FOR054F Multivariate statistical methods 7,5 credits

COURSE SYLLABUS

Multivariate statistical methods, 7,5 credits, FOR054F

Course name: Multivariate statistical methods in research focusing on humans and organizations

ECTS/HP: 7.5 hp

Course code: FOR054F

Education level: Third-cycle course

Eligibility requirements: The course is open for students admitted to third-cycle studies at LTU.

Entry requirements:

General entry requirements for the doctoral level. Admitted to doctoral studies at LTU. Recommended prior knowledge is familiarity with the following statistical concepts: Sample mean, sample variance, sample standard deviation, box-plot, probability distribution, population mean, population variance, population standard deviation, the normal distribution, the t-distribution, confidence interval, hypothesis testing, simple regression analysis.

Course content:

• Introduction to the field – including a review of basic statistics
• Conceptual and practical understanding of some key multivariate methods
• Practical application of software to perform statistical analyses
• Practical application within one’s own research area

Learning outcomes:

After completed course the student will be able to:

1. Relate to the theoretical basis for quantitative research methodology and measurement validity
2. Describe and apply the most common statistical multivariate methods used in social and health sciences
3. Justify and argue for specific method selection and interpretation of analyses for given problems

With the aim of preparing for addressing complex relationships between variables in quantitative social and health sciences research.

The learning outcomes address the following outcomes in the Higher Education Ordinance, Annex 2:

• demonstrate familiarity with research methodology in general and the methods of the specific field of research in particular.
• demonstrate the capacity for scholarly analysis and synthesis as well as review and assess new and complex phenomena, issues and situations autonomously and critically

• demonstrate the skills in both national and international contexts to present and discuss research and research findings authoritatively in speech and writing and in dialogue with the academic community and society in general
• demonstrate specialized insight into the possibilities and limitations of research, its role in society and the responsibility of the individual for how it is used.

Course methods:

The course will start with a repetition task. Students’ learning is based on course literature, specific study tasks and exercises, seminar discussions and presentations, as well as statistical labs. This is supported by introductory lessons and recorded material. There will be seven scheduled occasions. Access to a laptop computer and the software IBM SPSS Statistics is necessary. Details will be presented in a study guide provided on admission to the course.

Examination form:

The course will be examined through participation in seminars (outcomes 1, 3 and 4), oral and written presentations and assignments (outcomes 2 and 3) and a final take home exam (outcome 2 and 3).

Grading scale: Pass/Fail

Course literature:

• Hair, Black, Babin and Anderson (2018). Multivariate Data Analysis: 8th Edition. Cengage Learning EMEA, ISBN: 9781473756540
• Pallant, Julie (2016), SPSS Survival Manual (6th ed.) McGraw Hill. ISBN: 9780335261543
• A selection of articles and recorded material will be available.

Education cycle: Lp 3, 2026

Course is given periodically: Yes, next 2028

Send application to: The application is made via the form below

• Application to FOR054F starting spring 2026

In the application, the doctoral student states: name, social security number, email address, division and department affiliation

Deadline for application: Dec 15, 2025.

Course open for application by doctoral students admitted to other universities than LTU:
No

Limited number of students: No

Tuition:

If the course is allocated resources via internal resource allocation system, the course is free of charge for doctoral students admitted at LTU.

Contact person: Mats Westerberg, mats.westerberg@ltu.se, 0920-491808

Examiner: Professor Mats Westerberg, mats.westerberg@ltu.se.

Course syllabus decided by: Helena Ranängen

Date of decision: 2025-10-13