140.652.01
Methods in Biostatistics II

Prerequisite:

140.651

Description:

Presents fundamental concepts in applied probability, exploratory data analysis, and statistical inference, focusing on probability and analysis of one and two samples. Includes 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.

Learning Objectives:

Upon successfully completing this course, students will be able to:

1. Discuss core applied statistical concepts and methods
2. Discuss the display and communication of statistical data
3. Describe the distinctions between the fundamental paradigms underlying statistical methodology
4. List the basics of maximum likelihood
5. List the basics of frequentist methods: hypothesis testing, confidence intervals
6. Identify basic Bayesian techniques, interpretation and prior specification
7. Discuss the creation and interpretation of P values
8. Describe estimation, testing and interpretation for single group summaries such as means, medians, variances, correlations and rates
9. Describe estimation, testing and interpretation for two group comparisons such as odds ratios, relative risks and risk differences
10. Describe the basic concepts of ANOVA

Methods of Assessment:

This course is evaluated as follows:

• 20% Homework
• 40% Midterm Paper
• 40% Final Exam

Instructor Consent:

No consent required

Special Comments:

Please note: This is the onsite section of a course that is also offered virtually. Students will need to commit to the modality for which they register. Students will choose only one of the two lab times.