experimenting by changing multiple factors (variables) simultaneously to efficiently identify 'which variables affect the results' and 'which combination is most effective'. However, the essence is ...

Variable selection is an unavoidable theme when conducting multivariate analysis. Deciding which variables to include in a model influences the interpretation and conclusions of a study far more than ...

The Python Toolkit for Uncertainty Quantification (PyTUQ) is a Python-only collection of libraries and tools designed for quantifying uncertainty in computational models. PyTUQ offers a range of UQ ...

Modern multivariate analysis relies heavily on probabilistic modelling to capture the joint behaviour of multiple interdependent variables. At its core lies the formulation of a joint probability ...

The Random Hardware Addresses feature is a great way to ensure that your computer is secure and that no one can track your movement. In this post, we will learn how to turn on Random Hardware ...

In the rapidly developing field of data science, using visual representations to understand complex datasets is a necessity. One potent tool in this analytical arsenal is the radar chart, an ...

The joint probability of two or more variables being “extreme” is relevant in Flood and Coastal Risk Management (FCRM) in various contexts, including: Assessing the likelihood of extreme peak flow ...

Abstract: This paper mainly discusses the application of multivariate Gaussian measure to KdV and Burgers equation. This paper used generalized polynomial chaos expansion (PCE) method and constructed ...

The lectures on this page should be watched before the live sessions on Monday, June 13, 2022 (Tuesday, June 14 in some time zones). Total viewing time for this lecture series is 2 hours 16 minutes.