Bi7491 Regression Modelling

Faculty of Science
Spring 2017
Extent and Intensity
2/1. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
prof. RNDr. Ladislav Dušek, Ph.D. (lecturer)
RNDr. Ondřej Májek, Ph.D. (lecturer)
RNDr. Tomáš Pavlík, Ph.D. (lecturer)
Guaranteed by
prof. RNDr. Ladislav Dušek, Ph.D.
RECETOX – Faculty of Science
Contact Person: RNDr. Ondřej Májek, Ph.D.
Supplier department: RECETOX – Faculty of Science
Timetable
Mon 20. 2. to Mon 22. 5. Thu 9:00–11:50 F01B1/709
Prerequisites
Student should be familiar with the following topics: fundamentals of the probability theory; vector and matrix algebra; random variable, its distribution and characteristics; hypothesis testing; linear model.
Course Enrolment Limitations
The course is offered to students of any study field.
Course objectives
At the end of this course, a student should be able to:
define various types of regression models;
design and build up a regression model suitable for the particular problem;
evaluate a fit of the proposed model;
interpret results of the regression analysis;
Syllabus
  • Repetition of relevant biostatistical topics.
  • Concepts in regression modelling: regression modelling strategies, assumptions of linear regression model, independent variables, setup and performance the analysis, interpretation and evaluation of the assumptions.
  • Logistic and Poisson regression models.
  • Mixed model.
  • Non-linear modelling.
  • Validation of the predictive regression model.
Literature
  • HARRELL, Frank E. Regression modeling strategies : with applications to linear models, logistic regression, and survival analysis. New York: Springer, 2001, xxii, 568. ISBN 1441929185. info
Teaching methods
Lectures focused on theoretical aspects as well as practical applications. Practices in a computer room focused on practical regression modelling in R software.
Assessment methods
There is one short test during the term. Students should work up a project concerning one practical application of regression modelling. The course is finished with both written and oral exam.
Language of instruction
Czech
Follow-Up Courses
Further comments (probably available only in Czech)
General note: Doporučeno absolvování předmětu Bi5040 Biostatistika - základní kurz nebo Bi5045 Biostatistika v matematické biologii.
Listed among pre-requisites of other courses
The course is also listed under the following terms Spring 2011 - only for the accreditation, Spring 2011, Spring 2012, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022.
  • Enrolment Statistics (Spring 2017, recent)
  • Permalink: https://is.muni.cz/course/sci/spring2017/Bi7491