We were recently approached by a government to optimally allocate teachers to schools. The state has a few hundred secondary schools and is meant to offer a set of subjects in all these schools. But there are a number of classrooms without a teacher allocated. To close these “gaps”, a new cohort of teachers were trained to join the existing set of teachers. They asked us how these new teachers should be assigned while taking operational and logistical constraints into account. These kinds of problems are notoriously hard to solve optimally1. Operational Research offers clever techniques to search the solution space for optimal solutions.
In this post, I discuss how IDinsight’s DSEM team implemented a data quality check for pairs of variables displaying linear relationships. We explain why we chose a Bayesian model, and the tweaks we made to address the hierarchy and outliers in data. We will also see how to implement the model using PyMC3.
