Statistical Modelling with Regression Methods, 6 credits
Statistisk modellering med regressionsmetoder, 6 hp
TAMS41
Main field of study
Mathematics Applied MathematicsCourse level
Second cycleCourse type
Programme courseExaminer
Martin SingullDirector of studies or equivalent
Nils-Hassan QuttinehEducation components
Preliminary scheduled hours: 44 hRecommended self-study hours: 116 h
Available for exchange students
YesMain field of study
Mathematics, Applied MathematicsCourse level
Second cycleAdvancement level
A1XCourse offered for
- Chemical Biology, M Sc in Engineering
- Engineering Biology, M Sc in Engineering
- Master's Programme in Mathematics
- Applied Physics and Electrical Engineering - International, M Sc in Engineering
- Applied Physics and Electrical Engineering, M Sc in Engineering
Entry requirements
Note: Admission requirements for non-programme students usually also include admission requirements for the programme and threshold requirements for progression within the programme, or corresponding.
Prerequisites
A first course in probability and statisticsIntended learning outcomes
The course is intended to give the knowledge and understanding of different regression methods with applications, i.e., give the students the statistical tools to analyze one or several response variables with different predictors. Models and methods in two different situations will be considered: i) classical statistical modelling, i.e., small number of variables with large number of observations, which leads to different types of (multivariate) regression models, and ii) high dimensional models, when the number of predictors is larger than the number of observations, which leads to prediction and classification algorithms for high dimensional data.
By the end of the course, the student should be able to:
- know the sampling properties of point estimators used in regression models as well as principles and assumptions behind different estimation techniques applied,
- list and understand the assumptions behind standard parametric and model inference in the regression models,
- assess the fit of a regression model to data and know how to identify and diagnose potential problems,
- identify and develop regression modelling strategies suitable for large sample as well as for high-dimensional settings,
- explain how the multiple linear regression can be generalized to handle a response variable that is categorical or a count variable,
- use generalized linear models to analyze data, interpret the analyzes and discuss the adequacy of the methods;
- motivate the needs for and benefits of resampling methods in regression modelling and use resampling algorithms, in particular bootstrap and cross-validation, for estimation of the model predictive accuracy,
- understand the need of mixed linear models and use these in statistical analyses,
- critically evaluate regression models in some real-world applications based on the above context.
Course content
Linear models. ANOVA and MANOVA. Multiple linear regression. Model validation and diagnostic strategies. Non-linear regression. Generalized linear models and logistic regression. Regression methods for high dimensional data (Ridge, Lasso). Mixed linear models. Repeated measurements. Partial least squares and principal component regression.
Teaching and working methods
Teaching consists of lectures, (computer) example classes and a project assignment.
Examination
UPG1 | Project assignment | 2 credits | U, G |
TEN1 | Written examination | 4 credits | U, 3, 4, 5 |
Grades
Four-grade scale, LiU, U, 3, 4, 5Department
Matematiska institutionenDirector of Studies or equivalent
Nils-Hassan QuttinehExaminer
Martin SingullCourse website and other links
Education components
Preliminary scheduled hours: 44 hRecommended self-study hours: 116 h
Course literature
Books
- Dobson, A. J., & Barnett, A., (2008) An introduction to generalized linear models CRC press
- Hastie, T., Tibshirani, R., & Friedman, J., (2017) The Elements of Statistical Learning 2 Springer
- James, G., Witten, D., Hastig, T., & Tibshirani, R., (2013) An introduction to statistical learning Springer
Compendia
Supplementary compendium issued by the Department.
Code | Name | Scope | Grading scale |
---|---|---|---|
UPG1 | Project assignment | 2 credits | U, G |
TEN1 | Written examination | 4 credits | U, 3, 4, 5 |
Course syllabus
A syllabus has been established for each course. The syllabus specifies the aim and contents of the course, and the prior knowledge that a student must have in order to be able to benefit from the course.
Timetabling
Courses are timetabled after a decision has been made for this course concerning its assignment to a timetable module. A central timetable is not drawn up for courses with fewer than five participants. Most project courses do not have a central timetable.
Interrupting a course
The vice-chancellor’s decision concerning regulations for registration, deregistration and reporting results (Dnr LiU-2015-01241) states that interruptions in study are to be recorded in Ladok. Thus, all students who do not participate in a course for which they have registered must record the interruption, such that the registration on the course can be removed. Deregistration from a course is carried out using a web-based form: www.lith.liu.se/for-studenter/kurskomplettering?l=sv.
Cancelled courses
Courses with few participants (fewer than 10) may be cancelled or organised in a manner that differs from that stated in the course syllabus. The board of studies is to deliberate and decide whether a course is to be cancelled or changed from the course syllabus.
Regulations relating to examinations and examiners
Details are given in a decision in the university’s rule book: http://styrdokument.liu.se/Regelsamling/VisaBeslut/622678.
Forms of examination
Examination
Written and oral examinations are held at least three times a year: once immediately after the end of the course, once in August, and once (usually) in one of the re-examination periods. Examinations held at other times are to follow a decision of the board of studies.
Principles for examination scheduling for courses that follow the study periods:
- courses given in VT1 are examined for the first time in March, with re-examination in June and August
- courses given in VT2 are examined for the first time in May, with re-examination in August and October
- courses given in HT1 are examined for the first time in October, with re-examination in January and August
- courses given in HT2 are examined for the first time in January, with re-examination at Easter and in August.
The examination schedule is based on the structure of timetable modules, but there may be deviations from this, mainly in the case of courses that are studied and examined for several programmes and in lower grades (i.e. 1 and 2).
- Examinations for courses that the board of studies has decided are to be held in alternate years are held only three times during the year in which the course is given.
- Examinations for courses that are cancelled or rescheduled such that they are not given in one or several years are held three times during the year that immediately follows the course, with examination scheduling that corresponds to the scheduling that was in force before the course was cancelled or rescheduled.
- If teaching is no longer given for a course, three examination occurrences are held during the immediately subsequent year, while examinations are at the same time held for any replacement course that is given, or alternatively in association with other re-examination opportunities. Furthermore, an examination is held on one further occasion during the next subsequent year, unless the board of studies determines otherwise.
- If a course is given during several periods of the year (for programmes, or on different occasions for different programmes) the board or boards of studies determine together the scheduling and frequency of re-examination occasions.
Registration for examination
In order to take an examination, a student must register in advance at the Student Portal during the registration period, which opens 30 days before the date of the examination and closes 10 days before it. Candidates are informed of the location of the examination by email, four days in advance. Students who have not registered for an examination run the risk of being refused admittance to the examination, if space is not available.
Symbols used in the examination registration system:
** denotes that the examination is being given for the penultimate time.
* denotes that the examination is being given for the last time.
Code of conduct for students during examinations
Details are given in a decision in the university’s rule book: http://styrdokument.liu.se/Regelsamling/VisaBeslut/622682.
Retakes for higher grade
Students at the Institute of Technology at LiU have the right to retake written examinations and computer-based examinations in an attempt to achieve a higher grade. This is valid for all examination components with code “TEN” and "DAT". The same right may not be exercised for other examination components, unless otherwise specified in the course syllabus.
Retakes of other forms of examination
Regulations concerning retakes of other forms of examination than written examinations and computer-based examinations are given in the LiU regulations for examinations and examiners, http://styrdokument.liu.se/Regelsamling/VisaBeslut/622678.
Plagiarism
For examinations that involve the writing of reports, in cases in which it can be assumed that the student has had access to other sources (such as during project work, writing essays, etc.), the material submitted must be prepared in accordance with principles for acceptable practice when referring to sources (references or quotations for which the source is specified) when the text, images, ideas, data, etc. of other people are used. It is also to be made clear whether the author has reused his or her own text, images, ideas, data, etc. from previous examinations.
A failure to specify such sources may be regarded as attempted deception during examination.
Attempts to cheat
In the event of a suspected attempt by a student to cheat during an examination, or when study performance is to be assessed as specified in Chapter 10 of the Higher Education Ordinance, the examiner is to report this to the disciplinary board of the university. Possible consequences for the student are suspension from study and a formal warning. More information is available at https://www.student.liu.se/studenttjanster/lagar-regler-rattigheter?l=sv.
Grades
The grades that are preferably to be used are Fail (U), Pass (3), Pass not without distinction (4) and Pass with distinction (5). Courses under the auspices of the faculty board of the Faculty of Science and Engineering (Institute of Technology) are to be given special attention in this regard.
- Grades U, 3, 4, 5 are to be awarded for courses that have written examinations.
- Grades Fail (U) and Pass (G) may be awarded for courses with a large degree of practical components such as laboratory work, project work and group work.
Examination components
- Grades U, 3, 4, 5 are to be awarded for written examinations (TEN).
- Grades Fail (U) and Pass (G) are to be used for undergraduate projects and other independent work.
- Examination components for which the grades Fail (U) and Pass (G) may be awarded are laboratory work (LAB), project work (PRA), preparatory written examination (KTR), oral examination (MUN), computer-based examination (DAT), home assignment (HEM), and assignment (UPG).
- Students receive grades either Fail (U) or Pass (G) for other examination components in which the examination criteria are satisfied principally through active attendance such as other examination (ANN), tutorial group (BAS) or examination item (MOM).
The examination results for a student are reported at the relevant department.
Regulations (apply to LiU in its entirety)
The university is a government agency whose operations are regulated by legislation and ordinances, which include the Higher Education Act and the Higher Education Ordinance. In addition to legislation and ordinances, operations are subject to several policy documents. The Linköping University rule book collects currently valid decisions of a regulatory nature taken by the university board, the vice-chancellor and faculty/department boards.
LiU’s rule book for education at first-cycle and second-cycle levels is available at http://styrdokument.liu.se/Regelsamling/Innehall/Utbildning_pa_grund-_och_avancerad_niva.
Books
Compendia
Supplementary compendium issued by the Department.
Note: The course matrix might contain more information in Swedish.
I | U | A | Modules | Comment | ||
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1. DISCIPLINARY KNOWLEDGE AND REASONING | ||||||
1.1 Knowledge of underlying mathematics and science (G1X level) |
X
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X
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X
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TEN1
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1.2 Fundamental engineering knowledge (G1X level) |
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1.3 Further knowledge, methods, and tools in one or several subjects in engineering or natural science (G2X level) |
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1.4 Advanced knowledge, methods, and tools in one or several subjects in engineering or natural sciences (A1X level) |
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1.5 Insight into current research and development work |
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2. PERSONAL AND PROFESSIONAL SKILLS AND ATTRIBUTES | ||||||
2.1 Analytical reasoning and problem solving |
X
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X
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X
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TEN1
UPG1
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2.2 Experimentation, investigation, and knowledge discovery |
X
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X
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UPG1
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2.3 System thinking |
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2.4 Attitudes, thought, and learning |
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X
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TEN1
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2.5 Ethics, equity, and other responsibilities |
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X
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TEN1
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3. INTERPERSONAL SKILLS: TEAMWORK AND COMMUNICATION | ||||||
3.1 Teamwork |
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X
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UPG1
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3.2 Communications |
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X
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UPG1
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3.3 Communication in foreign languages |
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X
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4. CONCEIVING, DESIGNING, IMPLEMENTING AND OPERATING SYSTEMS IN THE ENTERPRISE, SOCIETAL AND ENVIRONMENTAL CONTEXT | ||||||
4.1 External, societal, and environmental context |
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4.2 Enterprise and business context |
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4.3 Conceiving, system engineering and management |
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4.4 Designing |
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4.5 Implementing |
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4.6 Operating |
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5. PLANNING, EXECUTION AND PRESENTATION OF RESEARCH DEVELOPMENT PROJECTS WITH RESPECT TO SCIENTIFIC AND SOCIETAL NEEDS AND REQUIREMENTS | ||||||
5.1 Societal conditions, including economic, social, and ecological aspects of sustainable development for knowledge development |
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5.2 Economic conditions for knowledge development |
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5.3 Identification of needs, structuring and planning of research or development projects |
X
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X
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UPG1
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5.4 Execution of research or development projects |
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5.5 Presentation and evaluation of research or development projects |
X
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X
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UPG1
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