Resources

Lecture Notes

• https://bookdown.org/hefleyt2/stat768spring2023/

Required Text

• Hooten, M.B., and Hefley, T.J. (2019) Bringing Bayesian Models to Life. CRC Press [amazon] [R code][errata]

Recommend texts

• Hobbs, N.T., and M.B. Hooten (2015) Bayesian models: a statistical primer for ecologists. Princeton University Press [amazon]

• Gelman, A., Carlin, J.B., Stern, H.S., Dunson, D.B., Vehtari, A. and Rubin, D.B. (2013) Bayesian data analysis. Third Edition. CRC Press [link]

Recommended software

• R Core Team (2023) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing [link]

• RStudio Team (2023) RStudio: Integrated Development for R. RStudio, Inc. [link]

Reproducible research

• Xie Y., Allaire J., Grolemund G. (2018) R Markdown: the definitive guide. CRC Press [bookdown]

Matrix algebra for statisticians

• Fieller, N. (2015) Basics of Matrix Algebra for Statistics with R. Chapman and Hall/CRC [amazon]