When it comes to statistics, we usually expect to be informed about what happens "on average." But sometimes the key ...

Statistical modeling lies at the heart of data science. Well-crafted statistical models allow data scientists to draw conclusions about the world from the limited information present in their data. In ...

Abstract: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision-making. In both traditional ...

Statistical modelling of latent variables refers to the suite of methods used to infer unobserved constructs from observed data. By representing underlying factors, traits or processes that cannot be ...

This book, “Statistical Modeling and Computation,” provides a unique introduction to modern statistics from both classical and Bayesian perspectives. It also offers an integrated treatment of ...

Statistical modelling of zero-inflated count data addresses datasets in which the frequency of zero outcomes exceeds that predicted by standard count distributions. Such phenomena arise across ...

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 ...