Online Course – Certified Professional Specialization in Methods and Statistics in the Social Sciences from the University of Amsterdam
Learn to analyze studies and results using R. Discover how to identify sloppy science, conduct thorough research, and perform appropriate data analyses.
Interpret results correctly to make evidence-based decisions
Internship content
Research methodologies
Statistical design and analysis for research purposes in the social sciences
Final project
Applying learned skills
Developing your own research question
Data Collection
Analyzing and reporting results using statistical methods
Details of the courses that make up the specialization
Quantitative research methods
Course 1 • 29 hours • 4.7 (2,259 ratings)
Course Details
What you’ll learn
Discover the principles of sound scientific methods in the behavioral and social sciences.
Join us and learn to separate sloppy science from basic research!
This course will cover the basic principles of science, history and philosophy of science, research designs, measurement, sampling, and ethics.
The course is similar to a university-level introductory course on quantitative research methods in the social sciences, but strongly emphasizes the integrity of the research.
We will use examples from the fields of sociology, political science, educational science, communication science, and psychology.
Qualitative research methods
Course 2 • 23 hours • 4.6 (1,298 ratings)
Course Details
What you’ll learn
This course will introduce the basic ideas behind qualitative research in the social sciences.
You will learn about data collection, description, analysis, and interpretation in qualitative research.
Qualitative research often involves an iterative process.
We will focus on the components required for this process: data collection and analysis.
You won’t learn how to use qualitative methods just by watching videos.
We will delve deeper into collecting data through observations and interviews and into analyzing and interpreting the data collected in additional work.
We will discuss the most important terms in qualitative research, as well as quality criteria, good practices, ethics, writing analysis methods, and combining methods.
We would love to dispel some prejudices and recruit many students for qualitative research.
Basic statistics
Course 3 • 26 hours • 4.6 (4,453 ratings)
Course Details
What you’ll learn
Understanding statistics is essential for understanding research in the social and behavioral sciences.
In this course, you will learn the basics of statistics; not only how to calculate them, but also how to evaluate them.
This course prepared you for the next course in the specialization – “Inferential Statistics”.
In the first part of the course, we will discuss methods of descriptive statistics.
You will learn what cases and variables are and how to calculate measures of central tendency (mean, median, and mode) and dispersion (standard deviation and variance).
Next, we will discuss how to assess relationships between variables and will be introduced to the terms correlation and regression.
The second part of the course deals with the basics of probability: calculating probabilities, probability distributions, and sampling distributions.
You need to know about these things to understand how inferential statistics works.
The third part of the course includes an introduction to inferential statistical methods – methods that help us decide whether the patterns we have seen in our data are strong enough to draw conclusions about the population of interest to us.
We will discuss “confidence intervals” and “significance tests.”
Not only will you learn about all these statistical terms, but you will also practice calculating and creating these statistics yourself, using free statistical software.
Inferential statistics
Course 4 • 22 hours • 4.3 (592 ratings)
Course Details
What you’ll learn
Inferential statistics deals with drawing conclusions based on relationships found in a sample, in order to relate them to the population.
Inferential statistics help us decide, for example, whether the differences between groups we observed in our data reinforced our assumption that there are differences between groups in the population as a whole.
We will begin by considering basic principles of significance tests: the sampling distribution and statistical test, the p-value, the significance level, power, and Type I and Type II errors.
We will then examine a wide range of technical tests that help us draw conclusions for different types of data and different research designs.
For each statistical test, we will examine how it works, for which data and design it is appropriate, and how the results should be interpreted.
You will also learn how to perform these tests using free software.
For those who are already familiar with statistical tests: we will examine z-tests for 1 and 2 proportions, the McNemar test for dependent proportion relationships, t-tests for one mean (matched differences) and two means, the Chi-square test for freedom, Fisher’s exact test, simple regression (linear and exponential) and multiple regression (linear and logistic), one-way analysis of variance and factorial analysis of variance, and non-parametric tests (Wilcoxon, Kruskal-Wallis, sign test, signed rank test, runs test).
Skills you will acquire
Category: Statistics
statistics
Category: Safety margin
Safety margin
Category: Statistical hypothesis testing
Statistical hypothesis testing
Category: R Programming
R programming
Methods and Statistics in the Social Sciences – Final Research Project
Course 5 • 13 hours • 4.4 (63 ratings)
Course Details
What you’ll learn
The final project includes research that you will conduct in collaboration with other learners.
Together you will formulate a research hypothesis and design, find ways to operate, create tools for analysis and measurement, collect data, perform statistical analyses, and document the results.
During the course, you will go through the entire research process and be able to help determine what research question we will investigate and how we will structure and handle the research.
This is an invaluable experience if you want to be able to critically evaluate scientific research in the social and behavioral sciences or to design and conduct your own research in the future.
