Introductory Statistics

Course Level: Graduate

Prerequisites: None

Description: When analyzing data, which statistical test is appropriate? Should you use a parametric test? What is the difference between standard deviation and standard error? What are probability distributions, and how are they useful? What is the best way to fit a curve? Are the data normal? Run by students and postdoctoral associates at Rockefeller, this course introduces elementary and intermediate topics in statistics. Each session includes a lecture followed by a breakout session during which students work together on biologically relevant problem sets. Topics include central tendency and dispersion, basic probability, probability distributions, inferential statistics, hypothesis testing, and regression. We will also provide background on advanced topics including multivariate statistics and advanced biostatistics. Sessions take place during the evenings on a weekly or biweekly basis. No background knowledge in statistics is required. There are two components to this course. The “main course” covers introductory topics in statistics, starting with central tendency (What is a mean?) and ending with nonlinear regression. The second component is a module on intermediate and advanced statistics, covering topics like the design of experiments and analysis of RNAseq data. The intermediate and advanced module requires no knowledge in calculus or linear algebra and its focus will be on the concepts and implementation of basic principles. Both components of the course are designed to be accessible to those without any prior knowledge in statistics, calculus, linear algebra, or programming.

Offering: This was a seminar-based course was offered to graduate students at The Rockefeller University. It is no longer being offered.

Resources: For more information on the seminars, please refer to the course website. Contact me directly for any questions or concerns.