MØLBA3007 Advanced statistical modelling
- Course codeMØLBA3007
- Number of credits7,5
- Teaching semester2024 Autumn
- Language of instructionEnglish
- CampusLillehammer
- Required prerequisite knowledge
LMØS120 Management Accounting and Control and LMSM130 Quantitative Methods.
- Multiple regression: linear- and non-linear regression
- Endogeneity issues and methods
- Models for limited dependent variables
- Models based on panel data
- Partial least squares Structural Equation Modelling (PlsSEM)
Learning Outcome
Upon passing the course, students have achieved the following learning outcomes:
The student
- has specialized knowledge about endogenous regressors, models with limited dependent variables, statistical models for panel data and how to model a set of equations with observed and unobserved variables (k1)
- has advanced knowledge of the underlying assumptions of the selected statistical models covered in the course (k2)
- can review and critically assess selected research problems in social sciences where application of advanced statistical methods is required (k3)
- can interpret and explain research results based on the use of advanced statistical models (k4)
The student can
- test and critically assess the reliability and validity of complex surveys (f1)
- justify the choice of methodology based on critical reflection about model properties and the underlying assumptions (f2)
- plan, design, and conduct advanced empirical studies (f3)
- analyse data from a range of sources within business, economics, and finance using advanced statistical techniques (f4)
- demonstrate professional reporting skills on the topics covered in the course through both oral presentations and written reports (f5)
The student can
- complete a research project built on the use of advanced statistical models (g1)
- debate findings from research using advanced statistical models with peers (g2)
- Mandatory homework assignments must be handed in before each teaching module (a total of 4). These will be combinations of practical and theoretical exercises covering key topics in the course.
- Three out of four homework assignments must be passed to be allowed to take the exam.
- Attendance on at least 50 % of the courses lectured teaching.
- Oral presentation of the final written academic report (see below).
| Form of assessment | Grading scale | Grouping | Duration of assessment | Support materials | Proportion | Comment |
|---|---|---|---|---|---|---|
Written assignment | ECTS - A-F | Group (2 - 2) | Semester(s) |
| 100 |
Group semester project (two students per group). The students shall plan, prepare, and execute a research project using selected techniques covered in the course. The data collected shall be analysed and reported in a final written academic report.
Reading list
No reading list available for this course