Quantitative methods 7,5 Credits

Aim

This is an introductory course for doctoral students with little knowledge of statistics, intended to give the doctoral student a basic understanding of the use of quantitative statistical techniques. The course aims to provide broad and comprehensive knowledge of quantitative methods, as well as to provide the conditions for developing the doctoral student to become a critical and independent researcher.
The aim of the course for the doctoral student is to understand the potential of quantitative methods and to be able to interpret statistical results.

Course objectives

After passing the course, the doctoral student should be able to describe the principles that form the basis for a position in the selection of data collection and analysis questions and be able to choose and apply relevant methods for analysis and interpretation of data.

Content

The course begins with the collection and completion of quantitative data. After that, univariata and preliminary analyses are processed, including review of data and descriptive statistics. During the course some of the most common bivariate and multivariate analytical techniques are shown, such as correlation, regression, and factor analysis. Statistical techniques for comparing different groups, such as t-test and ANOVA, are also discussed during the course.

Entry requirements

Admission to the course requires that the student be admitted to third-cycle education and can be credited for the course in his/her doctoral education.
(Äldre gymnasiebetyg)

Selection rules and procedures

The selection process is in accordance with the Higher Education Ordinance and the local order of admission.

Teaching form

Teaching is conducted in the form of lectures, computer labs and independent individual assignments.

Examination form

The individual examination consists of a written assignment for which the doctoral student has chosen and applied relevant methods for analysis and interpretation of collected data.

Grading system

Fail (U) or Pass (G)

Other information

The course is given as an optional course at the Faculty of Human Sciences.