Course - Quantitative Research Methods - AM521817
Quantitative Research Methods
Choose study yearAssessments and mandatory activities may be changed until September 20th.
About
About the course
Course content
Description:
This course provides an overview of the key concepts, techniques, and applications required to leverage data for answering research questions and supporting decision-making. It explores the philosophy of scientific theory while focusing on how data can be used to test hypotheses, identify patterns, and make predictions. The course builds on the tools and techniques used by statistical learning, placing particular emphasis on predictive modeling, classification, and regression.
Topics:
- Scientific theory, the research process and planning
- Data preparation and exploration
- Linear regression and classification
- Resampling methods
- Model selection
- Non-linear models
- Tree-based methods
- Unsupervised learning
Learning outcome
Learning objectives
- to describe fundamental philosophy and data science concepts, including data collection, cleaning, and preprocessing, as well as the principles of statistical analysis and statistical learning.
- to apply appropriate data science techniques in analyzing business data sets, for deriving insights that inform strategic decisions in international business and sustainability challenges.
- to critically analyze challenges in international business by using statistical learning models to identify patterns, trends, and anomalies, and assess the potential impact of these findings.
- evaluate the effectiveness of data-driven strategies and models, assessing their impact on business performance and making recommendations for improvement.
- to work with diverse perspective when creating comprehensive reports and visualizations that highlight business solutions;
- to communicate findings effectively.
Learning methods and activities
Lectures, discussions in groups and in plenary.
Compulsory assignments
- Statistic exercises
Further on evaluation
Assessment:
Continuous during the semester: 50% of the final grade - a group project based on three assignments completed throughout the semester. All group members will present the project results. Specific details about the assignments' content and deadlines will be provided in the course Syllabus.
Final school exam: 50% of the final grade - 3 hours - written individual exam.
Students will have to pass both the project and the written school exam in order to complete the course. The project will to be handed in via Inspera at specified date which will be announced later in the semester.
Re-sit examination: A re-sit on the school exam part will be held the following semester. If a student fails the project but pass the written exam, the student must retake both examination parts in the next ordinary examination period. In case a student wants to improve the grade in the course, one must retake the whole course.
Specific conditions
Admission to a programme of study is required:
International Business and Marketing (860MIB)
Management of Innovation and Sustainable Business Development (MSMI)
Recommended previous knowledge
As for the study programme.
Required previous knowledge
As for the study programme.
Course materials
To be announced at the start of the term.
Subject areas
- Economics and Administration