Course Description

Save a bundle and receive 30% off the individual course rate when you register for both STAT 101 and STAT 515!

Statistical analyses are a fundamental component of experimental design in many biomedical research fields. Particularly when working with large, messy data, proper understanding of statistics is essential to perform proper statistical analyses. This course will build on students' existing knowledge of statistics to help them expand their analysis toolkits and will cover topics including modeling, bootstrapping, simulations, imputation, and basic machine learning. Students will attend lectures to gain theoretical understanding of topics before applying concepts through practice problems and projects using the R programming language.

Bundle Courses:

STAT 101 | Introduction to Statistics

STAT 515 | Statistics for Biomedical Researchers

Learner Outcomes

When you complete these courses successfully, you will be able to:

• Use and interpret results of basic statistical tests
• Select the appropriate statistical test for a given data analytics problem
• Design experimental procedures with statistics in mind
• Use R to run basic statistical analyses
• Fit and interpret multiple regression models including interaction and non-linear terms
• Fit and interpret logistic regression models
• Evaluate model fit to perform model selection
• Perform bootstrapping and simulation analyses to quantify statistical confidence
• Fit basic machine learning models
• Identify the strengths and weaknesses of different machine learning models.

Microcredential(s)

These courses apply toward the Bioinformatics Endeavor digital badge.

Textbook Information