140.613.13
Data Analysis Workshop I
Cancelled
- Location:
- East Baltimore
- Term:
- Winter Inst. term
- Department:
- Biostatistics
- Credits:
- 2 credits
- Academic Year:
- 2022 - 2023
- Instruction Method:
- Synchronous Online
- Auditors Allowed:
- Yes, with instructor consent
- Undergrads Allowed:
- Yes
- Grading Restriction:
- Letter Grade or Pass/Fail
- Contact:
- Mary Joy Argo
- Resources:
- Prerequisite:
Experience in using a statistical analysis package; 140.611-612
- Description:
-
Intended for students with a broad understanding of biostatistical concepts used in public health sciences who seek to develop additional data analysis skills.
Emphasizes concepts and illustration of concepts applying a variety of analytic techniques to public health datasets in a computer laboratory using Stata statistical software. Learns basic methods of data organization/management and simple methods for data exploration, data editing, and graphical and tabular displays. Includes additional topics: comparison of means and proportions, simple linear regression and correlation.
- Learning Objectives:
-
Upon successfully completing this course, students will be able to:
- Create, save and edit STATA datasets, log files and do files
- Use STATA to perform exploratory data analysis for continuous and dichotomous variables
- Use STATA do files to create reproducible analyses
- Explain the distinction between and appropriate uses of the binomial, Poisson and normal probability models
- Use STATA to perform paired and unpaired t-tests for differences in group means
- Describe the appropriate use of paired and unpaired t-tests and the interpretation of the resulting STATA output
- Use STATA to perform a chi-squared test and compute confidence intervals for differences in group proportions, relative risks and odds ratios
- Describe the appropriate use of chi-squared tests and the interpretation of the resulting STATA output
- Use STATA to visualize relationships between two continuous measures
- Use STATA to fit simple linear regression models, and interpret relevant estimates from the results
- Methods of Assessment:
This course is evaluated as follows:
- 80% Lab Assignments
- 20% Final Exam
- Enrollment Restriction:
Enrollment limited to 20 students enrolled in an SPH degree program
- Instructor Consent:
Consent required for some students
- Consent Note:
Instructor consent required for registrants not enrolled in a degree program currently with enrollment in the Winter Institute.
- For consent, contact:
- Special Comments:
Instructor consent required for registrants not concurrently enrolled in a JHSPH part-time degree program