STAT340 Applied Methods in Statistics
There may be changes to the course due to to corona restrictions. See Canvas and StudentWeb for info.
Showing course contents for the educational year 2019 - 2020 .
Course responsible: Thore Egeland
Teachers: Kathrine Frey Frøslie, Martin Paliocha
ECTS credits: 10
Faculty: Faculty of Chemistry, Biotechnology and Food Science
Teaching language: EN
Limits of class size:
Teaching exam periods:
The course starts in the spring semester. Teaching and exam is also in the spring semester.
Course frequency: Anually
First time: 2015H
Short introduction to R and R Studio. Practical analysis in R using various statistical methods followed by theoretical and practical interpretation of the results. The methods taught will be a collection from the following list: Multiple regression, ANOVA, random effects models, generalized linear models (logistic, poisson, multinomial regression etc), classification (lda, qda, knn, logistic, multinomial, etc), clustering, multivariate analysis (PCA, PLS, CCA, etc). A short overview of the difference in using regression techniques to predict (including prediction error and cross-validation), and to estimate effect estimates (including confounders, mediators, colliders and DAGs).
The students should know the assumptions, applications and theoretical background for the methods presented.
The students should master the use of R/R Studio as a tool for practical data analysis. It will be emphasised that the students, to a given problem, should be able to formulate the problem in such a way that it can be analysed by means of suitable methods.
The students are able to decide which method(s) to use to model and analyse the problem, and to do the analysis. The students are also able to give the practical interpretation of and to assess the validity of models, methods and results.
1. Lectures. 2. Voluntary colloquia. 3. Supervised exercises in groups. 4. Compulsory assignment. 5. Individual study.
Lectures, colloquia and exercises. In addition, the teacher offers academic guidance during regular office hours.
Will be announced on the course pages in Canvas.
STAT100, or equivalent.
STAT200, STAT210, STIN300 or equivalent.
There will be at least one compulsory assignment (near the end of the course).
Written exam, 3.5 hours, counts 100 %.
Lectures: 26 hours. Colloquia 26 hours. Exercises 26 hours. Individual study 222 hours.
Special requirements in Science
Type of course:
Lectures: 2 hours per week. Colloquia: 4 hours per week. Exercises: 2 hours per week.
Students are required to have a personal laptop.
An external examiner approves the examination questions and assesses 25 randomly selected examination papers.
Allowed examination aids: C2 Alle typer kalkulatorer, alle andre skriftlige hjelpemidler.
Examination details: One written exam: A - E / F