Every summer, the Osborne-Nishimura lab does a summer workshop series, and it has grown every year! This summer we're focusing on different topics related to regression, linear or otherwise.
Linear regression is a popular method for finding the relationship between quantitative measurements. There are many relevant aspects that go beyond "fitting Y to X", taking R-squared, and finding a p-value. This workshop will highlight some aspects of regression, (not just the linear variety), that we may not commonly use in our research, or never learned in the first place, or may be using incorrectly.
We're looking for presenters!
Enterprising folks are encouraged to build their presentation into an RMarkdown document so that the audience can follow along. However, straight PowerPoint presentations are also welcome.
In the past, we have had people find a tutorial of some kind and present it to the workshop. Extra kudos if you can add your own data to it to test it out! Email me at David.King@colostate.edu if you are interested in presenting.
- Basics and Assumptions A very important review and walk-through of what linear regression is, and how to check the assumptions on your data.
- Choosing the type of regression Kudos if you can find biological examples for these different types! Hint: try the resources below.
- Regression connection to ANOVA
- Focus on a non-linear type of regression?
- Evaluation of outliers?
- Different (better?) libraries in R
Modern Statistics for Modern Biology
Ben will demonstrate, by simulation, the consequences of controlling for different experimental variables in an experimental model of bacterial colonization in the C. elegans intestine.