Experimental Methods in Business Research

Information

The course is built on three pillars: Testing research ideas with clean and rigorous experimental designs, mastering the statistical techniques necessary to analyse these designs (using SPSS), and writing a research report about it that conforms to journal standards. Topics include: causal inference, experimental designs (factorial designs, within- vs. between-subject designs, mixed designs), validity of designs (internal, external, statistical, construct), experimental caveats (demand characteristics, confounds, experimenter expectancy, checks, measurement order, control variables), Ordinary Least Square models (ANOVA, linear regression, simple effects, simple slopes, contrasts, statistical assumptions, use of SPSS), statistical issues in experiments (non-parametric data, random factors, outliers, violated assumptions, statistical power), mediation (moderated mediation, mediated moderation, PROCESS), scientific integrity (researcher degrees of freedom, questionable research practices, transparency, p-hacking) and the review process (how to write, review experiments, respond to reviewers, and publish).
We will examine these topics from the perspective of an applied behavioural researcher (with examples from fields such as marketing, organizational behaviour, economics, and psychology). Our focus is thus very practical—to help you overcome any issues that might arise in designing and conducting your experiment, analysing your data, writing up your results, and getting your paper published.