Course Description

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

Bundle Courses:

STAT 101 | Introduction to Statistics

STAT 515 | Statistics for Biomedical Researchers

STAT 101: In this course, students will be introduced to basic statistical theory, real-world statistics applications, and statistical test implementations in R. Students will learn the theory behind common statistical tests and how to perform them before moving on to perform statistical analyses using a dataset of their choice. Through this process, students will learn how to select the correct test for a dataset, how to design experiments amenable to statistical analyses, and how to avoid common statistical analysis pitfalls.

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.

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.

What FAES Learners are Saying

“instructor was very willing to help and kind when I needed help, made me feel like I could ask any question I needed” - FAES Learner (STAT 101)

"lectures were clear, understandable, and reflected the assigned material." - FAES Learner (STAT 515)

Textbook Information