The first step in conducting a regression-based study is to specify a model. In real applications, this is usually the most challenging step - deciding which variables “belong” in the model and which ...

Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...

Meteorological dispersion modeling (DM) and land-use regression modeling (LUR) are alternative methods describing small scale variations in air pollution levels, and both have been documented to ...

Statistical models predict stock trends using historical data and mathematical equations. Common statistical models include regression, time series, and risk assessment tools. Effective use depends on ...

Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on this powerful machine learning technique used to predict a single numeric value. A regression problem is one ...

A behind-the-scenes blog about research methods at Pew Research Center. For our latest findings, visit pewresearch.org. Many of Pew Research Center’s survey analyses show relationships between two ...

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...