One cannot think clearly about cause and effect without having a basic understanding of probabilities, populations and samples. Statistics, the analysis of the probability that two events, phenomena, or constructs are related to each other, is the bread and butter of modern social science from economics and finance to marketing and HRM. And research design – the deliberate planning for the collection and analysis of data to minimize the possibility that observations are not the result of enduring, direct and genuine relationships among the variables – is fundamental to scientific knowledge.
The four courses in this series are the basis of a scientific understanding of the world. They are the foundation of action grounded in knowledge rather than hunch, guess and assumption. Â The first three courses lead the student through increasingly complex methods of manipulating data and extracting associations among variables, correlational and causal. Â The last course links these skills to the student’s skripsi. Â The student will design his or her skripsi research project.
Probability, samples and populations, variables and descriptive statistics, R.
Measures of association, t-tests, ANOVA, and multiple regression, factor analysis, etc.
Multivariate statistics: latent variables, path analysis, PCA, QCA, etc.