Scientific Computing References, Guides, and Notes
An in-progress website storing tricks, tips, and reminders for various aspects of scientific computing (at least as far as I practice it...).
Right now this site is fairly minimal (though check out the more complete guide to conda environments) but will continue to grow over time.
Occupancy Modeling WorkshopWebsite and materials associated with a 2-day workshop on occupancy modeling I co-led at the 2019 CECAM conference in Mérida, Yucatán. Materials include: lecture slides, R code for single- and multi-season models, and other resources.
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Teaching Resources for Inference and Statistics
"Everything is a Model"Blog post to Rapid Ecology co-authored with Elizabeth Pansing. We remind readers that all inference is based on models - yes even so-called "tests".
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Surprising Risk of Type I ErrorsBlog post walking through some of the math of Type I error rates. Using simple probability rules, I show how making a Type I error might be more likely that most people think.
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The Normal DistributionLecture slides for teaching the Normal (Gaussian) distribution and Central Limit Theorem in introductory biostats with R code.
Markdown to generate/modify these slides here! |
Software
pinpointreadRR package to download and compile data from Lotek PinPoint archival GPS tags.
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checkyourselfR package and vignettes containing code for stylized examples of pre-data collection simulation modeling.
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betaGraphR
COMING SOON!
R package containing tools for visualizing how to interpret the coefficients of linear models. Useful as a teaching tool. |
You can also install any of these directly from an R session using the package devtools. Simply run:
> devtools::install_github("syanco/[packagename]")
> devtools::install_github("syanco/[packagename]")