Statistical Inference
Statistical inference is a branch of statistics that involves drawing conclusions about populations or processes based on data from samples. It uses probability theory to quantify uncertainty and make predictions, typically through methods like hypothesis testing, confidence intervals, and estimation. This concept is fundamental for making data-driven decisions in fields such as science, engineering, and business.
Developers should learn statistical inference when working with data analysis, machine learning, or any domain requiring evidence-based conclusions, such as A/B testing in web development or model validation in data science. It enables them to assess the reliability of results, avoid spurious correlations, and design experiments effectively, which is crucial for building robust applications and conducting reproducible research.