Pearson product-moment correlation coefficient
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Correlation Coefficients: Appropriate Use and Interpretation Open
Correlation in the broadest sense is a measure of an association between variables. In correlated data, the change in the magnitude of 1 variable is associated with a change in the magnitude of another variable, either in the same (positiv…
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User's guide to correlation coefficients Open
When writing a manuscript, we often use words such as perfect, strong, good or weak to name the strength of the relationship between variables. However, it is unclear where a good relationship turns into a strong one. The same strength of …
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The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation Open
Background To evaluate binary classifications and their confusion matrices, scientific researchers can employ several statistical rates, accordingly to the goal of the experiment they are investigating. Despite being a crucial issue in mac…
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Comparing the Pearson and Spearman correlation coefficients across distributions and sample sizes: A tutorial using simulations and empirical data. Open
The Pearson product–moment correlation coefficient (rp) and the Spearman rank correlation coefficient (rs) are widely used in psychological research. We compare rp and rs on 3 criteria: variability, bias with respect to the population valu…
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Effect Size Guidelines, Sample Size Calculations, and Statistical Power in Gerontology Open
Background and Objectives Researchers typically use Cohen’s guidelines of Pearson’s r = .10, .30, and .50, and Cohen’s d = 0.20, 0.50, and 0.80 to interpret observed effect sizes as small, medium, or large, respectively. However, these gui…
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DeepSynergy: predicting anti-cancer drug synergy with Deep Learning Open
Motivation While drug combination therapies are a well-established concept in cancer treatment, identifying novel synergistic combinations is challenging due to the size of combinatorial space. However, computational approaches have emerge…
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Effects of e-learning on Students’ Motivation Open
E-learning has a significant role in instruction of students in higher education, so the objective of this study is investigating the strength of the relationship between e-learning and students' motivation among students participating in …
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Coupling a firefly algorithm with support vector regression to predict evaporation in northern Iran Open
Evaporation accounts for varying shares of water balance under different climatic conditions, and its correct prediction poses a significant challenge before water resources management in watersheds. Given the complex and nonlinear behavio…
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On relationships between the Pearson and the distance correlation coefficients Open
In this paper we show that for any fixed Pearson correlation coefficient strictly between −1 and 1, the distance correlation coefficient can take any value in the open unit interval (0,1).
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Sample Size Guideline for Correlation Analysis Open
Correlation analysis is a common statistical analysis in various fields. The aim is usually to determine to what extent two numerical variables are correlated with each other. One of the issues that are important to be considered before co…
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Evaluation of Satellite-Based Rainfall Estimates and Application to Monitor Meteorological Drought for the Upper Blue Nile Basin, Ethiopia Open
Drought is a recurring phenomenon in Ethiopia that significantly impacts the socioeconomic sector and various components of the environment. The overarching goal of this study is to assess the spatial and temporal patterns of meteorologica…
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Dependent Evidence Combination Based on Shearman Coefficient and Pearson Coefficient Open
Dempster-Shafer evidence theory is efficient to deal with uncertain information. One assumption of evidence theory is that the source of information should be independent when combined by Dempster's rule for evidence combination. However, …
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Biostatistics series module 6: Correlation and linear regression Open
Correlation and linear regression are the most commonly used techniques for quantifying the association between two numeric variables. Correlation quantifies the strength of the linear relationship between paired variables, expressing this…
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The Predictive Role of Systemic Inflammation Response Index (SIRI) in the Prognosis of Stroke Patients Open
Elevated SIRI was associated with higher risk of mortality and sepsis and higher stroke severity. Therefore, SIRI is a promising low-grade inflammatory factor for predicting stroke prognosis that outperformed NLR, PLR, LMR, and RDW in pred…
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Word2Vec Model Analysis for Semantic Similarities in English Words Open
This paper examines the calculation of the similarity between words in English using word representation techniques. Word2Vec is a model used in this paper to represent words into vector form. The model in this study was formed using the 3…
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Correlation and agreement: overview and clarification of competing concepts and measures. Open
Agreement and correlation are widely-used concepts that assess the association between variables. Although similar and related, they represent completely different notions of association. Assessing agreement between variables assumes that …
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Conducting correlation analysis: important limitations and pitfalls Open
The correlation coefficient is a statistical measure often used in studies to show an association between variables or to look at the agreement between two methods. In this paper, we will discuss not only the basics of the correlation coef…
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Sample Size Determination in Test-Retest and Cronbach Alpha Reliability Estimates Open
The estimation of reliability in any research is a very important thing. For us to achieve the goal of the research, we are usually faced with the issue of when the measurements are repeated, are we sure we will get the same result? Reliab…
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Investigating the Correlation Among Chinese EFL Teachers' Self-efficacy, Work Engagement, and Reflection Open
As the forerunners of education, teachers and their psycho-affective variables have been the focus of numerous studies in the past decades. To add to this line of inquiry, the present study aimed to scrutinize the correlation among English…
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Correlation Analysis to Identify the Effective Data in Machine Learning: Prediction of Depressive Disorder and Emotion States Open
Correlation analysis is an extensively used technique that identifies interesting relationships in data. These relationships help us realize the relevance of attributes with respect to the target class to be predicted. This study has explo…
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Assessing the accuracy of predictive models for numerical data: Not r nor r2, why not? Then what? Open
Assessing the accuracy of predictive models is critical because predictive models have been increasingly used across various disciplines and predictive accuracy determines the quality of resultant predictions. Pearson product-moment correl…
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Investigation of performance metrics in regression analysis and machine learning-based prediction models Open
Performance metrics (Evaluation metrics or error metrics) are crucial components of regression analysis and machine learning-based prediction models. A performance metric can be defined as a logical and mathematical construct designed to m…
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k-means based load estimation of domestic smart meter measurements Open
A load estimation algorithm based on kk-means cluster analysis was developed. The algorithm applies cluster centres – of previously clustered load profiles – and distance functions to estimate missing and future measurements. Canberra, Man…
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Best-Fit Probability Distributions and Return Periods for Maximum Monthly Rainfall in Bangladesh Open
The study of frequency analysis is important to find the most suitable model that could anticipate extreme events of certain natural phenomena e.g., rainfall, floods, etc. The goal of this study is to determine the best-fit probability dis…
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Voice Pathology Detection and Classification Using Auto-Correlation and Entropy Features in Different Frequency Regions Open
Automatic voice pathology detection and classification systems effectively contribute to the assessment of voice disorders, enabling the early detection of voice pathologies and the diagnosis of the type of pathology from which patients su…
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Estimation of Poverty Using Random Forest Regression with Multi-Source Data: A Case Study in Bangladesh Open
Spatially explicit and reliable data on poverty is critical for both policy makers and researchers. However, such data remain scarce particularly in developing countries. Current research is limited in using environmental data from differe…
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The validity and reliability of the My Jump 2 app for measuring the reactive strength index and drop jump performance Open
The results of the present study show that the My Jump 2 app is a valid and reliable tool for assessing drop jump performance.
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Automated Quantification of CT Patterns Associated with COVID-19 from Chest CT Open
A new method segments regions of CT abnormalities associated with COVID-19 and computes (PO, PHO), as well as (LSS, LHOS) severity scores.
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Effective degrees of freedom of the Pearson's correlation coefficient under autocorrelation Open
The dependence between pairs of time series is commonly quantified by Pearson's correlation. However, if the time series are themselves dependent (i.e. exhibit temporal autocorrelation), the effective degrees of freedom (EDF) are reduced, …
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Mathematical statistical analysis of attainment levels of primary left handed students based on pearson's conformity criteria Open
Quantitative changes in improving the effectiveness of teaching writing and developing the skills of elementary school students were summarized in the assessment of teaching effectiveness using Student and Pearson methods. Using the χ ^2 P…