Quantitative Business Research

About the course

Subjects

Statistics Quantitative methods

Course content

The course introduces you to basic quantitative business analysis and statistics. By emphasizing homework exercises with concrete examples of statistical analysis, general concepts and methodological issues, the pedagogy of the course is designed to make you an educated user of quantitative methods rather than a statistician. Topics include: data representation and summary measures; exploratory data analysis, data collection and basic research design; probability theory and distributions, sampling distributions, confidence intervals, significance tests, contingency tables and Bayesian inference, analysis of proportions, single and multivariate regression analysis, analysis of variance, and problems with false positives in academic research. Examples will be drawn from sustainability, business economics, and cultural and political analysis.

See course description in course catalogue

What you will learn

Identify different types of quantitative data and explain basic methods of quantitative data collection and experimental design.
Use and critically evaluate the use of graphics, tables, and summary measures to illustrate relationships in data, appropriate for the purpose at hand.
Use elementary theory of probability and distributions to calculate sample distributions and the probabilities of alternative outcomes and make basic statistical inferences (tests) about population characteristics from samples.
Use and interpret the output of methods to statistically analyze associations in data, such as contingency tables, single and multiple regression, and analysis of variance, and recognize common problems and limitations in such methods.
When faced with a specific research question and available data, select one or more appropriate statistical methods to address the question, develop a structured and disciplined approach to statistical analysis critically evaluate the results
Account for some inherent pitfalls and limitations in statistical analysis as it is done in practice and suggest ways such problems may be mitigated.

Facts

Level

Bachelor

Type

Mandatory course – also offered as elective

ECTS

7.5

Code

BBLCU1226U

Teaching periods

Spring – semester

Academic year

2024/2025

Status

Available places

Teaching language

English

Teaching Format

Hybrid

Exams

Written exam on campus
Individual exam, summer

Assessment type

7 point grading scale