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3622351 Statistical Data analysis, 6 Cp 
Code 3622351  Validity 01.01.1950 -
Name Statistical Data analysis  Abbreviation TDA 
Credits6 Cp  Date of expiry  
TypeIntermediate Studies Subject0390 Statistics 
ClassStudy Unit  Hours  
Study right   Grading0-5 
Recommended scheduling 
Organisation Computer Science (J,K) 

Learning outcomes 

The student understands the linear model and its most important extensions and is able to do these analyses using R-software.


Simple linear regression and multiple linear regression using matrix notations, when residual errors are independent and they have constant variance. Use of categorical and continuous predictors in the model and interpretation of model parameters. Use of transformations. Estimation using ordinary least squares (OLS) and the properties of the estimator. Test of hypothesis, model diagnostics and prediction. t-test, analysis of variance and analysis of covariance as special cases of the model. Model formulation if the assumption of constant error variance and independence is not met (so called general linear model). Generalized least squares (GLS), maximum likelihood (ML), and restricted maximum likelihood. Review of generalized linear models (GLM, e.g. binary logistic regression).

Modes of study 

Exercises and written exam

Teaching methods 

Lectures (36 h) and exercises (18 h)

Study materials 

Fahrmeir, L., Kneib, T., Lang, S. and Marx, Brian 2013. Regression models, methods and applications. Springer. Chapters 3-5.

Evaluation criteria 



Basic course in statistics, R-language. Probabilistic inference for data science 1 and 2 / Introduction to statistical inference 1 and 2 are also suggested. Special tutorials on matrices will be arranged if needed. 


Letter (J, K) in front of the name of the course/exam indicates the campus on which teaching or exam takes place: J = Joensuu, K = Kuopio.

Present and future teaching
No teaching

Future exams
No exams