|Fakulteit||Faculty of Economic and Management Sciences|
Supervised learning. Linear and non-linear regression. Ordinary least squares and maximum likelihood estimation. Violations of the assumptions, residual analysis. Cross validation. Statistical inference. Bootstrap inference. Supporting mathematical concepts. Statistical concepts are demonstrated and interpreted through practical coding and simulation within a data science framework.
|Service modules||Faculty of Engineering, Built Environment and Information Technology
Faculty of Humanities
Faculty of Natural and Agricultural Sciences
|Prerequisites||STK 210, STK 220|
|Contact time||1 practical per week, 3 lectures per week|
|Language of tuition||Module is presented in English|
|Period of presentation||Semester 1|
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