Applied Statistics for Educational Researchers (DUH165)
This course consists of an introduction to R with a focus on latent variable modeling. We will cover confirmatory factor analysis and structural equation modeling, together with relevant psychometric theory. You will learn how to import, visualize, describe, and analyze real-world datasets, and to conduct reproducible analysis with quarto.
Course description for study year 2024-2025. Please note that changes may occur.
Course code
DUH165
Version
1
Credits (ECTS)
5
Semester tution start
Spring
Number of semesters
1
Exam semester
Spring
Language of instruction
English
Content
Learning outcome
By completion of this course, the PhD candidate will have gained the following:
Knowledge:
- of measurement theory
- a good understanding of multiple regression and factor analysis
- a good understanding of SEM
- understanding the importance of reproducible research
- deeper understanding of statistical inference
Skills:
- running latent variable models in R
- preparing results of such analyses for publication
General competences:
- being able to choose and apply the right analyses for the given data
- developing advanced strategies for further research
Required prerequisite knowledge
Recommended prerequisites
The students are expected to
- have R and RStudio already installed
- formulate a research question in their PhD project, and acquire a relevant dataset that might help answer the question
Exam
Form of assessment | Weight | Duration | Marks | Aid |
---|---|---|---|---|
Paper | 1/1 | Passed / Not Passed |
Evaluation will be based on the active participation and analyses performed in group work, presented in a brief paper.Coursework requirements: Active participation in lectures and seminars at the workshop. Self-study. The students’ workload will be approximately 150 hours of work.
Coursework requirements
Course teacher(s)
Course coordinator:
Njål FoldnesStudy Program Director:
Hein BerdinesenCourse teacher:
Ulrich DettweilerMethod of work
Overlapping courses
Course | Reduction (SP) |
---|---|
Advanced Statistics for Educational Researchers: Analyzing Structural Equation Models and Latent Growth Curves w/ MPlus (DSP165_1) | 5 |