26 papers · ranked by Valyu relevance
Birk Diedenhofen, Jochen Musch, Jake Olivier
A valid comparison of the magnitude of two correlations requires researchers to directly contrast the correlations using an appropriate statistical test. In many popular statistics packages, however, tests for the significance of the difference between correlations are missing. To close this gap, we introduce cocor, a…
Hélio Amante Miot
It is common for researchers conducting clinical or biomedical studies to be interested in investigating whether the values of two or more quantitative variables change in conjunction in a given individual or object of study. In other words, whether when the value of one variable increases, the value of another tends…
Laura C. Guglielmetti, Fabio Faber-Castell, Lukas Fink, Raphael N. Vuille-dit-Bille
'Raphael N. Vuille-dit-Bille'] Background Statistic scripts are often made by mathematicians and cryptic for clinicians or non-mathematician scientists. Nevertheless, almost all research projects necessitate the application of some statistical tests or at least an understanding thereof. The present review aims on…
M Harshvardhan, Pritam Ranjan
Pearson correlation is the default measure of association in most statistical software, yet it is only appropriate for pairs of continuous variables with a linear relationship. When variables are binary, ordinal, or categorical, specialized methods (e.g., point-biserial, polychoric, tetrachoric, and Cramér's~$V$) may…
Constantine Stalikas, Vasilios Sakkas
In this tutorial review, we provide a guiding reference on the good practice in building calibration and correlation experiments, and we explain how the results should be evaluated and interpreted. The review centers on calibration experiments where the relationship between response and concentration is expected to be…
Yi Wang, Yi Li, Hongbao Cao, Momiao Xiong + 2 more
Background Testing dependence/correlation of two variables is one of the fundamental tasks in statistics. In this work, we proposed a new way of testing nonlinear dependence between two continuous variables (X and Y). Results We addressed this research question by using CANOVA (continuous analysis of variance, software…
Pero Hrabač, Vladimir Trkulja
A somewhat bizarre title of this column comes from one of the charts shown on the website named “Spurious Correlations” (1). It shows the correlation or association between two variables. The variables in question are per capita cheese consumption and the number of people who died by becoming entangled in their…
Alex E. Yuan, Wenying Shou
In disciplines from biology to climate science, a routine task is to compute a correlation between a pair of time series, and determine whether the correlation is statistically significant (i.e. unlikely under the null hypothesis that the time series are independent). This problem is challenging because time series…
Robert M Flight, Praneeth S Bhatt, Hunter NB Moseley
Almost all correlation measures currently available are unable to directly handle missing values. Typically, missing values are either ignored completely by removing them or are imputed and used in the calculation of the correlation coefficient. In both cases, the correlation value will be impacted based on a…
Fatih Dikbaş
Correlation remains to be one of the most widely used statistical tools for assessing the strength of relationships between data series. This paper presents a novel compositional correlation method for detecting linear and nonlinear relationships by considering the averages of all parts of all possible compositions of…
Ming Luo, S. Radhakrishnan, Sagar Kamarthi
Study on Surface Roughness in Finish Turning Authors: ['Ming Luo' 'S. Radhakrishnan' 'Sagar Kamarthi'] | 1 | INTRODUCTION | 3 | | --- | --- | --- | | 2 | THE CONCEPT OF CORRELATION BETWEEN TWO VARIABLES | 3 | | | 2.1 Pearson Correlation Coefficient | 8 | | | 2.2 Spearman's Rank Correlation Coefficient | 9 | | | 2.3…
Aditi Kathpalia, Nithin Nagaraj
Determining and measuring cause-effect relationships is fundamental to most scientific studies of natural phenomena. The notion of causation is distinctly different from correlation which only looks at association of trends or patterns in measurements. In this article, we review different notions of causality and focus…
Donald St. P. Richards
The difficulties of detecting association, measuring correlation, and establishing cause and effect have fascinated mankind since time immemorial. Democritus, the Greek philosopher, underscored well the importance and the difficulty of proving causality when he wrote, "I would rather discover one cause than gain the…
Catherine S Cutts, Stephen J Eglen
Correlations in neuronal spike times are thought to be key to processing in many neural systems. Many measures have been proposed to summarise these correlations and of these the correlation index is widely used and is the standard in studies of spontaneous retinal activity. We show that this measure has two…
Florian Griessenberger, Wolfgang Trutschnig, Robert R. Junker
Correlations belong to the standard repertoire of ecologists for quantifying the strength of dependence between two random variables. Classical dependence measures are usually not capable of detecting non-monotonic or non-functional dependencies. Furthermore, they completely fail to detect asymmetry and direction in…
Md. Aktar Hossain, Saima Sultana
In silico analysis is a powerful technique to identify better therapeutic interventions. Molecular docking is widely used to screen ligands through analysing binding affinities for target receptors. In this study we screened ligands for two proteins which are potential drug targets: deoxyuridine triphosphate…
Authors not listed
Chiral 2D metal halide perovskites (MHPs) hold promise for next-generation spin-optoelectronic applications. While still in early-stage development, significant efforts have focused on optimizing the dissymmetry factor (g), particularly in terms of their circular dichroism (gabs), which quantifies the chiroptical…
Alex E. Yuan, Wenying Shou
In disciplines from ecology to neuroscience, researchers analyze correlations between pairs of nonstationary time series to infer relationships among variables. This often involves a statistical test to determine whether an observed correlation is stronger than expected under the null hypothesis of independence.…
David Lovell, Vera Pawlowsky-Glahn, Juan José Egozcue, Samuel Marguerat + 1 more
In the life sciences, many measurement methods yield only the relative abundances of different components in a sample. With such relative—or compositional—data, differential expression needs careful interpretation, and correlation—a statistical workhorse for analyzing pairwise relationships—is an in-appropriate measure…
Elisa Claire Alemán Carreón, 尋史 野中, 透 平岡
In current times, the importance of online hotel review sites has become more and more apparent. Users of these sites reference of reviews strongly influences their purchase behavior and as such, reviews are important to companies and researchers alike. The majority of review sites offer both text reviews and numerical…
Souvik Manna, Diptendu Roy, Sandeep Das, Biswarup Pathak
Application of data science and machine learning (ML) techniques in the domain of materials science has been increasing by leaps and bounds recently. With the help of ML, through input features derived from available databases we can rapidly screen materials based on our desired output. Capacity is one of the important…
Joseph Davies, David Pattison, Jonathan Hirst
Machine learning models were developed to predict product formation from time-series reaction data for ten Buchwald-Hartwig coupling reactions. The data was provided by DeepMatter and was collected in their DigitalGlassware cloud platform. The reaction probe has 12 sensors to measure properties of interest, including…
Authors not listed
Explainability methods in machine learning-driven research are increasingly being used, but it remains challenging to assess their reliability without deeply investigating the specific problem at hand. In this work, we present a Python-based Workflow for Interpretability Scoring using matched molecular Pairs (WISP).…
Authors not listed
We developed OpenStats, a user-friendly web application that brings the power of the R language to researchers through a high-level interface and broad support for statistical methods such as t-tests and ANOVA. OpenStats was integrated into our electronic lab notebook Chemotion ELN via its third-party API, enabling…
Authors not listed
High-throughput experimentation (HTE) in materials science generates vast, high-dimensional datasets relating synthesis parameters to material properties. While machine learning (ML) models excel at predicting properties from these parameters, they often fail to distinguish causal drivers from merely correlated…
Authors not listed
Mechanical agitation (stirring) is a cornerstone of organic synthesis, but has received little scientific attention due to its “obvious” role in facilitating reactions. A very recent study by Huang and coworkers compared the isolated yields in approximately 600 paired stirred and unstirred reactions, across a range of…