METHODS IN BIOSTATISTICS II 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
- Describe the distinctions between the fundamental paradigms underlying statistical methodology
- List the basics of maximum likelihood
- List 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
Presents 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.
Biostatistics master's students and quantitatively-oriented students from other depts
Methods of Assessment
Grading Policy: Student evaluation based on several problem sets and one exam each term.
Grading Restrictions: Letter grade
Academic Ethics Code
The code, discussed in the Policy and Procedure Memorandum for Students, March 31, 2002, will be adhered to in this class:
Students enrolled in the Bloomberg School of Public Health of The Johns Hopkins University assume an obligation to conduct themselves in a manner appropriate to the University's mission as an institution of higher education. A student is obligated to refrain from acts which he or she knows, or under the circumstances has reason to know, impair the academic integrity of the University. Violations of academic integrity include, but are not limited to: cheating; plagiarism; knowingly furnishing false information to any agent of the University for inclusion in the academic record; violation of the rights and welfare of animal or human subjects in research; and misconduct as a member of either School or University committees or recognized groups or organizations.
Disability Support Services
If you are a student with a documented disability who requires an academic accommodation, please contact Betty H. Addison in the Office of Student Life Services: firstname.lastname@example.org, 410-955-3034, or 2017 E. Monument Street.