Here are some resources that I have found useful in my work.
Please let me know if you don't have access to any that are paywalled.
Please let me know if you don't have access to any that are paywalled.
R
QCBS R Workshop series - This is a series of workshops run at Quebec universities for (mostly) early career researchers in ecology and evolutionary biology, but the site includes slides and scripts that can function as self-guided tutorials. While the examples are biology- and ecology- centric, the themes of the lessons are broadly applicable to anyone using R, and I've even recommended the course to political scientists before.
R cheatsheets - These downloadable cheatsheets for some popular R packages are great as quick references when you are familiar with a package, but can't quite recall the proper syntax or function you need.
Geometric Morphometrics
Geometric morphometrics describe a group of methods designed for statistical analyses of shape that have been developed over the past several decades to avoid the problems associated with using linear measurements to describe complex shapes.
The canonical primer to these methods is Zelditch et al.'s Geometric Morphometrics for Biologists. The book provides an introduction to be the practical application of GM methods and the underlying theory in accessible language that does not assume a comprehensive understanding of the underlying math. The authors have also written an accompanying, freely-available guide to implementation of these methods.
Some key software for performing these analyses are: geomorph (R package), Morpho (R package), stereomorph (R package), and tpsDig (standalone program, unfortunately Windows-only)
General Stats
A table of common statistical tests, the data types to which they are suited, and examples of their execution in common stats programs
Stan
I am just getting started on using stan, a C++ based programming language used to run Bayesian models, in my work. Stan's website includes many helpful resources, including a user guide, information on how to access stan through common interfaces including R and Python. I have found that the user guide doesn't always provide reproducible examples, so here are some things I have found helpful so far:
Coding Club intro tutorial: A guide on writing, executing, and running diagnostics on stan models using the rstan R package. Unfortunately, the comprehensiveness of rstan's many useful features make it difficult for the developers to keep up with both R and stan updates, but I have found that the code in this tutorial can easily be modified to work with the cmdstanr package, as well.
WeirdFishes blog tutorial: The tutorial on fisheries scientist Dan Ovando's blog is excellent not only because it features a tutorial using a real-life application of stan, but also because it starts with a discussion on how stan actually works and why it is useful in straightforward, illustrative language.
QCBS R Workshop series - This is a series of workshops run at Quebec universities for (mostly) early career researchers in ecology and evolutionary biology, but the site includes slides and scripts that can function as self-guided tutorials. While the examples are biology- and ecology- centric, the themes of the lessons are broadly applicable to anyone using R, and I've even recommended the course to political scientists before.
R cheatsheets - These downloadable cheatsheets for some popular R packages are great as quick references when you are familiar with a package, but can't quite recall the proper syntax or function you need.
Geometric Morphometrics
Geometric morphometrics describe a group of methods designed for statistical analyses of shape that have been developed over the past several decades to avoid the problems associated with using linear measurements to describe complex shapes.
The canonical primer to these methods is Zelditch et al.'s Geometric Morphometrics for Biologists. The book provides an introduction to be the practical application of GM methods and the underlying theory in accessible language that does not assume a comprehensive understanding of the underlying math. The authors have also written an accompanying, freely-available guide to implementation of these methods.
Some key software for performing these analyses are: geomorph (R package), Morpho (R package), stereomorph (R package), and tpsDig (standalone program, unfortunately Windows-only)
General Stats
A table of common statistical tests, the data types to which they are suited, and examples of their execution in common stats programs
Stan
I am just getting started on using stan, a C++ based programming language used to run Bayesian models, in my work. Stan's website includes many helpful resources, including a user guide, information on how to access stan through common interfaces including R and Python. I have found that the user guide doesn't always provide reproducible examples, so here are some things I have found helpful so far:
Coding Club intro tutorial: A guide on writing, executing, and running diagnostics on stan models using the rstan R package. Unfortunately, the comprehensiveness of rstan's many useful features make it difficult for the developers to keep up with both R and stan updates, but I have found that the code in this tutorial can easily be modified to work with the cmdstanr package, as well.
WeirdFishes blog tutorial: The tutorial on fisheries scientist Dan Ovando's blog is excellent not only because it features a tutorial using a real-life application of stan, but also because it starts with a discussion on how stan actually works and why it is useful in straightforward, illustrative language.
