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Contents

The course provides knowledge and skills in scientific data analysis relevant to the fields of psychology and cognitive science. The main aim is to prepare students for independent research by developing their ability to select, apply, interpret, and critically evaluate both quantitative and qualitative methods. 

The quantitative part of the course introduces central concepts in descriptive and inferential statistics where inferential statistics are in focus, with examples of commonly used techniques for analyzing relationships and differences between variables. Students are also introduced to key practices in data preparation, assumption testing, and interpretation and reporting of results according to scientific standards. Selected topics related to the evaluation of psychological measurements are included. 

The qualitative part of the course covers fundamental approaches to the analysis of data. Students practice techniques for coding, identifying patterns, and interpreting qualitative material, while considering quality criteria such as credibility, transparency, and reflexivity. 

The course emphasizes an active learning model where students engage in problem-solving, analysis, and critical discussion, both individually and in groups. Teaching activities such as lectures, supervised exercises, and seminars support the development of methodological understanding and analytical skills. Supervision is offered throughout the course to guide students in their work. 

Expected learning outcomes

After completed course the student should be able to show:

Knowledge and understanding

• Demonstrate knowledge of key quantitative methods used for analyzing relationships, differences, and effects in psychological and cognitive science data.
• Demonstrate knowledge of core qualitative approaches for analyzing and interpreting textual or other non-numeric data.
• Explain central concepts related to data characteristics, methodological assumptions, and the evaluation of analytical results. 

Skills and ability

• Apply suitable quantitative analysis techniques using statistical software to address research questions in psychology and cognitive science.
• Interpret and report results from statistical analyses, demonstrating an understanding of methodological considerations.
• Conduct qualitative analyses of textual or other non-numeric data, applying relevant approaches for identifying patterns and interpreting meaning.
• Critically assess the applicability, strengths, and limitations of different analytical strategies in relation to specific research contexts. 
• Demonstrate the ability to communicate in English within the scientific field the course pertains to.

Evaluation ability and approach

• Assess and motivate methodological choices in data analysis based on scientific, and contextual considerations.
• Reflect on the interpretation and relevance of analytical findings in relation to research aims and practical implications.
• Demonstrate a critical and transparent approach to the analysis, interpretation, and reporting of research data. 
• Discuss the rationale for choosing appropriate analytical methods in relation to research questions, study design, and data type.

Required Knowledge

90 credits (Higher Education Credits/ hp) in any subject. Research design and data collection 7,5 credits or equivalent

Proficiency in English equivalent to Swedish Upper Secondary course English A/6.
Where the language of instruction is Swedish, applicants must prove proficiency in Swedish to the level required for basic eligibility for higher studies.

Form of instruction

The course integrates applied components where students formulate research questions, use appropriate analytical strategies, and critically interpret results. Particular emphasis is placed on preparation for the degree project and the ability to evaluate and produce methodologically sound research

The course is based on an active and student-centered learning approach.

Quantitative module:
Teaching in the quantitative part consists of lectures, seminars, and supervised computer lab sessions. Students work individually with statistical software to conduct analyses, including data preparation, assumption testing, and interpretation of outputs. Assignments involve applying analytical methods to example datasets, working with case studies, and reporting results following scientific conventions. Instruction emphasizes analytical reasoning and the connection between research design and the choice of statistical methods. Several seminars and practical sessions are mandatory due to their applied nature.

Qualitative module:
The qualitative part is taught through lectures and workshops. Students practice key approaches to qualitative data analysis, focusing on analytic thinking, conceptual understanding, and reflective interpretation of textual data. All assignments are completed individually. Supervision is provided throughout the course to support students in methodological choices, analytical strategies, and the evaluation of the quality and trustworthiness of qualitative analyses.

The right to receive teaching, including supervision, is valid only during the period of the course instance for which the student is registered. 

Examination modes

Examination is conducted individually through a combination of written and practical assessments.

Students are assessed through the following components:

• A digital exam assessing basic statistical knowledge and application skills (U-G).
• A digital individual exam focusing on application and interpretation of statistical knowledge (U-VG).
• An individual written assignment on qualitative data analysis and interpretation (U-VG).
• Workshop assignments where students use statistical software to solve analytical problems (U-VG).

The occurrence of examination and mandatory assignments are specified in the schedule. Grades for the course and/or its respective examinations are made when all examinations and mandatory assignments have been successfully completed.

Final course grade: To achieve a final grade of Pass (G) for the course, the student must achieve at least Pass (G) on all components.To achieve a final grade of Pass with Distinction (VG), the student must achieve at least Pass (G) on all components and Pass with Distinction (VG) on more than 50% of the components.

Students are entitled to 5 examinations. For students who have not passed the regular examination, additional examination opportunities will be arranged in accordance with the University's Regulations for Grading and Examination, FS 1.1-574-22. A student who has failed an examination twice for a course or part of a course has the right to request a different examiner, unless there are specific reasons against it (HF Chapter 6, Section 22). Requests for a new examiner should be addressed to the Head of the Department of Psychology. Students have the right to be examined under the same syllabus as the original examination at least twice within two years after their initial registration. 

The provisions of the Discrimination Act (2008:567) include requirements for universities to offer the possibility of adapted examinations or alternative forms of examination. Deviations from the syllabus's examination form may be made for a student with a decision for pedagogical support due to a disability. 

The examiner may decide on deviations from the syllabus's examination form. Individual adjustments to the examination form must be considered based on the student's needs. The examination form is adapted within the framework of the course's expected learning outcomes. A student requiring an adapted examination must request the adjustment from the responsible department no later than 10 days before the examination. The examiner decides on the adapted examination, and this decision is communicated to the student. 

Other regulations

This course, 2PS243, replaces the course 2PS103 and cannot be included in the same degree.