Statistical modelling
The goal of this course is to provide basic notions of statistical analysis and inference as well as advanced statistical methods. In addition to the theoretical concepts, this course will focus on the practical applications of these methods.
Instructor
Course details
- Fall 2020
- Wednesday
- 15:30–18:30
- Zoom
Contact
I am best reached by email or on Piazza
Course description
The objective is to provide students with the basics of statistical inference, as well as statistical tools for data modeling in a regression framework. The theory behind the statistical models will be reviewed with some specific emphasis on data applications using the software SAS.
The course will focus on regression models, including linear models, generalized linear models and models for longitudinal data with random effects and correlation structure. For each of these models, basic inference principles will be reviewed such as hypothesis testing and estimation procedures.
- Basic principles in inference and statistical modeling
- Linear models
- Generalized linear models
- Models for longitudinal data and correlated data
- Introduction to survival analysis
Concept
This course is organized as a flipped classroom. The learning material includes course notes, slides with accompanying videos and quiz along with short coding exercises.
Students must read and go through the learning material before class time: the latter will be devoted to discussion about the material and exercises, workshops and code demonstrations.
Prerequisites
The course is of an overview course. Students should have basic training in statistics at the level of Introductory Statistics with Randomization and Simulation (Chapters 1–4, excluding special topics). Familiarity with basic calculus and linear algebra is also assumed.
Target audience
Statistical modelling is a compulsory course of the M.Sc. in Data Science and Business Analytics (Supervised Project stream) and an optional course for the Thesis stream. Please note this course is not credited in the “Intelligence d’affaires” specialization: the course is incompatible with MATH606019(A).
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Contributors
- Léo Belzile wrote the new version of the course notes and created most of the exercise sheets and the accompanying solutions.
- Denis Larocque wrote the initial course notes for Analyse et inférence statistique, a precursor to this course.
- Aurélie Labbe transformed these notes into slides and taught multiple iterations of the course, writing R scripts and some exercises.
- Kevin McGregor translated the slides from French to English.
- Juliana Schulz taught the first iteration of MATH60604A in the Fall 2019 and created the material for survival analysis.