METHODS IN BIOSTATISTICS I Syllabus
Course Learning Objectives
Upon successfully completing this course, students will be able to:
- Discuss core applied statistical concepts and methods
- Discuss the display and communication of statistical data.
- List the distinctions between the fundamental paradigms underlying statistical methodology
- Identify the basics of maximum likelihood
- Identify the basics of frequentist methods: hypothesis testing, confidence intervals
- Identify basic Bayesian techniques, interpretation and prior specification
- Discuss the creation and interpretation of P values
- Describe estimation, testing and interpretation for single group summaries such as means, medians, variances, correlations and rates
- Describe estimation, testing and interpretation for two group comparisons such as odds ratios, relative risks and risk differences
- Describe the basic concepts of ANOVA
Course DescriptionPresents fundamental concepts in applied probability, exploratory data analysis, and statistical inference, focusing on probability and analysis of one and two samples. Topics include discrete and continuous probability models; expectation and variance; central limit theorem; inference, including hypothesis testing and confidence for means, proportions, and counts; maximum likelihood estimation; sample size determinations; elementary non-parametric methods; graphical displays; and data transformations.
Intended AudienceBiostatistics master's students, quantitatively-oriented students from other departments
Methods of AssessmentStudent evaluation based on several problem sets and one exam each term.
PrerequisitesWorking knowledge of calculus and linear algebra
Please see the course Session for a full list of dates and items for this course.
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