# 140.651.41Methods in Biostatistics I

Location
Internet
Term
1st Term
Department
Biostatistics
Credit(s)
4
2023 - 2024
Instruction Method
Synchronous Online with Some Asynchronous Online
Class Time(s)
Tu, Th, 10:30 - 11:50am
Lab Times
Tuesday, 3:30 - 4:20pm (01)
Wednesday, 3:30 - 4:20pm (02)
Auditors Allowed
Yes, with instructor consent
Yes
Course Instructor(s)
Contact Name
Frequency Schedule
Every Year
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. Includes topics 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. 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. Discuss the creation and interpretation of P values
7. Describe estimation, testing and interpretation for single group summaries such as means, medians, variances, correlations and rates
8. Describe estimation, testing and interpretation for two group comparisons such as odds ratios, relative risks and risk differences
9. Describe the basic concepts of ANOVA
10. Select the appropriate statistical method to evaluate the results of a public health program, policy or intervention
Methods of Assessment
This course is evaluated as follows:
• 40% Homework
• 20% Midterm
• 40% Final Exam