Introductory course by Maastricht University in data analytics using R and RStudio, focusing on basic programming, data handling, analysis, and visualization for complete beginners. Covers core R objects, control flow, and practical data work through lectures and hands-on tutorials.
Introduction to Data Analytics in R Read More »
Course by University of St. Gallen on computational statistics focused on data mining and modeling of large, high-dimensional datasets using modern statistical and machine learning methods. Covers regression, nonparametric models, trees, splines, additive models, neural networks, and resampling techniques like bootstrap and cross-validation. Emphasizes model building, evaluation, and handling challenges like the curse of dimensionality.
Computational Statistics Read More »
Course on multilevel analysis for continuous outcomes, focusing on hierarchical data structures where individuals are nested within social groups. Covers theory and applied examples, including multilevel modelling and extensions to longitudinal data analysis by Utrecht University.
Introduction to Multilevel Analysis Read More »
Introductory statistics course by University College London using R/RStudio, covering data analysis, visualization, and interpretation with no prior advanced math required. Includes topics from descriptive statistics and hypothesis testing to regression, multivariate analysis, and model optimization. Also examines proper use and limitations of statistics in real-world contexts.
Statistics with R and RStudio Read More »
Introductory course on modern survey methodology covering design, data collection, questionnaire testing, and analysis techniques, including nonresponse and scale construction. Emphasizes best practices across all survey phases and explores international and longitudinal surveys with expert guidance by Utrecht University.
Survey Research: Design, Implementation and Data Processing Read More »
Introductory course on using R and RStudio for data manipulation, visualization, statistical analysis, and reproducible reporting with R Markdown. Covers tidyverse workflows, generalized linear models, and techniques like bootstrapping, with hands-on exercises for all levels by Utrecht University.
Data Science: Statistical Programming with R Read More »