Join Monika Wahi for an in-depth discussion in this video What you should know, part of Descriptive Healthcare Analytics in R.
- [Instructor] Here is what you should know before taking this course. You should have already had at least one course in basic statistics. Also, you should have a background in health, healthcare, or public health. However, you don't need a heavy background in statistical programming. This is not so much a course on R per say, but a course that shows you how to develop a descriptive analysis using health data. We use R to make our deliverable, a completed, descriptive analysis on a health topic.
This detailed, practical course is designed to help those in the field of public health, medicine, and data science to edit, analyze, and interpret data. Learn how to code new variables, use the forward-stepwise modeling process, and document your decisions. Find out how to visualize results by generating charts and graphics, and how to add tables and figures to your documentation. This course helps equip you to independently design, develop, and execute a full BRFSS analysis, and even publish your results in scientific publications or journals.
- Reviewing survey data and documentation
- Conducting a BRFSS analysis
- Understanding naming conventions
- Editing variables
- Reviewing distributions
- Generating an analytic dataset
- Developing descriptive statistics to answer prespecified hypotheses
- Preparing publication-worthy tables and plots
Skill Level Advanced
1. What Is the BRFSS?
2. Designing Your Metadata
3. Reading in Data and Applying Exclusions
4. Preparing for Descriptive Analysis
5. Conducting Descriptive Analysis
Making a frequency macro4m 8s
6. Descriptive Analysis: Weights and Tests
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