Learn to recognize the opportunities to apply basic tools from mathematics and inferential statistics in business.
Learn to implement statistical tools using the statistical software package SPSS, and to correctly interpret the results.

This course is devoted to refreshing, extending, and actively applying the mathematical and statistical tools introduced in the first-year quantitative methods courses.

In the mathematics part, we study three applications of mathematical tools to business economics: decision theory, portfolio theory, and game theory. Each application consists of two case studies. The purpose is to get acquainted with basic quantitative business models.

In the statistics part, we review and extend first-year inferential tools, including t-tests (one-sample, independent, and paired), one-way ANOVA, chi-square tests, and regression analysis. We also introduce new techniques, such as non-parametric tests, logistic regression, and factor analysis. Students apply these methods to real-world business problems in marketing and finance through case studies. All empirical analyses are conducted using R Markdown in RStudio.

* Sharpe, Norean R., Richard D. De Veaux and Paul F. Velleman (2019), Business Statistics and Extra Texts, 4th ed., New York: Pearson Education International, Maastricht University Edition.
* QM1 and QM2 mathematics readers, to be downloaded on the corresponding course pages

Intermediate knowledge of mathematics and statistics, comparable to the course Quantitative Methods II, code EBC1033/1034/1035.