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About 10,000 papers for “Correlation coefficient”

correlation coefficient

2008

Citation: 'correlation coefficient' in the IUPAC Compendium of Chemical Terminology, 3rd ed.; International Union of Pure and Applied Chemistry; 2006. Online version 3.0.1, 2019. 10.1351/goldbook.C01347 • License: The IUPAC Gold Book is licensed under Creative Commons Attribution-ShareAlike CC BY-SA 4.0 International for individual terms. Requests for commercial usage of the compendium should be directed to IUPAC.

Cited by 19

Correlation coefficient.

Yongmei Li (227480), Hao Wang (39217), Hongli Zhao (1974871) et al. · Figshare · 2024

<p>PVIs represents published vegetation indices. Origin-PVIs,reciprocal-PVIs, logarithm-PVIs, square root-PVIs,FD-PVIs, and SD-PVIs represents published vegetation indices calculated from the original spectra, reciprocal spectra, logarithm spectra, square-root spectra, first-derivative spectra and second-derivative spectra datasets, respectively.</p> <p>(XLSX)</p>

Cited by 0Open access

Correlation coefficient.

Xinjian Xu (2697517), Yongneng Tan (22234123), Borhannudin bin Abdullah (22379045) · Figshare · 2025

<div> Background Despite the Chinese government’s focus on student physical education, low student participation in physical activities persists, necessitating efforts to improve engagement. Purpose This study explores the relationship between teacher support and university students’ engagement in physical education, focusing on the mediating roles of academic self-efficacy and sport task orientation, Methods A quantitative analysis was conducted to investigate the mediation effects among 2,625 students from various regions and school types. Results The study demonstrated significant correlations between teacher support, academic self-efficacy, sport task orientation, and PELE. Teacher support was found to positively influence physical education learning engagement (PELE) both directly and through academic self-efficacy and sport task orientation. The model fit indices suggested a good fit, Conclusion The findings highlight the critical roles of teacher support, academic self-efficacy, and sport task orientation in enhancing students’ engagement in physical education, offering valuable insights for improving physical education practices. </div>

Cited by 0Open access

Correlation coefficient.

Masaki Tago (9132206), Naoko E. Katsuki (9132209), Yoshimasa Oda (9132212) et al. · Figshare · 2020

Cited by 0Open access

Correlation coefficient

Mullainadhan, P · Eprints@CMFRI Open Access Institutional Repository (Central Marine Fisheries Research Institute) · 1981

Correlation coefficient (r) is an index of association between continuous variables. The coefficient • r ' may have values ranging from + 1 to — 1. r = +1 corresponds to a rectilinear relationship (of the form y=a+bx) in which the two variables are positively related. r=—1 corresponds to a rectilinear relationship (of the form y=a-bx) in which the two variables are negatively related. Values of' r ' near -f 1 (or—1) indicate an approach to a rectilinear relationship. But intermediate values of ' r ' are more difficult to interpret (Parker, 1973). Values of&#13;\n' r ' near zero may arise under two conditions : 1. when there is no relationship and 2. when there is a real relationship but it is curvi-linear.

Cited by 0

Correlation coefficient.

Minghui Zhao (558468), Zhenhua Wang (426041), Shuangshuang Liu (1780054) · Figshare · 2025

<div> In the context of intensifying global competitiveness and rapid technological advancement, industrial robots have emerged as a pivotal component in the integration of digital technology, exerting a vital influence on the transformation and enhancement of the manufacturing industry. The question of whether this transformative shift can significantly enhance total factor productivity (TFP) and accelerate the transformation of the manufacturing industry has attracted substantial academic attention. This study employs micro-panel data drawn from Chinese A-share listed manufacturing enterprises from 2007 to 2022 to examine the implications of industrial robot application on TFP and the underlying mechanisms. The results of our study indicate that industrial robots have a positive influence on TFP, and this effect persists over time. The results of the mechanism tests indicate that industrial robot application facilitates an increase in human capital, confirming their “talent aggregation effect”. Moreover, the application of industrial robots enhances enterprises’ innovative capabilities, thereby validating their “innovation effect”. Further examination of heterogeneity indicates that the enhancing impact of applying industrial robots on TFP is more pronounced among enterprises with high labor productivity, those that are state-owned, and enterprises operating in high-tech sectors. This research contributes to the understanding of the impact of industrial robot application on TFP, which is of considerable practical significance for emerging economies seeking to transform traditional enterprise factors, accelerate new technology integration, and steer the digital transformation of manufacturing. </div>

Cited by 0Open access