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Quantitative Methods

Quantitative methods in biomedical sciences

Overview

This is the home page for a 16 week class taught by Ken Campbell at the University of Kentucky.

“Quantitative methods for biomedical research” is a 2 credit graduate-level class designed for PhD students and others who wish to develop skills relating to data analysis and interpretation. The course will include sections on data handling, plotting, statistics, and image analysis. Students will be shown how to automate routine analysis tasks and encouraged to develop quantitative skills that will help them to solve future problems by themselves. The course will use MATLAB software but the techniques and content are relevant to all types of scientific programming. Students will also be introduced to GitHub and shown how to organize code and data to improve rigor and reproducibility.

At the end of this course, a student should be able to use MATLAB or similar software to:

  • Import experimental data from text files, spread-sheets, images, and movies
  • Plot data in appropriate formats (including bar charts, scatter plots, surface plots)
  • Fit models to data (including straight lines, polynomials, and exponentials)
  • Perform and interpret hypothesis tests (including t-tests and ANOVA)
  • Segment images to detect features
  • Extract statistics about image features (including areas, colors, and eccentricities)
  • Analyze gels and immunoblots

Accessing content

All of the material for this course can be accessed from this site or the course repository on GitHub.

Videos of the lectures are hosted on the University of Kentucky’s Yuja system and are linked from this site.

University of Kentucky students

Students who are taking the class at the University of Kentucky have access to the syllabus, weekly assignments, and information relating to grading through Canvas.