The department OMD teaches research methodology and statistics to all **Premaster students of the Faculty BMS.**

The department OMD teaches research methodology and statistics to all Premaster students of the Faculty BMS. It is meant as a preparation for the Master education and especially for the Master thesis for which a basic knowledge of these topics is absolutely necessary. The theory is treated in the lectures and is applied (‘learning by doing’) in tutorials and SPSS in-class computer exercises. Knowledge of the theory will be assessed by tests and knowledge of SPSS by (individual) computer assignments. (The lectures in the Premaster education are given by dr. ir. H.J. Vos, whereas ir. W.M.M. Tielen gives an introduction in the statistical software package SPSS.)

Brief description of courses taught by department OMD in the Premaster.

1). Research Methodology and Descriptive Statistics (201300063; 1^{st} and 3^{rd} quartile; 5ECTS).

In this course students are introduced to the basic principles of empirical research in the social sciences. The role of research in testing theories (‘empirical cycle’) will be treated. Doing so, also some attention will be paid to science-philosophical background (especially to Popper’s critical-rationalism). The students get acquainted with some important types of research (experimental, quasi-experimental, correlational and qualitative research) and its potential threats to internal and external validity.

The following phases of conducting scientific research will be dealt with in more detail:

A) formulating research question (embedded within a relevant theoretical framework and mostly emanating from a literature study)

B) splitting up the research question into subquestions

C) formulating hypothese(s)

D) setting up a research design

E) developing measurement instruments (including reliability and validity as its two

most important quality criteria)

F) collecting data (including sampling strategy)

G) analyzing data

H) drawing conclusions and reporting results (including discussion)

In addition, attention is paid in this course to descriptive statistics. Students will get familiar with methods and techniques for representing data (both graphically and numerically). Amongst others bar charts, pie charts, stem-and-leaf displays, histograms, boxplots, contingency tables, percentile scores, means, medians, modes, standard deviations, variances, interquartile ranges, correlation coefficients and linear regression. Also, the normal distribution (including the z-transformation) will be introduced during the descriptive statistics part.

2) Inferential Statistics (201300064; 2nd and 4th quartile; 5ECTS).

This course introduces inferential statistics (i.e., hypotheses tests and constructing confidence intervals). Basic concepts from inferential statistics are discussed on the basis of conclusions concerning an average with a known population standard deviation (i.e., *z*-test). Additionally, several popularly used statistical tests are treated: *t*-tests (both independent and dependent), binomial tests (both for a single proportion and two proportions), and chi-square tests. Also several popularly used (more advanced) statistical techniques are addressed: simple linear regression, multiple linear regression, one-way and two-way analysis of variance (one-way ANOVA and two-way ANOVA), and nonparametric tests. During the in-class computer exercises, students are taught analyzing small and greater data files using the IBM SPSS statistical program.