To obtain a degree in Social Science (Bachelor of Arts) your curriculum must satisfy a number of criteria. One of these criteria is that students must take two courses in Methods and Statistics.

Methods and statistics classes form an integral part of the curriculum for all social science students. Not only are the students introduced to various statistical analysis techniques, but they also learn about the scientific method, the research cycle, sampling, ethical principles, measurement tools, and various data collection techniques, such as experiments, surveys, open interviews, etc.

If students wish to enter a research master after the completion of their bachelor’s degree, a minor in Methods and Statistics will be beneficial (and sometimes even required). UCU social science students have the opportunity to do a minor in Methods and Statistics.

100-level course

UCACCMET12: Research in Practice – Methods and Statistics for the Social Scientist
This course gives a general introduction to research Methodology and Statistics for the Social Sciences. The methodology introduction includes the logic and design of social research and some specific techniques. The introduction to statistics includes descriptive statistics, covering graphs, measures of central tendency and variation, distributions, and measures of association. It also includes inferential statistics, such as t-tests, Chi-square tests, correlation, and regression.

200-level courses

UCACCMET22: Methods and Statistics II (Applied Multivariate Statistics)
The summer course is equivalent to UCACCMET23 (see below). It satisfies all the same requirements as the fall and spring classes. However, the content of the course is predetermined.

UCACCMET23: Methods and Statistics II (Applied Multivariate Statistics)
This course covers the theory and application of multivariate statistical models. The techniques that are dealt with include multiple regression analysis, ANOVA, factorial ANOVA, ANCOVA, repeated measures analysis, and MANOVA. These models can be used to investigate the relations among many variables simultaneously.

As part of this course, students must elect one of the following modules:

  • UCACCMET2A: Analysis of Behavioral Data
    This module is recommended for students with an interest in different areas of psychology and cognitive sciences and focuses mainly on factor analysis and reliability analysis.
  • UCACCMET2B: Analysis of Societal Data
    This module is recommended for students with an interest in sociology, economics, geography, criminology, empirical political sciences, social psychology and focuses mainly on logistic regression analysis.
  • UCACCMET2C: Analysis of Econometric Data
    This module focuses on the analysis of time series based on economic data. However, trend analysis is used in many other fields of research, i.e. climate change, evolution, age/generation related research. This module is recommended for students with an interest in economics, especially econometrics, but may be interesting for students in many other fields.
  • UCACCMET2D: Qualitative Research Techniques
    This module is recommended for students with an interest in non-quantitative data, as often used in for instance anthropology.

Usually we offer modules B en D in the Fall and modules A and C in the Spring. This may, however, change in the future!

The summer course (UCACCMET22) is equivalent to the Fall and Spring classes. It satisfies all the same requirements as the fall and spring classes. However, the content of the course is predetermined.

Prerequisites: Introduction to Methods and Statistics I

For all UCU courses students must earn a C- or better in the prerequisite courses. To qualify for admission to Methods and Statistics II, students must satisfy the following additional requirements:

  • at least a D- on the SPSS proficiency test
  • at least a D+ average on the two theory tests (that is, an F on one test must be compensated by a grade of B- or higher on the other test, etc.)

Students who do not satisfy one or more of the above requirements can qualify by taking and passing, as an entrance exam, the second theory test of Methods and Statistics I, offered in the final week of fall and spring semesters and at the end of the summer break. Students who do self-study of the material (for example, students who did a statistics course somewhere else, or science majors who have studied the material on their own) may also sit the qualifying test at these times.

Students who have received an F on the SPSS proficiency test will be asked to re-take this test, offered in the second to last week of every semester or at the end of summer break.

For questions about requirements or to register for tests contact Dr. Kirsten Namesnik. See the UCU calendar for upcoming testing dates.

UCACCMET24: Qualitative Inquiry in Everyday Life
The purpose of this course is to equip students to critically design, conduct, report, read, and evaluate qualitative research projects and methodologies, e.g., ethnography, grounded theory, and discourse analysis. The course has the dual aim of equipping students with conceptual understandings of different methods and the practical skills to put those methods into practice. It covers the classic sources of qualitative data, such as interviews, focus groups, and participant observation, and deals with modern sources of data, such as visual materials, internet, and social media. It also discusses data analysis methods, in particular, thematic analysis and the integrative procedures that support qualitative data-analysis. The course will train students in understanding the life cycle of a qualitative research project, from design to data collection, analysis, reporting and dissemination.

300-level courses

UCACCMET31: Methods and Statistics III (Structural Equation Modeling: The Analysis of "Causal" Models)
This course is aimed at students in social, behavioral, and economic sciences who plan to go into research. Theories in social, behavioral, and economic science are becoming more complex as modern research produces data that requires sophisticated analysis methods. As a result, social scientists use increasingly complex statistical modeling to test their theories. Modern modeling software avoids difficult mathematical equations. The emergence of these powerful and easy-to-use modeling tools makes it important for students to understand both the possibilities and limitations of such techniques.

Prerequisites: At least one of the following courses must be completed with a passing grade: UCACCMET22 or UCACCMET23.

UCU social science students have the opportunity to do a minor in Methods & Statistics. If UCU students wish to enter a research master after the completion of their bachelor’s degree, a minor Methods and Statistics will be beneficial (and sometimes even required).

Requirements

The Methods & Statistics minor consists of 4 courses. Three of these courses are required courses:

  • Methods & Statistics I (UCACCMET12)
  • Methods & Statistics II (UCACCMET23 or UCACCMET22)
  • Methods & Statistics III (UCACCMET31)

Note: Theory construction & statistical modeling (200300125: taught in English in the first quarter through the department of Methods and Statistics at the UU) may be used as a substitute for Methods & Statistics III.

The fourth course can be selected from the list below:

  • Qualitative Inquiry in Everyday Life (UCACCMET24)
  • Psychology Lab Course (UCSSCPSY25)
  • Mathematical Methods (UCSCIMAT21)
  • Basic Mathematics: Calculus (UCSCIMAT11)  (can only be used if Methods & Statistics minor is being used as preparation for research master)
  • Mathematical Modeling: Networks (UCSCIMAT22)
  • A combination of two (2) additional modules of the Methods and Statistics II sequence (UCACCMET2A/ 2B/ 2C/ 2D) in combination with the Intro to Probability and Statistics lab (UCSCIMATL4)
  • Conducting a survey (200500126: taught in English in the second quarter through the department of Methods and Statistics at the UU)
  • Doing a qualitative research project (2010000129: taught in English in the third quarter through the department of Methods and Statistics at the UU)

Note: The module UCACCMET2D cannot be taken in combination with UCACCMET24.

If you wish to use a different (off-campus) course as the fourth course in the M&S minor, you can file forms ‘minor proposal’ and ‘off-campus course’ with the exam board. The course must be either:

  • another methods and/or statistics course; or
  • a higher level mathematics course; or
  • a course containing extended training in applying statistics in empirical studies.

Note: The course UCSCIMAT01 does not fulfill these requirements!

Methods & Statistics Fall Spring Summer Prerequisites
UCACCMET12 Research in Practice 2 2   None
UCACCMET22 Applied Multivariate Statistics     1 UCACCMET12
UCACCMET23 Applied Multivariate Statistics 1 2   UCACCMET12
UCACCMET24 Qualitative Inquiry in Everyday Life 1 0   None
UCACCMET31 Structural Equation Modeling: The Analysis of "Causal" Models 0 1   UCACCMET22 or
UCACCMET23

The PhD work of dr. Emmeke Aarts at the VU University Amsterdam focused on improving statistical methods to optimize inference from complex neuroscience data. She has been working at the Department of Methods and Statistics as an assistant professor since September 2016. Her fields of expertise include the analysis of longitudinal / long sequences of data, data science, hierarchical data, and Bayesian estimation methods.

Dr. Lakshmi Balachandran Nair received her Ph.D. in Communication Sciences (specializing inQualitative Research Methodology) from Università della Svizzera Italiana. She currently serves as an Assistant Professor in the Department of Methodology and Statistics at UU. Her areas of expertise include general qualitative research, grounded theory, case study research, qualitative content analysis, and qualitative research synthesis with a special focus on methodological innovation, deviant case analysis, rigor, and transparency. Outside methodology, her work includes case studies on strategic innovation and general management.

Dr. Dave Hesse received his MA, his Ph.D., and his Post-Doctoral training in psychological methods and psychometrics at the University of Amsterdam. He has been working at the Department of Methods and Statistics at the UU since November 2005. His expertise includes multivariate statistics, structural equation modeling, psychometrics, and categorical data analysis.

Dr. Guus de Krom received a Ph.D. in speech acoustics and perception from the University in Leiden. He has been at UCU since 2001. He currently serves on the UCU Exam Board. He was appointed as Fellow of Methods and Skills Teaching in 2015. His areas of expertise include general methods and statistics, quality control, and coaching.

Dr. Kirsten Namesnik received a double BS in mathematics and statistics from the University of Michigan. She obtained a Ph.D. in statistics from the University of Michigan. She currently serves as the Fellow of Methods and Statistics. She is a lecturer in the Department of Methods and Statistics at the UU and is involved in curriculum development and developing interactive teaching strategies.

Dr. Bella Struminskaya is Assistant Professor at the Department of Methodology & Statistics at Utrecht University. She holds a Ph.D. in Survey Methodology from Utrecht University and an MA in Sociology from the University of Mannheim. Her areas of expertise include survey methodology and quantitative methods. Her research focuses on survey errors, data quality, online and smartphone surveys.

Contact person

Dr. Kirsten Namesnik is the Methods & Statistics fellow at UCU and holds office in the Sjoerd Groenmangebouw, Room C.101 in the Uithof, and in the Writing and Skills Center in Locke Ll.