Course code STAT340

STAT340 Applied Methods in Statistics

Norsk emneinformasjon

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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
(NO=norsk, EN=Engelsk)
Limits of class size:
1000
Teaching exam periods:
The course starts in the spring semester. Teaching and exam is also in the spring semester.
Course frequency: Anually
First time: Study year 2015-2016
Course contents:
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).
Learning outcome:

Knowledge

The students should know the assumptions, applications and theoretical background for the methods presented.

Skills

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.

General competence

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.

Learning activities:
1. Lectures. 2. Voluntary colloquia. 3. Supervised exercises in groups. 4. Compulsory assignment. 5. Individual study.
Teaching support:

Lectures, colloquia and exercises. In addition, the teacher offers academic guidance during regular office hours.

Canvas

Syllabus:
Will be announced on the course pages in Canvas.
Prerequisites:
STAT100, or equivalent.
Recommended prerequisites:
STAT200, STAT210, STIN300 or equivalent.
Mandatory activity:
There will be at least one compulsory assignment (near the end of the course).
Assessment:
Written exam, 3.5 hours, counts 100 %.
Nominal workload:
Lectures:  26 hours. Colloquia 26 hours. Exercises 26 hours. Individual study 222 hours.
Entrance requirements:
Special requirements in Science
Type of course:
Lectures: 2 hours per week. Colloquia: 4 hours per week. Exercises: 2 hours per week. 
Note:
Students are required to have a personal laptop.
Examiner:
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