When it comes to statistics, we usually expect to be informed about what happens "on average." But sometimes the key information lies in deviations from that mean: how likely is heavy rain, and how ...

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 ...

A well-designed data model is the cornerstone of effective operational systems and BI and analytics applications that deliver business value by transforming enterprise data into a useful information ...

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 ...