This course serves as a follow-up to MAT 1411 Applied Statistics or MAT 1415 Applied Statistics I and MAT 1416 Applied Statistics II. The content can be broken up into three parts. Students will learn models for fitting data beyond linear regression and probability distributions beyond the normal and t distributions. Students will be introduced to time series data and its correlation and covariance, as well as ways to model time series like ARMA. Students will learn about model selection, using multifactor ANOVA, maximum likelihood, and information criteria as tests for goodness of fit. Throughout, data sets will be chosen from the fields of Biology and Environmental Science, and students will be encouraged to find and use data sets relevant to them. Prerequisites: MAT 1411 Applied Statistics or MAT 1415 Applied Statistics I & MAT 1416 Applied Statistics II.
- Teacher: Christopher Potvin