Statistical Models
Statistical models are mathematical frameworks used to represent, analyze, and interpret relationships between variables in data, often for prediction, inference, or decision-making. They involve specifying assumptions about data generation processes and using statistical methods to estimate parameters and test hypotheses. Common types include linear regression, logistic regression, time series models, and Bayesian models.
Developers should learn statistical models when working on data-driven applications, such as machine learning, A/B testing, or analytics systems, to make informed decisions based on data patterns. They are essential for tasks like predicting user behavior, optimizing algorithms, or validating software performance through statistical inference, ensuring robust and evidence-based outcomes.