All Courses
On this page you can find all the courses and tracks offered by the Utrecht Summer School. Detailed information is published on all individual course pages.
30 course(s) found
Survey Research: Statistical Analysis and Estimation
The course is based on a total survey error perspective and discusses the major sources of survey error. Participants will be presented with tools for detection and adjustment of such errors. Analysis methods are introduced using R statistical software. Knowledge of R is beneficial but not required if you have worked with SPSS, Stata, SAS or other statistical software already. Topics include coverage errors, complex sampling, nonresponse…
1
Structural Equation Modeling in R using lavaan (E-Learning Course)
Online course
In this e-learning course, we will cover the basics of structural equation modeling (SEM) using the R package lavaan. Participants will learn how to interact with the lavaan software and how to run common types of structural equation models (e.g., path models, confirmatory factor analyses, latent regression models, multiple group models) using lavaan. No prior knowledge of lavaan is necessary, but some experience with R and SEM (although not…
1
Psychodiagnostics: Theory and Skills Training ONLINE
Online course
This summer, Utrecht University offers you a 'bridging' course in psychodiagnostics, in order to overcome deficiencies in psychodiagnostics and assessment for entering the master course Clinical Psychology. This summer course focusses on familiarizing oneself with theoretical backgrounds of psychodiagnostics, practicing skills necessary to master all stages of the diagnostic process (intake, formulating a diagnostic question, formulating…
1
Data Science: Network Science
How can networks help us understand and predict social systems? How to find important individuals and communities? How to predict unobserved connections between genes? How to learn the dependencies between interrelated entities? How can we stop disease or information spreading in networks? In this course, we provide participants with the conceptual and practical skills necessary to use network science tools to answer social, economic and…
1
Regression in R
Linear regression is one of the most ubiquitous statistical methods. Most statistical techniques can be viewed as either special cases of linear regression (e.g., t-tests, ANOVA) or generalizations of linear regression (e.g., multilevel modeling, SEM, neural networks, GLM, survival analysis). In this workshop, participants will learn how to apply linear regression techniques in R. We will cover (multiple) linear regression, categorical predictor…
1
Data Science: Introduction to Text Mining with R
Applications of text mining are everywhere: social media, web search, advertising, emails, customer service, healthcare, marketing, etc. In this course, students will learn how to apply text mining methods on text data and analyse them in a pipeline with statistical learning algorithms. The course has a strongly practical hands-on focus, and students will gain experience in using and interpreting text mining on data examples from humanities,…
1
Bayesian Hypothesis Evaluation using JASP or R
In this one day course participants will be introduced to informative hypotheses that are alternatives for the traditional null and alternative hypotheses, and, to the Bayes factor and GORIC which are alternatives for the p-value. This course is applied, hands-on, and build around concepts and not formulas.
1
A gentle introduction to Bayesian Estimation
This course introduces all the essential ingredients needed to start Bayesian estimation and inference. We discuss specifying priors, obtaining the posterior, prior/posterior predictive checking, sensitivity analyses, and the usefulness of a specific class of priors called shrinkage priors. We propose strategies for reproducibility and reporting standards, outlining the WAMBS-checklist (when to Worry and how to Avoid the Misuse of Bayesian…
1
Advanced Survey Design
This course in ‘advanced survey design’ takes students beyond the introductory courses and will discuss the state of the art in both the design and the analysis of modern survey data, with a focus on new types of data. We discuss new ways to analyse modern surveys, including non-probability survey designs, smartphone data collection, digital trace data and data collected via apps. Course participants must be proficient working with the…
1
Advanced Communication Skills: Between Persuasion and Empathy
Effective communication is key for high performing professionals. If you want to bring your communication skills to the next level and work on your personal development, then this course is here for you! Two experienced professionals teach you the most valuable skills they learned themselves over the past 15 years. This course takes you beyond the ‘basics’. You will, amongst other things, learn the highlights from principle-based negotiation,…
1
Data Science: Statistical Programming with R
This course offers an elaborate introduction to statistical programming with R. Students learn to operate R, form pipelines for data analysis, make high quality graphics, fit, assess, and interpret a variety of statistical models, and do advanced statistical programming. The statistical theory in this course covers t-testing, regression models for linear, dichotomous, ordinal, and multivariate data, statistical inference, statistical learning,…
1
Introduction to R
This workshop will introduce participants to the R statistical programming language. R is a completely free and open-source programming language and environment for statistical analysis. In this workshop, participants will learn what R is and how it differs from other statistical software packages and programming languages. They will learn the basics of data I/O, manipulation, and visualization in R. We will also cover basic statistical analyses…
1
Data Science: Data Analysis
The course Data science: Data Analysis offers a range of techniques and algorithms from statistics, machine learning and data mining to make predictions about future events and to uncover hidden structures in data. The course has a strong practical focus; participants actively learn how to apply these techniques to real data and how to interpret their results. The course covers both classical and modern topics in data analysis.
1
Eye Tracking Research Toolbox
Eye tracking is a powerful method to study the human mind and behavior. This course will allow you to explore key concepts in eye tracking research and help you integrate it in your study. The course is divided into two components: (1) a conceptual framework to help you make better decisions when planning and executing a study, allowing you to turn eye tracking data into valuable insights; (2) a practical introduction to the challenges and trade…
1
Survey Research: Design, Implementation and Data Processing
Changes in technology and society strongly influence modern survey research. This course covers the essentials of modern survey methodology, organized by the Department of Methodology and Statistics. Central to the course is survey quality and the reduction of Total Survey Error (coverage, sampling, nonresponse, including questionnaire and mode effects), while balancing logistics and survey costs. Best practice guidelines for surveys from design…
1
Applied Multivariate Analysis
The summer school course 'Applied Multivariate Analysis' offers hands-on experience using SPSS for the most frequently encountered multivariate statistical techniques in the social and behavioural sciences. The emphasis is on applying multivariate techniques using the computer programme SPSS, and on how to interpret the SPSS output in substantive terms. During the course, we do not discuss the mathematical details of these techniques.
1
Coaching Skills for Young Leaders
Coaching skills are about helping others to live their full potential. Its a great skill in and of itself, but it is also a key ingredient for effective leadership. So, are you a student or a young professional and do you want to acquire or deepen coaching skills? Then this Summer School is for you. This course will teach you the coaching skills you need as a coach or a leader. In every session you will learn and practice with powerful coaching…
1
Advanced longitudinal modeling in Mplus
This is a 5-day course on structural equation modeling (SEM) using Mplus. In this course, SEM experts will teach you about the fundamentals of SEM and various types of longitudinal data analysis techniques, such as growth curves analysis, cross-lagged panel models, and dynamic structural equation modeling (DSEM). The course consists of in-depth lectures and computer lab meeting on the fundamentals of Mplus and on advanced longitudinal models.
1
Structural Equation Modelling in Mplus
If you expect to work with the software Mplus, this course can help you to get started! This course is a compact 1-day workshop introducing Mplus. We will focus on preparing data for Mplus, introducing common model syntax, avoiding common mistakes, interpreting output, and dealing with common error messages. Practice exercises demonstrate multiple regression and factor analysis models, which are the basis of structural equation models in Mplus.
1
Modeling the Dynamics of Intensive Longitudinal Data
This is a five-day course on how to study dynamics in intensive longitudinal data, such as ambulatory assessments (AA), experience sampling method (ESM) data, ecological momentary assessments (EMA), real time data capture, observational data or electronic daily diaries. We provide a tour of diverse modeling approaches for such data and the philosophies behind them, as well as practical experience with these modeling techniques using different…
1
Data Science: Programming with Python
Python has become the dominant programming language used in data science. This course offers an introduction to computational thinking about data-related problems and the implementation of data analysis programs with Python. It starts at the very basics and is explicitly intended for students who have no or only little programming experience.
1
Introduction to Python (online course)
If you are looking for a powerful programming language, you should learn Python, a language with a simple syntax and a powerful set of libraries. It is easy for beginners to learn Python and it is widely used in many scientific fields for data exploration. This workshop is an introduction to the Python programming language and, in particular, is geared toward people who are new to the language and who have relatively little experience with other…
1
Open Science Hypothesis Testing
This 3-day course discusses the evaluation of theory-based hypotheses using p-values, the Bayes factor, and information criteria. There will be attention for contemporary phenomena, like publication bias, questionable research practices, the replication crisis, the statistical evaluation of replication studies, and studies in which multiple data sets are used to evaluate the same research question. The course will be non-technical in nature,…
1
Introduction to Structural Equation Modeling using Mplus
We offer a 5-day course on how to perform basic SEM analyses using Mplus. The main objective of this course is to learn how to analyse several models with Mplus (e.g., path models, multiple group models, mediation and moderation, confirmatory factor analysis, and longitudinal models). No previous knowledge of Mplus is assumed, but prior knowledge of SEM, although not mandatory, will make this course more useful.
1
Introduction to Multilevel Analysis
This course will teach you the theoretical basics of multilevel modelling and some important methodological and statistical issues. You will also learn how to analyse multilevel data sets with the R and R Studio programs, to interpret the output and to report the results. The benefits of multilevel analysis are discussed both in theory as with empirical examples. This course restricts to a quantitative (i.e. continuous) outcome variable.…
1