Statistics

Statistics, Thoughts

Causality, the Philosophy, Evaluation, and the Tawhidic View

Understanding causality is essential in everyday life because it shapes how people make decisions, assign responsibility, and anticipate outcomes. From simple actions such as taking medicine to relieve pain, to complex choices like implementing public health policies, people rely on assumptions about cause and effect. When these assumptions are unclear or mistaken, decisions may be ineffective or harmful. Reflecting on… Continue reading Causality, the Philosophy, Evaluation, and the Tawhidic View

Statistics

The Evolution of Statistical Inference: From Formulas to Computers

Statistics is the science of learning from data. Every time researchers use a sample to understand a population, they are practising statistical inference. Over the past century, the way we make these inferences has changed dramatically. Each new approach has brought a different philosophy about what “truth” means and how we can best estimate it. This article explains the main… Continue reading The Evolution of Statistical Inference: From Formulas to Computers

Public Health, Statistics

Statistics and Machine Learning in Public Health: When to Use What

If you’re trained in epidemiology or biostatistics, you likely think in terms of models, inference, and evidence. Now, with machine learning entering the scene, you’re probably hearing about algorithms that can “predict” disease, “detect” outbreaks, and “learn” from data. But while ML offers exciting possibilities, it’s important to understand how it differs from classical statistical approaches—especially when public health decisions… Continue reading Statistics and Machine Learning in Public Health: When to Use What