In today's data-driven world, researchers and analysts often face situations where they need to evaluate the impact of a factor on multiple outcomes simultaneously. Whether in education, healthcare, ...

Abstract: Over the past few years, many researchers around the world have been keen to know the potential and efficiency of quantum computers. The researchers have focused on specific issues that ...

Data science brings together computational and statistical skills for data-driven problem solving. This programme will equip students with the analytical tools to design sophisticated technical ...

Complex traits often exhibit substantial genetic sharing: many of the variants that are associated with one phenotype are also associated with other phenotypes. In the context of psychiatric disorders ...

Welcome to “Analytically Speaking,” the podcast from LCGC International and Spectroscopy. Here in Episode #33, podcast host Dr. Jerry Workman speaks with Dr. Brian G. Rohrback, President of Infometrix ...

Statistical science skills are powerful tools that play a valuable role in all pure and applied sciences, as well as in finance, commerce and medicine. The quantitative skills training provided by ...

MV2ScML is designed to perform the Multivariate Two-stage Constrained Maximum Likelihood (MV-2ScML) method to conduct the causal inference for multiple exposures. Here we provide a tutorial on how to ...

Mapping brain-behaviour associations is paramount to understand and treat psychiatric disorders. Standard approaches involve investigating the association between one brain and one behavioural ...

The emphasis is on statistical thinking rather than mathematical techniques, consequently statistical or mathematical theory are not discussed. The conceptual basis of the methods is emphasised; the ...

Biologics manufacturing entails multiple complex unit operations across three key process areas: cell culture, purification, and sterile fill–finish (Figure 1). Numerous raw materials are used to ...

Time series forecasting is a fundamental task in data science, applied statistics, and econometrics. With time series forecasting we aim to predict the future values of time series datasets. A time ...