Methods and Statistics in Social Sciences Specialization

Starts May 08

Methods and Statistics in Social Sciences Specialization

Critically Analyze Research and Results Using R

Learn to recognize sloppy science, perform solid research and do appropriate data analysis.

About This Specialization

Identify interesting questions, analyze data sets, and correctly interpret results to make solid, evidence-based decisions. This Specialization covers research methods, design and statistical analysis for social science research questions. In the final Capstone Project, you’ll apply the skills you learned by developing your own research question, gathering data, and analyzing and reporting on the results using statistical methods.

Created by:

courses
5 courses

Follow the suggested order or choose your own.

projects
Projects

Designed to help you practice and apply the skills you learn.

certificates
Certificates

Highlight your new skills on your resume or LinkedIn.

Courses
Beginner Specialization.
No prior experience required.
  1. COURSE 1

    Quantitative Methods

    Upcoming session: May 8 — Jul 10.
    Commitment
    8 weeks, 4-5 hours/week
    Subtitles
    English, Chinese (Simplified)

    About the Course

    Discover the principles of solid scientific methods in the behavioral and social sciences. Join us and learn to separate sloppy science from solid research! 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.
  2. COURSE 2

    Qualitative Research Methods

    Upcoming session: May 8 — Jul 10.
    Commitment
    8 weeks of study, 4-6 hours/week
    Subtitles
    English

    About the Course

    In this course you will be introduced to the basic ideas behind the qualitative research in social science. 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 ingredients required for this process: data collection and analysis. You won't learn how to use qualitative methods by just watching video's, so we put much stress on collecting data through observation and interviewing and on analysing and interpreting the collected data in other assignments. 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. We hope to take away some prejudice, and enthuse many students for qualitative research.
  3. COURSE 3

    Basic Statistics

    Upcoming session: May 22 — Jul 24.
    Commitment
    8 weeks of study, week 1: 3-6 hours; week 2-8: 1-3 hours/week.
    Subtitles
    English

    About the Course

    Understanding statistics is essential to understand research in the social and behavioral sciences. In this course you will learn the basics of statistics; not just how to calculate them, but also how to evaluate them. This course will also prepare you for the next course in the specialization - the course 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 you can compute measures of central tendency (mean, median and mode) and dispersion (standard deviation and variance). Next, we discuss how to assess relationships between variables, and we introduce the concepts correlation and regression. 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. The third part of the course consists of an introduction to methods of inferential statistics - methods that help us decide whether the patterns we see in our data are strong enough to draw conclusions about the underlying population we are interested in. We will discuss confidence intervals and significance tests. You will not only learn about all these statistical concepts, you will also be trained to calculate and generate these statistics yourself using freely available statistical software.
  4. COURSE 4

    Inferential Statistics

    Current session: Apr 24 — Jun 19.
    Commitment
    7 weeks of study, 1-3 hours/week
    Subtitles
    English

    About the Course

    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: the sampling and test statistic distribution, 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 and exponential) and multiple regression (linear and logistic), one way and factorial analysis of variance, and non-parametric tests (Wilcoxon, Kruskal-Wallis, sign test, signed-rank test, runs test).
  5. COURSE 5

    Methods and Statistics in Social Science - Final Research Project

    Upcoming session: Jul 3 — Sep 4.
    Commitment
    6 weeks of project work; week 1-3: 3-5 hours / week; week 4-6: 4 - 8 hours / week
    Subtitles
    English

    About the Capstone Project

    The Final Research Project consists of a research study that you will perform in collaboration with fellow learners. Together you will formulate a research hypothesis and design, come up with operationalizations, create manipulation and measurement instruments, collect data, perform statistical analyses and document the results. In this course you will go through the entire research process and will be able to help determine what research question we will investigate and how we design and perform 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 design and perform your own studies in the future.

Creators

  • University of Amsterdam

    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.

  • Emiel van Loon

    Emiel van Loon

    Assistant Professor
  • Gerben Moerman

    Gerben Moerman

    Dr.
  • Annemarie Zand Scholten

    Annemarie Zand Scholten

    Assistant Professor
  • Matthijs Rooduijn

    Matthijs Rooduijn

    Dr.

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