- 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.

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., Richard D. De Veaux and Paul F. Velleman (2019), Business Statistics and Extra Texts, 4th ed., New York: Pearson Education International, Maastricht University Edition.

This course is in transition for the bachelor Fiscal Economics.
See the Bachelor Education and Examination Regulations for more information.

The following rule applies to bachelor Fiscal Economics students.
TRANSITIONAL REGULATION (EBS2001):
The bachelor Fiscal Economics has been discontinued.

There will be repeat education for year 1 and year 2 courses up to and including academic year 2025-2026 and exam-only up to and including academic year 2026-2027. For year 3 courses there will be repeat education up to and including 2026-2027 and exam-only up to and including academic year 2027-2028.

Whether a course is in transition, cancelled, or replaced may depend on the cohort you are in. Sometimes there are additional criteria. It is therefore very important to carefully read the EER and the addendum so you can apply the rules to your individual situation.


PREREQUISITES:
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.