TILM3627 Statistical learning: Boot camp (1 cr)
Cooperation network course
Network: Cross-institutional studies in advanced courses in mathematics and statistics
This course is offered through the Network for Advanced Studies in Mathematics. These studies are available for the following degree students:
- Bachelor's Degree Programme in Mathematics
- Master's Degree Programme in Mathematics
- Bachelor's Degree Programme in Mathematics (Subject Teacher)
- Master's Degree Programme in Mathematics (Subject Teacher)
- Bachelor's Degree Programme in Mathematics, Chemistry or Physics Subject Teacher Education and Primary Teacher Education (Specialication in Mathematics)
- Master's Degree Programme in Mathematics, Chemistry or Physics Subject Teacher Education and Primary Teacher Education (Specialication in Mathematics)
- Doctoral Programme in Mathematics and Statistics
- Doctoral Programme in Mathematics and Science (Specialication in Mathematics)
Grading scale:
Pass - fail
Description
This intensive course provides a short overview on the principles of regression modeling and statistical inference needed as prerequisites for the subsequent Advanced Regression Analysis and Statistical Learning course (TILM3587/TILM3622, "Regressioanalyysi ja tilastollinen oppiminen" in Finnish). This course does not replace elementary, and preferably also some intermediate, level courses in statistics. Instead, this course is intended for those wishing to improve their understanding on the basics of linear and logistic regression analyses and their R interface (including a short introduction to R program) and to illustrate by examples how especially the multiple linear regression model can be constructed and applied in practice.
Learning outcomes
By the end of the course, the student should have knowledge on the following topics:
- Basics of linear and logistic regression model (with one and multiple predictors)
- Simple matrix algebra needed in regression analysis
- Basics of R programming (RStudio) related to regression analysis (basic commands and data handling)
- Necessary basic prerequisites to participate in the course Advanced Regression Analysis and Statistical Learning (TILM3587/TILM3622)
Additional information
This course contains material typical for basic and intermediate level studies in statistics before moving to advanced studies.
Description of prerequisites
Basic level and preferably also some intermediate level knowledge on statistics.
In the UTUGS programme (postgraduate students), at least Basics of Statistics TILM3582 (or equivalent) and preferably also Basics of Statistical Modelling TILM3583.