Quantitative Research Methods

Description:

This course teaches you how to use data to answer real business questions and make better decisions in international settings. You will learn practical tools for predicting trends, classifying information, and running regressions to solve everyday business problems—like understanding markets or making forecasts. The course shows how data can drive smarter strategies, innovation, and competitiveness across the world. As a core course in the program, it helps you build the skills needed to work effectively in today’s data‑driven global business environment.

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 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.

Lectures, discussions in groups and in plenary.