Statistical Inference via Data Science: A ModernDive into R and the Tidyverse ...

The heplots package provides functions for visualizing hypothesis tests in multivariate linear models (MANOVA ... heplot3d() constructs analogous 3D plots for triples of response variables. The pairs ...

Background In a bustling corporate office, Sarah, a finance manager at Apex Financial Solutions, was tasked with optimizing ...

This probability can be estimated by defining a 'null hypothesis ... all methods for calculating P-values or for performing multiple testing correction assume a valid statistical model—either ...

Statistical methods are mathematical formulas, models, and techniques that are used in statistical analysis of raw research data. The application of statistical methods extracts information from ...

The CIO of this pioneering research organization says an iterative approach to emerging technology is the best way to build ...

STK1110 gives an introduction to statistical thinking and an overview of central statistical models and methods. The students are given insight into the theoretical foundation of the methods for ...

To prove the effectiveness of testing methods, it's essential to present clear metrics and tangible results, such as reduced production bugs, increased code coverage, and improved software stability.

How would we use statistical methods to determine which of two local grocery stores is less expensive ... mu_Z$, of the differences between the paired observations from the two sample and use a ...

This short course will enable you to develop your understanding of the statistical basis of generalised linear modelling (GLM) and its application in different situations, including the GLM regression ...

The problem is cast as a binary composite hypothesis testing ... where the statistics of the maximum likelihood estimates (MLEs) of the parameters are calculated. The optimization problem involved by ...