Mathematics in Ecuadorian Professional Life: Quantitative Literacy and a Bayesian Analysis of Unemployment by Educational Level

Abstract

Objective: To reflect on the role of mathematics in professional practice in Ecuador and to demonstrate, using open data, how quantitative reasoning (particularly Bayesian inference) supports decision-making. Methodology: A thematic review was combined with an empirical study based on open data from the World Bank (World Development Indicators, based on ILO estimates) on unemployment rates by educational level in Ecuador between 2005 and 2024 (n = 57 country-year observations). Two Bayesian models were estimated using PyMC—a comparison of means by educational level and a time trend—with weakly informative priors and Hamiltonian Monte Carlo (NUTS) sampling. Results: The average unemployment rate was higher among those with intermediate education (6.15%; 94% credibility interval: [5.73, 6.59]) and advanced education (4.95%; [4.57, 5.34]) than among those with basic education (2.49%; [2.20, 2.80]); the posterior probability that unemployment among those with advanced education would exceed that of those with basic education was 1.00, and unemployment among those with advanced education showed an upward trend (0.068 percentage points per year; [0.009, 0.128]; probability of a positive slope = 0.98). Conclusions: Far from denying the value of education, this pattern reflects informality and the wait for formal employment, and demonstrates why careful statistical interpretation is an indispensable professional skill in contemporary Ecuador.