Course 1: Quantitative Methods
This course will cover the fundamental principles of science, some history and philosophy of science, research designs, measurement, sampling and ethics. The course is comparable to a university level introductory course on quantitative research methods in the social sciences, but has a strong focus on research integrity. We will use examples from sociology, political sciences, educational sciences, communication sciences and psychology.
Course 2: Qualitative Research Methods
Obviously, the most important concepts in qualitative research will be discussed, just as we will discuss quality criteria, good practices, ethics, writing some methods of analysis, and mixing methods.
To read more about course 2, click here!
Understanding statistics is essential to understand research in the social and behavioral sciences. In almost all research studies, statistics are necessary to decide whether the results support the research hypothesis. In this course you will learn the basics of descriptive statistics; not just how to calculate them, but also how to evaluate them. An important part of the material treated in this course will prepare you for the next course in the specialization, namely the course Inferential Statistics.
We will start with the concepts variable and data, the difference between population and sample and types of data. Then we will consider the most important measures for centrality (mean, median and mode) and spread (standard deviation and variance). These will be followed by the concepts contingency, correlation and regression. All these statistics make it possible to represent large amounts of data in a clear way, enabling us to spot interesting patterns.
The second part of the course is concerned with the basics of probability: calculating probabilities, probability distributions and sampling distributions. You need to know about these things in order to understand how inferential statistics work. We will end the course with a short preview of inferential statistics – statistics that help us decide whether the differences between groups or correlations between variables that we see in our data are strong enough to conclude that our predictions were confirmed and our hypothesis is supported.
You will not only learn about all these concepts, you will also be trained to calculate and generate these statistics yourself using freely available statistical software.
Course 4: Inferential Statistics
Inferential statistics are concerned with making inferences based on relations found in the sample, to relations in the population. Inferential statistics help us decide, for example, whether the differences between groups that we see in our data are strong enough to provide support for our hypothesis that group differences exist in general, in the entire population.
We will start by considering the basic principles of significance testing: probability distributions, p-value, significance level, power and type I and type II errors. Then we will consider a large number of statistical tests and techniques that help us make inferences for different types of data and different types of research designs. For each individual statistical test we will consider how it works, for what data and design it is appropriate and how results should be interpreted. You will also learn how to perform these tests using freely available software.
For those who are already familiar with statistical testing: We will look at z-tests for 1 and 2 proportions, McNemar’s test for dependent proportions, t-tests for 1 mean (paired differences) and 2 means, the Chi-square test for independence, Fisher’s exact test, simple regression (linear, exponential en logistic) and multiple regression, one way and multi-way analysis of variance, and non-parametric tests (Wilcoxon, Kruskal-Wallis, sign test, signed-rank test).
Course 5 – Social Science Final Research Project
The capstone consists of a research project that you will perform in collaboration with fellow students. You will formulate a research hypothesis and design and collect data or work with a secondary data set provided by one of our external partners (TBA). You will document and analyze the data and write a research report. Depending on the topic you choose, the project may involve developing your own questionnaire and collecting your own data or contributing to a research project running at the University of Amsterdam or one of our external partners.
To read more about course 5, click here!
The University of Amsterdam traces it roots back to 1632, and is one of the largest comprehensive universities in Europe.
A modern university with a rich history, the University of Amsterdam (UvA) traces its roots back to 1632, when the Golden Age school Athenaeum Illustre was established to train students in trade and philosophy. Today, with more than 30,000 students, 5,000 staff and 285 study programmes (Bachelor’s and Master’s), many of which are taught in English, and a budget of more than 600 million euros, it is one of the largest comprehensive universities in Europe. It is a member of the League of European Research Universities and also maintains intensive contact with other leading research universities around the world.