Social Sciences Specialization
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.
Shareable Certificate
• Earn a Certificate upon completion
100% online courses
• Start instantly and learn at your own schedule.
Flexible Schedule
• Set and maintain flexible deadlines.
Beginner Level
• No prior experience required.
Approximately 10 months to complete
• Suggested pace of 3 hours/week
English
• Subtitles: English, Arabic, French, Portuguese (European), Chinese (Simplified), Italian, Vietnamese, German, Russian, Spanish
How the Specialization Works
Take Courses
A Coursera Specialization is a series of courses that helps you master a skill. To begin, enroll in the Specialization directly, or review its courses and choose the one you'd like to start with. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. It’s okay to complete just one course — you can pause your learning or end your subscription at any time. Visit your learner dashboard to track your course enrollments and your progress.
Hands-on Project
Every Specialization includes a hands-on project. You'll need to successfully finish the project(s) to complete the Specialization and earn your certificate. If the Specialization includes a separate course for the hands-on project, you'll need to finish each of the other courses before you can start it.
Earn a Certificate
When you finish every course and complete the hands-on project, you'll earn a Certificate that you can share with prospective employers and your professional network.
There are 5 Courses in this Specialization
Course 1 - Quantitative Methods
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.
Course 2 - Qualitative Research Methods
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.
Course 3 - Basic Statistics
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.
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: 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).
Course 5 - Methods and Statistics in Social Science - Final Research 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.
Offered by University of Amsterdam
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 39,000 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.
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