Closed
Closed
Closed
This course is aimed at analysts and researchers who work with household survey data on children’s foundational learning. You may be comfortable with Excel or Stata but new to R, or you may be returning to quantitative work after time in the field. The course assumes no prior programming experience. It does, however, assume familiarity with basic statistical concepts such as means, proportions, correlation, and the logic of regression.
Throughout the course, you will work with the ICAN-ICAR 2025 household survey. This is a nationally representative, household-based study of children aged 5–16, covering foundational numeracy and reading across multiple countries. The dataset is large (containing tens of thousands of children and households) and rich in policy-relevant variables, including reading and mathematics ability scores, minimum proficiency indicators, enrolment, grade level, household composition, and assessment context. By working with a single real-world survey from start to finish, you will develop skills that transfer directly to population-level reporting and research, rather than simply describing the particular sample in front of you.
The teaching approach is hands-on and cumulative. Each chapter builds on the previous one, with guided practice, independent exercises, and code that you can adapt to your own questions. A central theme is survey-aware analysis: ICAN-ICAR uses a stratified, multi-stage cluster design with household weights. The course explains why unweighted tables can misrepresent the population, how weights and survey design variables are incorporated into the analysis, and how to obtain design-correct estimates and standard errors in R.
A second theme is reproducibility: organising work in RStudio projects, writing scripts, chaining steps together using readable pipelines, and saving outputs such as tables and figures.
Closed