- Learn to recognize the opportunities to apply basic tools from inferential statistics in practical business situations.
- Learn to implement these tools correctly, using the statistical software package SPSS.
- Learn to interpret the results of such analyses correctly, and understand their limitations.

PLEASE NOTE THAT THE INFORMATION ABOUT THE TEACHING AND ASSESSMENT METHOD(S) USED IN THIS COURSE IS WITH RESERVATION. A RE-EMERGENCE OF THE CORONAVIRUS AND NEW COUNTERMEASURES BY THE DUTCH GOVERNMENT MIGHT FORCE COORDINATORS TO CHANGE THE TEACHING AND ASSESSMENT METHODS USED. THE MOST UP-TO-DATE INFORMATION ABOUT THE TEACHING/ASSESSMENT METHOD(S) WILL BE AVAILABLE IN THE COURSE SYLLABUS.

This skills training is devoted to refreshing and actively applying the basic inferential tools introduced in the statistics part of typical first year quantitative methods courses: a.o. the one-sample t-test, the independent-samples t-test, the paired-sample t-test, one-way-ANOVA, the chi-square test and regression analysis. Six case studies using real-life datasets that reflect business problems from a.o. marketing and finance are examined extensively. The empirical analyses are performed with SPSS, a statistical software package widely used in professional practice.

Sharpe, Norean R., De Veaux, Richard D., and Paul F. Velleman (2017), Business Statistics and Extra Texts, 3rd. Intern. Ed., New York: Pearson Education International.

Basic principles from inferential statistics as discussed in typical first-year Quantitative Methods courses such as QM1 (code EBC 1005/1006/1007) and QM2 (code EBC 1033/1034/1035): basic probability theory, population versus sample, sampling distribution, point estimation, confidence intervals, type I error, regression analysis.

Exchange students must have attended courses similar to QM1 and QM2 at their home university. If not, successful completion of QM3 is impossible.