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Short R and BUGS tutorials for beginners.
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data
models
.gitignore
01_basic_operations.R
02_importing_data.R
03_basic_statistics.R
04_figures.R
05_conditionals_loops_functions.R
06_glms_glmms.R
07_maximum_likelihood.R
08_JAGS_intro.R
09_glms_JAGS.R
10_randomeffects_JAGS.R
11_debugging_JAGS.R
12_advanced_models.R
13_resampling.R
LICENSE
README.md

README.md

tutorials

Short R and JAGS tutorials for beginners, mainly for use in various classes I have taught.

The tutorials are presented in a suggested order. The data directory contains data files (CSV) used in the examples. The model directory contains JAGS models used in example Bayesian analyses. The R files include step-by-step comments and observations.

To download an individual tutorial file, click on the file, select 'raw', and download the file using 'save page as' in your browser options.

Summary of tutorial contents:

  1. Basic operations in R including math, simple functions, data formats and containers

  2. Importing data into R from spreadsheets; manipulating data in R data frames; saving R objects and workspaces

  3. Basic statistical tests in R, e.g. t-tests, ANOVA, simple linear regression

  4. Creating and customizing plots and figures in R

  5. Conditionals and true/false statements; looping structures in R (for, while loops); writing custom functions

  6. Fitting generalized linear models and generalized linear mixed models in R using glm(), lme(), and glmmPQL()

  7. A brief introduction to maximum likelihood estimation in R using optim()

  8. Introduction to JAGS (Just Another Gibbs Sampler) and the R interface package R2jags for doing Bayesian analysis in R

  9. Generalized linear models (logistic and Poisson) fit in JAGS

  10. Mixed models in JAGS (i.e., including both fixed and random effects)

  11. A demonstration of common errors when running analyses using JAGS

  12. More advanced models fit in a Bayesian framework including occupancy and N-mixture models

  13. Introduction to resampling tests in R (randomization/permutation tests)

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