References

Math Camp References

  • Aragón-Artacho, Francisco J., and Miguel A. Goberna. 2024. Mathematics in Politics and Governance. Cham: Springer Nature Switzerland. doi:10.1007/978-3-031-52776-0.

  • Fox, John. 2015. Applied Regression Analysis and Generalized Linear Models. SAGE Publications.

  • Fox, John. 2020. A Mathematical Primer for Social Statistics. SAGE Publications.

  • Gelman, Andrew, and Aki Vehtari. 2024. Active Statistics: Stories, Games, Problems, and Hands-on Demonstrations for Applied Regression and Causal Inference. Cambridge University Press.

  • Kropko, Jonathan. 2015. Mathematics for Social Scientists. SAGE Publications.

  • Moore, Will H., and David A. Siegel. 2013. A Mathematics Course for Political and Social Research. doi:10.1515/9781400848614.

Coding Camp References

  • Lafaye de Micheaux, Pierre, Rémy Drouilhet, and Benoit Liquet. 2013. The R Software: Fundamentals of Programming and Statistical Analysis. Springer. https://espace.library.uq.edu.au/view/UQ:328604 (August 13, 2024).

  • Mailund, Thomas. 2017. Functional Programming in R: Advanced Statistical Programming for Data Science, Analysis and Finance. Apress.

  • Mathematics and Programming for Machine Learning with R | From the Gro. https://www.taylorfrancis.com/books/mono/1 0.1201/9781003051220/mathematics-programming-machine-learning-william-claster (August 13, 2024).

  • Okoye, Kingsley, and Samira Hosseini. 2024. R Programming: Statistical Data Analysis in Research. Springer Nature.

  • Pace, Larry. 2012. Beginning R: An Introduction to Statistical Programming. Apress.

  • Software for Data Analysis. https://link.springer.com/book/10.1007/978-0-387-75936-4.

  • Wiley, Matt, and Joshua F. Wiley. 2019. Advanced R Statistical Programming and Data Models: Analysis, Machine Learning, and Visualization. Apress.