Statistical Inference and Its Role in Public Health Research
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Description
Assess understanding of statistical inference principles integral to public health research, emphasizing confidence intervals and p-values for informed decision-making.
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Exam Details
Duration: 50 minutes
Prerequisites: Introduction To Biostatistics, Research Methodology, Probability Theory
Key Topics
- Statistical Inference
- Confidence Intervals
- P-Values
- Hypothesis Testing
- Type I and II Errors
Learning Outcomes
- Explain Statistical Inference Principles
- Assess Confidence Intervals
- Discuss P-Values
- Analyze Errors in Hypothesis Testing
Full Description
This examination focuses on statistical inference as a cornerstone of public health research methodologies. Key concepts include confidence intervals, p-values, and error types.
Statistical inference enables researchers to draw conclusions about populations from sample data, fundamentally influencing public health policy, practice, and research outcomes.
Students must demonstrate their understanding of statistical inference, including its assumptions and limitations, while articulating its relevance in real-world public health situations.
Preparation should include a review of case studies illustrating the application of statistical inference in public health decisions.
Sample Questions
- What is the significance of p-values in hypothesis testing?
- How do confidence intervals assist in making data-driven public health decisions?
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