. Describe the participants in the study sample, referencing numer- ical and graphical summaries from the appendix as needed. The description should not simply be a list of observations; provide context for the reader and highlight which aspects of the summaries are most interesting or informative.
– Analyticresults.,anyconfidenceinter - vals calculated, and/or any linear models fitted. It is appropriate in this section to briefly interpret the results quantitatively; e. g., to identify significant p-values and di- rection of associations. Assumptions checking for linear models should also be in this section.
– Discussion (20 pts). Present your conclusions, interpreting the results of the analysis and their implications for the research question.
– hypothesis test and their interpretation in a larger scientific context. Connect results back to any initial scientific hypotheses.
– Describe limitations of the study and possible further directions.
– Assess the generalizability of the results.
A maximum of 6 total bonus points, 2 per category, are available for a) especially thorough,
thoughtful analysis, b) particularly clear, logical writing, and c) presentation-quality figures.
This problem set does not require material from Unit 7 (Multiple Regression), but you are wel- come to use techniques covered in Unit 7 if you like.