spring 2017
HEL-8024 Quantitative Research Methods - 3 ECTS

Application deadline

External applicants: Application deadline is December 1st. Application code 9303 in Søknadsweb.

It granted admission to the course you have to register for class and exam in Studentweb by February 1st.

PhD students and students at the Medical Student Research Program at UiT - The Arctic University of Norway go driectly to Studentweb to register for class and exam.

Type of course

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

Admission requirements

PhD students, masters students at a Medical Student Research Program, or holders of a Norwegian master´s degree of five years or 3+ 2 years (or equivalent) may be admitted. Valid documentation is a statement from your institution that you are a registered PhD student, or master student at a Medical Student Research Program or a Master´s Diploma with Diploma Supplement / English translation of the diploma. PhD students are exempt from semester fee.

For more information regarding PhD courses at the Faculty of Health Sciences go to: http://uit.no/helsefak/forskning/phd/emner

It is recommended that you take this course early in your PhD study and after having taken HEL-8010.

Course overlap

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

Course content

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.

Objectives of the course


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
  • discuss the concept of statistical power


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

Language of instruction and examination

The instruction language will be in English given attendance from foreign students.

Teaching methods

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



Written exam graded as pass/fail. The exam will contain a mixture of multiple choice questions and open-ended questions. Length of exam: 2 hours.

No re-sit exam will be given as the course is given continuously.

Recommended reading/syllabus

Recommended reading/syllabus

Andy Field: Discovering Statistics Using SPSS (Fourth Edition) chapter 1-5, 7-9


Andy Field: an adventure in statistics, 2016, first edition

  • About the course
  • Campus: Tromsø |
  • ECTS: 3
  • Course code: HEL-8024
  • Tilleggsinformasjon
  • PhD students at UiT
  • External applicants
  • Course information
  • Tidligere år og semester for dette emnet