Statistical Inference Techniques in Public Health Research
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Description
This exam assesses knowledge of statistical inference in public health research. Emphasis is placed on hypothesis testing, confidence intervals, and their implications in health outcomes.
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Exam Details
Duration: 45 minutes
Prerequisites: Fundamentals of Biostatistics, Epidemiology Principles
Key Topics
- Statistical Inference
- Hypothesis Testing
- Confidence Intervals
- P-Values
Learning Outcomes
- Articulate Statistical Inference Concepts
- Explain Hypothesis Testing
- Interpret Confidence Intervals
- Discuss P-Value Implications
Full Description
This exam focuses on statistical inference techniques used in public health research, including hypothesis testing, confidence intervals, and p-values. Candidates are expected to demonstrate their understanding of these concepts in the context of health outcomes.
The significance of these techniques lies in their ability to provide insights into population health, help inform policy decisions, and assess the effectiveness of public health interventions. Mastery of these principles is essential for a career in biostatistics and public health.
The exam will evaluate the student's verbal comprehension of statistical inference, including the ability to articulate the implications of statistical results and their relevance to public health practice.
In addition to theoretical understanding, candidates may be asked to provide real-world examples of how statistical inference has influenced public health outcomes.
Sample Questions
- Can you explain the significance of a p-value in public health research?
- How would you interpret a 95% confidence interval in a health study?
Field: Medical and Health Sciences
Subfield: Biostatistics
Specialization: Public Health Biostatistics
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