FAR-8001 Statistical Modeling and Multivariate Analysis of Multidimensional Data Sets - 5 stp

The course will offer training opportunity in applied, advanced statistics, combining statistical modelling and multivariate analyses. With its balance between statistical theory and application, the course focus on analysis of real multidimensional data obtained from complex designs, and stress on effective communication of quantitative results in reports, publications and oral presentations, and will provide a thorough introduction to advanced statistical applications for young researchers in the health sciences.

After a brief review of study design and data analysis in biomedical and pharmaceutical research, the course will cover statistical modelling (Maximum Likelihood models), classification and ordination methods. The multivariate methods covered will include cluster analysis, discriminant analysis, multidimensional scaling (MDS), Principal Component Analysis (PCA), Correspondence Analysis (CA), and Constrained Correspondence Analysis (CCA). Graphical presentation and interpretation will play a prominent role to ensure exposure to effective communication of quantitative results.

Application deadline is June 1st.

Application code is 9301.

PhD students or holders of a Norwegian master´s degree of five years or 3+ 2 years (or equivalent) may be admitted. PhD students must upload a document from their university stating that they are registered PhD students. This group of applicants does not have to prove English proficiency and are exempt from semester fee. Students are expected to have skills equivalent to the prerequisites listed for the course.

Holders of a Master´s degree must upload a Master´s Diploma with Diploma Supplement / English translation of the diploma.

Mandatory prerequisites:

Course attendants are expected to be familiar with descriptive statistics (figures and summary tables) and basic inferential statistics (estimation and confidence intervals, hypothesis testing and P-values). Attendants should also have some experience handling databases (in e.g. Excel) and using statistical software. During the course we will use the software R, exposure to this program helps but is not required to participate.

English proficiency:

Proficiency in English must be documented.

For more information on accepted English proficiency tests and scores, as well as exemptions from the English proficiency tests, please see here.

Course capasity:

The course has a capasity of 25 students. If there are more applicants than available spaces in the course, students will be given priority from category 1 to 5:

1. PhD students, who are affiliated with the national network "National PhD School of Pharmacy" (NFIF).

2. PhD students, research fellows and students participating in the Student Research Programme at UiT The Arctic University of Norway.

3. Participants in the Associate Professor Programme.

4. PhD students and students at a Student Research Programme at other universities.

5. People who have minimum a master's degree or equivalent, but have not been admitted to a PhD programme.

The course aims to achieve the following learning goals. By the end of the course, attendants should

Knowledge

• know how to design and perform complex quantitative studies
• know how to clearly and effectively communicate the results of the analyses of complex studies with the help of graphical representations
• know how to interpret statistical modelling and multivariate analysis results and draw correct inferences from these

Skills

• be able to choose appropriate statistical methods based on problem and character of the data
• be able to implement correctly the chosen statistical methods (with the help of suitable software, e.g. R)
• be able to report results of complex quantitative studies

Competence

• understand the relevant methodological literature, including new advancements
• be able to critically evaluate complex quantitative studies
• be able to plan, perform and report complex quantitative studies

Work requirements:

Mandatory lectures and pc-lab.

The course attendants will have to prepare a short presentation of their research outlining i) research question(s), ii) aims, iii) approach (emphasis on quantitative aspect, i.e. study design and planned statistical analyses), preliminary results and interpretation of findings.

Examination: Written home examination, max. 10 pages.

Grading scale: Passed / Failed

Examination language: English/Norwegian.

Re-sit examination:

Students who get the grade "Failed" on the examination may register for a re-sit exam. The re-sit exam is given in the beginning of the following semester. Registration deadline for the re-sit exam is January 15th.