Quantitative methods (BPS310)

Content

The course provides an introduction to quantitative methods for analyzing psychological data. The course gives students an introduction to statistical procedures for analyzing quantitative research data, such as data from questionnaire responses and psychological tests.

The students will be introduced to basic statistical inference, i.e. drawing conclusions about unknown quantities, parameters, related to the population and the use of statistics programs, e.g. SPSS. The course will step by step review descriptive statistics of one variable (univariate analysis), relationship between two variables (bivariate analysis), and statistical modeling of relationships (regression analysis). The course will review traditional statistical tests (including chi-square test, T-test, ANOVA and correlation), and put these in context with linear and logistic regression. The course will also cover mixed methods approaches.

The course will provide a broad introduction to quantitative methods and knowledge of when different methods are used. The students will learn to apply the various methods and discuss the results from these. Furthermore, students will learn to document procedures, as well as to discuss the importance of being able to reproduce results at a later stage.

Learning outcome

Knowledge

After completing the course, the student will be able to:

• basic knowledge of various quantitative methods, their assumptions and challenges
• basic knowledge of statistical analysis of psychologically relevant data
• knowledge of statistical inference
• knowledge of the use of statistical software
• knowledge of research ethics and principles of transparency in scientific activity

Skils

After completing the course, the student will be able to:

• import data from common formats (open text format, CSV and similar)
• perform common statistical analyzes in one or more common statistical programs (SPSS)
• communicate results from statistical analyzes in text, similar to how it is done in relevant journals
• document the above-mentioned process (from import to results section) in a transparent and verifiable manner so that all results, tables and figures can be reproduced by others without other documentation
• be able to critically assess statements that are wholly or partly based on statistics

General competence

After completing the course, the student will be able to:

• have a basic understanding of key quantitative methods in psychology
• be able to apply quantitative methods within a sound and satisfactory scientific standard
• be able to use statistics programs to analyze various forms of quantitative data

Required prerequisite knowledge

Recommended prerequisites

Exam

Coursework requirements

All of the compulsory activities must be approved in order for the student to be eligible for examination. Approval/non-approval of compulsory activities is announced on Studentweb, normally no later than 7 days before the examination. Students who lack approval of one or more compulsory activities will be withdrawn from the examination.

Compulsary activities:

• Seminars: Preparation for, attendance and participation in five seminars. Students who have less than 75% attendance at the seminars lose the right to take the examination, regardless of the reason.
• Written assignment: Written assignment: Written individual work requirement assessed as approved/not approved. Extent: 1000 words (+/-10%). incl. table of contents, source references and bibliography. Reference style: APA 7th. The topic for the assignment is defined by the course supervisor.

Course teacher(s)

Course coordinator:

Method of work

Various teaching and learning methods are used in the subject, including lectures, seminars, demonstration videos and individual work.

The student is expected to prepare for the lectures through literature studies. Recommended literature is indicated in the lecture plan.

At the seminars, the different theoretical directions and methods are treated via different learning activities, including hands-on practical methods in statistics. The seminars are structured around practical problem solving and guided skills training, including data collection, data analysis, interpretation and dissemination of results. The video presentations used in the course show the practical procedures for common statistical analyses, from importing data to presenting results. The videos are created for SPSS and the datasets used will be made openly available for download in a usable format for students, so they can follow the procedures from import to report at their own pace.

Open for

Course assessment

Literature