 # 140.651.01 Methods in Biostatistics I

Department:
Biostatistics
Term:
1st term
Credits:
4 credits
2019 - 2020
Location:
East Baltimore
Class Times:
• Tu Th,  10:30 - 11:50am
Lab Times:
• Tuesday,  1:30 - 2:20pm (01)
• Wednesday,  2:30 - 3:20pm (02)
Auditors Allowed:
Yes, with instructor consent
Contact:
Ciprian Crainiceanu
Course Instructor :
Resources:
Prerequisite:

Working knowledge of calculus and linear algebra

Description:

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 interval for means, proportions, and counts; maximum likelihood estimation; sample size determinations; elementary non-parametric methods; graphical displays; and data transformations. Also introduces R and concepts are presented both from a theoretical, practical and computational perspective.

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. List the distinctions between the fundamental paradigms underlying statistical methodology
4. Identify the basics of maximum likelihood
5. Identify 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:

Student evaluation based on several problem sets and one exam each term.

Instructor Consent:

No consent required