Quantitative Research Methods

PhD course. This course is available as a singular course.

The aim of the course is to provide an introduction to basic concepts in statistics and the theoretical foundations for basic statistics that are relevant across most branches of the health sciences. The objective is to introduce the students to descriptive statistics e. g. central tendency and dispersion as well as to inferential statistics based on probability distributions, confidence intervals, hypothesis testing and scientific study designs. Furthermore, the course teaches t-test, correlation analysis and basics for regression analyses.

PhD students and students at the Student Research Programme, or holders of a Norwegian master´s degree of five years or 3+ 2 years (or equivalent) may be admitted. External PhD students and students at other student research programmes, must upload a document from their university stating that they are registered students. This group of applicants does not have to prove English proficiency and are exempt from semester fee.

Holders of a Master´s degree must upload their Master´s Diploma with Diploma Supplement / English translation of the diploma. Applicants from the below list of countries must document proficiency in English. To find out if this applies to you see the following list:

Proficiency in English must be documented - list of countries

For more information on accepted English proficiency tests and scores, as well as exemptions from the English proficiency tests, please see the following document:

Proficiency in English - PhD level studies

It is recommended that you take this course early in your PhD study and after having taken HEL-8040.

Knowledge

By the end of this course, the candidate has knowledge that enables him/her to:

• organize the basic concepts in statistics, such as central tendency and variance and be able to discuss their theoretical foundations
• be able to judge types of probability distributions
• be able to organize different study designs
• discuss the concept of a confidence interval
• discuss the principle behind a significance test
• is able to check the assumptions for performing t-tests

skills and competence

By the end of this course, the candidate has skills that enables him/her to:

• conduct a hypothesis test comparing two means (t-test)
• carrying out a correlation/partial correlation analysis and reporting the results according to publication standards, and interpreting the results
• perform simple regression analyses
• report the results of a statistical analysis according to publication standards
• to calculate effect sizes and p values

If you pass the examination in this course, you will get an reduction in credits (as stated below), if you previously have passed the following courses:

• HEL-8012 Quantitative Research Methods 3 stp
• HEL-8047 Statistical models, conclusions and uncertainty for scientific data analysis 1 stp

The course consists of four full teaching days and combines introductory lectures with exercises/examples for group work or plenary discussions. A high degree of participant involvement and activity is expected.

The topics for the four days will be:

Day 1: Variables and research/study design

Day 2: Descriptive statistics, probability, sampling and distributions

Day 3: Correlations/partial correlations and regression

Day 4: Hypothesis testing and significance testing, t-test

Language of instruction and examination

PhD students and students at the Student Research Program at UiT The Arctic University of Norway register for class and exam in Studentweb by September 1st for autumn semester and February 1st for spring semester.

Other applicants apply for the right to study by June 1st for courses that are taught in the fall semester and December 1st for courses that are taught in the spring semester. Application is sent through Søknadsweb. Please use the appliction code "9301 - Singular courses at the PhD level".

Emnet legges ned og siste mulighet til å avlegge eksamen etter dette semesteret, er vår 2024.

Her finner du mer informasjon om eksamen i nedlagte emner

Re-sit examination