This comprehensive course introduces fundamental statistical concepts and their specialized applications in biological and health sciences research. Students will develop a strong foundation in descriptive and inferential statistics, probability theory, and research methodology essential for evidence-based practice. The course progresses from basic statistical principles to more advanced biostatistical methods commonly employed in clinical trials, epidemiological studies, and health outcomes research. Students will learn to select appropriate statistical tests, analyze and interpret health-related data, and critically evaluate published research.
The biostatistics component focuses on the unique challenges of analyzing biological data, including clinical measurements, survival analysis, and risk assessment. Students will gain skills in data management, analysis, and presentation of findings. This course emphasizes the ethical considerations in biostatistical analysis and the crucial role statistics plays in clinical decision-making, public health policy, and advancing healthcare research.
Learning objectives
After the completion of this course, you will be able to:
- Apply fundamental statistical concepts to summarize and describe health-related data using appropriate measures of central tendency, variability, and graphical representations.
- Formulate testable hypotheses and select appropriate statistical methods to analyze healthcare and biological data.
- Interpret probability distributions and their applications in clinical decision-making, diagnostic testing, and risk assessment.
- Perform and interpret parametric and non-parametric hypothesis tests commonly used in health sciences research.
- Analyze relationships between variables using correlation and regression techniques, with applications to clinical prediction and epidemiological research.
- Understand how to design research studies with appropriate sample size calculations and sampling methodologies to achieve valid and reliable results.
- Apply specialized biostatistical methods, including survival analysis, logistic regression, and analysis of variance to address complex health research questions.
- Utilize statistical software to manage, analyze, and visualize health data effectively.
- Critically evaluate the statistical methods, results, and conclusions in published health sciences literature.
- Communicate statistical findings to both technical and non-technical audiences through clear data visualization, proper reporting of results, and contextual interpretation relevant to healthcare practice.
Course outline
- Epidemiology and Health Research
- Statistics Part I:
- Measures of Association
- Introduction to Statistics and Contingency Tables
- Screening Tests
- Summarizing Quantitative Variables and Comparing Distributions
- Standardizing Data and the Normal Distribution
- Linear Regression and Addressing Issues with Regression Assumptions
- Randomness and Survey Sampling
- Experiments and Observational Studies
- Introduction to Probability and General Rules of Probability
- Random Variables and Probability Models
- Statistics Part II:
- Sampling Distributions for Proportions and Means
- Confidence Intervals for Proportions and Testing Hypotheses about Proportions
- More about Hypothesis Tests and Comparing two Proportions
- Inference for Means and Comparing two Means
- Inference for Paired Data and Regression
- Categorical Data Analysis
- Statistical Biases
