Jul 02, 2024
OHIO University Undergraduate Catalog 2023-2024
OHIO University Undergraduate Catalog 2023-2024
[Archived Catalog]
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IHS 4303 - Secondary data analysis in global health and development
This applied research course utilizes secondary analysis of existing data to analyze research questions in global health and development. Students develop a research plan, obtain IRB approval and analyze publicly available and faculty generated quantitative and qualitative data on critical health issues among various cultures. By the end of the course, students complete a research project utilizing an existing global health data source. Students are strongly encouraged to have completed a basic research methods course prior to enrolling in this course.
Requisites: IHS 2210
Credit Hours: 4
Repeat/Retake Information: May be retaken two times excluding withdrawals, but only last course taken counts.
Lecture/Lab Hours: 3.0 lecture, 2.0 laboratory
Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I
Learning Outcomes:
- Students will be able to appraise the suitability of different study designs for evaluating global health questions
- Students will be able to describe ethical considerations for research in a variety of cultural settings
- Students will be able to compare existing data sources available to answer a global health and development questions , such as WHO, DHS, etc
- Students will be able to describe analytical methods for testing hypotheses and addressing research questions
- Students will be able to develop an IRB proposal for secondary data analysis
- Students will be able to conduct a literature search and write a literature review
- Students will be able to demonstrate use of bibliographic management system
- Students will be able to develop and explain a research question utilizing an existing data source
- Students will be able to present research results
- Students will be able to understand secondary data including data structure sampling design and weighting
- Students will be able to utilize statistical software (SAS) for data management and analysis of secondary data
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