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Journal articles on the topic 'Pearson's coefficient'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Sedgwick, P. "Pearson's correlation coefficient." BMJ 345, jul04 1 (2012): e4483-e4483. http://dx.doi.org/10.1136/bmj.e4483.

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2

Emerson, Robert Wall. "Causation and Pearson's Correlation Coefficient." Journal of Visual Impairment & Blindness 109, no. 3 (2015): 242–44. http://dx.doi.org/10.1177/0145482x1510900311.

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3

L Suresh, P., and Kalidindi Narayana Raju. "Study of Test for Significance of Pearson's Correlation Coefficient." International Journal of Science and Research (IJSR) 11, no. 10 (2022): 164–66. http://dx.doi.org/10.21275/sr22915140002.

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4

Hauke, Jan, and Tomasz Kossowski. "Comparison of Values of Pearson's and Spearman's Correlation Coefficients on the Same Sets of Data." Quaestiones Geographicae 30, no. 2 (2011): 87–93. http://dx.doi.org/10.2478/v10117-011-0021-1.

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Comparison of Values of Pearson's and Spearman's Correlation Coefficients on the Same Sets of Data Spearman's rank correlation coefficient is a nonparametric (distribution-free) rank statistic proposed by Charles Spearman as a measure of the strength of an association between two variables. It is a measure of a monotone association that is used when the distribution of data makes Pearson's correlation coefficient undesirable or misleading. Spearman's coefficient is not a measure of the linear relationship between two variables, as some "statisticians" declare. It assesses how well an arbitrary

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5

Kader, Gary, and Christine Franklin. "The Evolution of Pearson's Correlation Coefficient." Mathematics Teacher 102, no. 4 (2008): 292–99. http://dx.doi.org/10.5951/mt.102.4.0292.

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Studying the relationship between two quantitative variables is a standard topic in statistics. In high school and introductory college-level statistics, Pearson's correlation coefficient, r, is typically included as a measure of the direction and strength of the linear relationship between two quantitative variables. This article describes an activity that aids an intuitive development of the formula for r and its interpretation. Exploring scatter plots allows students to develop an intermediate measure of association called the quadrant count ratio (QCR), investigate properties of the QCR, a

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Kader, Gary, and Christine Franklin. "The Evolution of Pearson's Correlation Coefficient." Mathematics Teacher 102, no. 4 (2008): 292–99. http://dx.doi.org/10.5951/mt.102.4.0292.

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Studying the relationship between two quantitative variables is a standard topic in statistics. In high school and introductory college-level statistics, Pearson's correlation coefficient, r, is typically included as a measure of the direction and strength of the linear relationship between two quantitative variables. This article describes an activity that aids an intuitive development of the formula for r and its interpretation. Exploring scatter plots allows students to develop an intermediate measure of association called the quadrant count ratio (QCR), investigate properties of the QCR, a

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7

Armstrong, Richard A. "Should Pearson's correlation coefficient be avoided?" Ophthalmic and Physiological Optics 39, no. 5 (2019): 316–27. http://dx.doi.org/10.1111/opo.12636.

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8

Ly, Alexander, Maarten Marsman, and Eric-Jan Wagenmakers. "Analytic posteriors for Pearson's correlation coefficient." Statistica Neerlandica 72, no. 1 (2017): 4–13. http://dx.doi.org/10.1111/stan.12111.

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9

Shah, Dharambhai, and Tanish Zaveri. "Hyperspectral endmember extraction using Pearson's correlation coefficient." International Journal of Computational Science and Engineering 24, no. 1 (2021): 89. http://dx.doi.org/10.1504/ijcse.2021.113656.

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Zaveri, Tanish, and Dharambhai Shah. "Hyperspectral endmember extraction using Pearson's correlation coefficient." International Journal of Computational Science and Engineering 24, no. 1 (2021): 89. http://dx.doi.org/10.1504/ijcse.2021.10036023.

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11

Puth, Marie-Therese, Markus Neuhäuser, and Graeme D. Ruxton. "Effective use of Pearson's product–moment correlation coefficient." Animal Behaviour 93 (July 2014): 183–89. http://dx.doi.org/10.1016/j.anbehav.2014.05.003.

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12

Amdisen, Amdi. "Pearson's correlation coefficient, p-value, and lithium therapy." Biological Psychiatry 22, no. 7 (1987): 926–28. http://dx.doi.org/10.1016/0006-3223(87)90094-1.

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13

Rebekić, Andrijana, Zdenko Lončarić, Sonja Petrović, and Sonja Marić. "PEARSON'S OR SPEARMAN'S CORRELATION COEFFICIENT - WHICH ONE TO USE?" Poljoprivreda 21, no. 2 (2015): 47–54. http://dx.doi.org/10.18047/poljo.21.2.8.

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14

Huhn, Craig. "Correlation Revelation: The Search for Meaning in Pearson's Coefficient." Mathematics Teacher 110, no. 2 (2016): 98–103. http://dx.doi.org/10.5951/mathteacher.110.2.0098.

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15

Gastmeier, Petra, Dorit Sohr, Dietmar Forster, et al. "Identifying Outliers of Antibiotic Usage in Prevalence Studies on Nosocomial Infections." Infection Control & Hospital Epidemiology 21, no. 5 (2000): 324–28. http://dx.doi.org/10.1086/501764.

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AbstractObjective:To investigate whether the correlation between patients' antibiotic treatment (yes/no) and patients' infections (yes/no) in each hospital department, described by Pearson's correlation coefficient (ρ) for binary data as a measure for adequate use of antibiotics, is an appropriate quality indicator.Design:Comparison of the results of repeated prevalence studies in different hospitals with the data of a national prevalence study, comparing the hospital (ρ) and reference (ρNIDHP[Nosokomiale Infektionen in Deutschland: Erfassung und Prävention]) correlation coefficients for “use

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16

Liu, Huiyu, Yunzhou Zhang, Xiaolin Su, Xintong Li, and Ning Xu. "Mobile Localization Based on Received Signal Strength and Pearson's Correlation Coefficient." International Journal of Distributed Sensor Networks 11, no. 8 (2015): 157046. http://dx.doi.org/10.1155/2015/157046.

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17

Afyouni, Soroosh, Stephen M. Smith, and Thomas E. Nichols. "Effective degrees of freedom of the Pearson's correlation coefficient under autocorrelation." NeuroImage 199 (October 2019): 609–25. http://dx.doi.org/10.1016/j.neuroimage.2019.05.011.

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18

DeGhett, V. J. "Effective use of Pearson's product-moment correlation coefficient: an additional point." Animal Behaviour 98 (December 2014): e1-e2. http://dx.doi.org/10.1016/j.anbehav.2014.10.006.

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CHO, SUNG-BAE. "EXPLORING FEATURES AND CLASSIFIERS TO CLASSIFY GENE EXPRESSION PROFILES OF ACUTE LEUKEMIA." International Journal of Pattern Recognition and Artificial Intelligence 16, no. 07 (2002): 831–44. http://dx.doi.org/10.1142/s0218001402002015.

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Bioinformatics has recently drawn a lot of attention to efficiently analyze biological genomic information with information technology, especially pattern recognition. In this paper, we attempt to explore extensive features and classifiers through a comparative study of the most promising feature selection methods and machine learning classifiers. The gene information from a patient's marrow expressed by DNA microarray, which is either the acute myeloid leukemia or acute lymphoblastic leukemia, is used to predict the cancer class. Pearson's and Spearman's correlation coefficients, Euclidean di

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20

Cowgill, George L. "Why Pearson's r is Not a Good Similarity Coefficient for Comparing Collections." American Antiquity 55, no. 3 (1990): 512–21. http://dx.doi.org/10.2307/281281.

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Pearson's coefficient of linear correlation, r, sometimes is used to express the similarity between two archaeological collections when each collection is characterized by the percents of the artifact types it includes. Examples show that r can be extremely misleading when used in this way, and patterns of similarity among a group of collections can be wildly misrepresented. The Brainerd–Robinson statistic is one example of a similarity coefficient that is much better than r for comparing collections.

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Ribeiro, Adriana Bouças, Suely Godoy Agostinho Gimeno, Solange Andreoni, and Sandra Roberta Gouveia Ferreira. "Should body mass index be adjusted for relative sitting height in cross-sectional studies of chronic diseases in Japanese-Brazilians?" Cadernos de Saúde Pública 22, no. 8 (2006): 1691–97. http://dx.doi.org/10.1590/s0102-311x2006000800017.

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The current article aimed to verify the degree of agreement in classification of nutritional status according to body mass index (BMI) and corrected body mass index (BMIc). Data were used from a cross-sectional study of Japanese-Brazilians. Statistical analysis provided prevalence rates for chronic diseases, kappa statistic, and Pearson's linear correlation coefficient. Some 5.9% of Japanese-Brazilians were discordant according to the BMI and BMIc classifications. The weighted kappa statistic (0.94; p = 0.000) indicated good agreement between the classifications. Similar prevalence rates for c

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22

Barlow, Andrew L., Alasdair MacLeod, Samuel Noppen, Jeremy Sanderson, and Christopher J. Guérin. "Colocalization Analysis in Fluorescence Micrographs: Verification of a More Accurate Calculation of Pearson's Correlation Coefficient." Microscopy and Microanalysis 16, no. 6 (2010): 710–24. http://dx.doi.org/10.1017/s143192761009389x.

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AbstractOne of the most routine uses of fluorescence microscopy is colocalization, i.e., the demonstration of a relationship between pairs of biological molecules. Frequently this is presented simplistically by the use of overlays of red and green images, with areas of yellow indicating colocalization of the molecules. Colocalization data are rarely quantified and can be misleading. Our results from both synthetic and biological datasets demonstrate that the generation of Pearson's correlation coefficient between pairs of images can overestimate positive correlation and fail to demonstrate neg

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23

Ma, Rubao, Weichao Xu, Yun Zhang, and Zhongfu Ye. "Asymptotic Properties of Pearson's Rank-Variate Correlation Coefficient under Contaminated Gaussian Model." PLoS ONE 9, no. 11 (2014): e112215. http://dx.doi.org/10.1371/journal.pone.0112215.

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24

Dai, Lixuan, Mingguang Ren, Zihong Li, Li Wang, and Weiying Lin. "A targetable fluorescent probe for imaging of mitochondrial viscosity in living cells." Analytical Methods 11, no. 36 (2019): 4561–65. http://dx.doi.org/10.1039/c9ay01575b.

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25

Timchenko, A. V., F. S. Bessarab, and A. V. Radievsky. "SEASONAL FEATURES OF THE CORRELATION OF THE TOTAL ELECTRON CONTENT AT MAGNETICALLY CONJUGATE POINTS." PHYSICS OF AURORAL PHENOMENA 44 (2021): 130–32. http://dx.doi.org/10.51981/2588-0039.2021.44.030.

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The paper presents the results of studies of the seasonal variability of statistical relationships between Magnetoconjugated Points (MCP) of the ionosphere. The analysis is based on the calculation of the correlation coefficients between the variations in the Total Electron Content (TEC) at points located on the same field line of the dipole magnetic field on both sides of the geomagnetic equator. Global TEC maps were used as initial data. For the four seasons of 2009 and 2015, the values of the Pearson’s correlation coefficient between the variations in the Total Electron Content in the MCP w

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26

Zhang, Lingfei, Jiayu Zhou, and Gaofeng Zhang. "Modelling And Research on Water Level Control of Great Lakes Based on Neural Network PID Algorithm." Highlights in Science, Engineering and Technology 113 (October 8, 2024): 97–104. http://dx.doi.org/10.54097/a0q10t93.

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The Great Lakes are situated in the border region between the United States and Canada, which has a significant impact on the climate and the lives of those living in the surrounding areas. The objective of this paper is to establish a network of the Great Lakes through Pearson's correlation coefficient analysis and to construct a two-tank water level model based on a PID control system in order to effectively manage the dynamics of the Great Lakes. Firstly, the strength and direction of the linear relationship between two variables is quantified through Pearson's correlation coefficient analy

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27

Moothathu, T. S. K. "On The Best Estimators of Coefficients of Variation, skewness and Kurtosis of Pareto Distribution and Their Variances." Calcutta Statistical Association Bulletin 37, no. 1-2 (1988): 29–40. http://dx.doi.org/10.1177/0008068319880103.

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Here we develop the uniformly minimum variance unbiased (best) estimators of coefficient of variation, Pearson's coefficients of skewness and kurtosis of two-parameter Pareto distribution, the variance of these best estimators and the best estimators of those variances. The best estimators are in terms of Kummer's function 1 F1 and Humbert's function ø2 ; and their variances are in terms of F2 , the Appel function of second kind and K 12 , a quadruple hypergeornetric function invented by Exton during the early 1970's.

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28

Sampaio, Nilo Antônio S., Felipe Cury Mazza, Sílvio Sérgio Silveira de Siqueira, João Ercio Miranda Junior, João Victor de Souza Moutinho, and Lucas de Oliveira Pacífico. "Applications of Correlation Analysis in Environmental Problems." Revista de Gestão Social e Ambiental 18, no. 3 (2024): e04925. http://dx.doi.org/10.24857/rgsa.v18n3-085.

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Objective: The aim of this work is to show the application of the Correlation Coefficient (Pearson, Spearman) to environmental problems. Theoretical framework: Although the concepts of correlation and regression are intimately related, they are nevertheless different. Correlation may be described as the degree of association between two variables, whereas regression expresses the form of the relationship between specified values of one (the independent, exogenous, explanatory, regressor, carrier or predictor) variable and the means of all corresponding values of the second (the dependent, outc

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29

Mudelsee, Manfred. "Estimating Pearson's Correlation Coefficient with Bootstrap Confidence Interval from Serially Dependent Time Series." Mathematical Geology 35, no. 6 (2003): 651–65. http://dx.doi.org/10.1023/b:matg.0000002982.52104.02.

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30

Ahlgren, Per, Bo Jarneving, and Ronald Rousseau. "Requirements for a cocitation similarity measure, with special reference to Pearson's correlation coefficient." Journal of the American Society for Information Science and Technology 54, no. 6 (2003): 550–60. http://dx.doi.org/10.1002/asi.10242.

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31

Wan, Zixin. "Analysis and Prediction of Wordle Dataset Based on ARIMA and Pearson's Correlation Coefficient." Frontiers in Computing and Intelligent Systems 3, no. 2 (2023): 39–43. http://dx.doi.org/10.54097/fcis.v3i2.7082.

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In this paper, a time series analysis was performed to ensure the parameters p, d, and q. Finally, the ARIMA (1,1,0) model was chosen to create a prediction interval for the number of outcomes to be reported in the future. The results of the precision test showed good confidence in the prediction with a goodness-of-fit of 98.2%. the prediction interval for March 1, 2023 was [10103,10523]. In addition, this paper used Pearson's correlation coefficient and chi-square test to verify the correlation between each attribute of the word and the percentage of scores in the hard model. In summary, this

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32

Pestman, Wiebe R. "Creating and classifying measures of linear association by optimization techniques." MATHEMATICA SCANDINAVICA 106, no. 1 (2010): 67. http://dx.doi.org/10.7146/math.scand.a-15125.

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The idea of measures of linear association, such as Pearson's correlation coefficient, can be put in a general framework by axiomization. Groups of linear transformations on $\mathsf{R}^n$ can be exploited to create new and classify existing measures according to their invariance properties. Thus invariance under the Euclidean transformation group leads to the class of so-called geometric measures. Similarly, a measure is called algebraic if it is invariant under scalings. Pearson's coefficient is an example of an algebraic measure; it is not geometric. It is proved that, generally, a measure

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33

Matusin, Daniel Patterson, Aldo José Fontes-Pereira, Paulo Tadeu Cardozo Ribeiro Rosa, et al. "EXPLORING CORTICAL BONE DENSITY THROUGH THE ULTRASOUND INTEGRATED REFLECTION COEFFICIENT." Acta Ortopédica Brasileira 26, no. 4 (2018): 255–59. http://dx.doi.org/10.1590/1413-785220182604177202.

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ABSTRACT Objective: This work evaluates the relationship between ultrasonic reflection and bone density from fourteen cylindrical bovine cortical bone samples (3.0-cm thick). Methods: Twenty US reflection signals per sample were acquired along the bone surface (2.0-mm step). The Integrated Reflection Coefficient (IRC) from each signal was compared to Quantitative Computed Tomography (QCT). Results: Seven IRC and QCT curves presented Pearson's Correlation R-values above 0.5. For weak correlation curves, QCT and IRC showed similar trends in several segments. Conclusion: IRC was sensitive to bone

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Silveira, Paulo Sergio Panse, and Jose Oliveira Siqueira. "Histogram lies about distribution shape and Pearson's coefficient of variation lies about relative variability." Quantitative Methods for Psychology 18, no. 1 (2022): 91–111. http://dx.doi.org/10.20982/tqmp.18.1.p091.

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35

Bartlett, R. F. "Linear Modelling of Pearson's Product Moment Correlation Coefficient: An Application of Fisher's z-Transformation." Statistician 42, no. 1 (1993): 45. http://dx.doi.org/10.2307/2348110.

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36

Kharchenko, A., and A. Yelinska. "DNA typing of the gastric mucosa of patients with chronic duodenal ulcer." Journal of Education, Health and Sport 11, no. 11 (2021): 221–30. http://dx.doi.org/10.12775/jehs.2021.11.11.022.

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The work involved a molecular biological technique (ISSR-PCR) using ISSR-primer S-2, with structure (AGC) 6G. Changes in the gastric mucosa in chronic duodenal ulcer disease against the background of severe chronic atrophic gastritis have been analyzed. Noteworthy is the fact that there is a strong correlation between the degree of dysplasia of the epithelium of the gastric mucosa and the mitotic index, the Pearson's correlation coefficient rxy was 0.853, respectively. A strong and very strong correlation relationship between the indicators of the degree of dysplasia of the epithelium of the g

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37

Pathirikattu, Aiswaria, Teja Reddy Vakamalla, and Narasimha Mangadoddy. "Predictive models for hydrocyclone performance parameters: Evaluating the impact of training functions using artificial neural network." Mineral Processing and Extractive Metallurgy: Transactions of the Institutions of Mining and Metallurgy 133, no. 4 (2024): 147–59. https://doi.org/10.1177/25726641241300618.

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This study introduces a multilayer perceptron artificial neural network model to predict water split, cut size and sharpness of separation in hydrocyclone classifiers. The model is developed based on experimental data from 75, 100, 150 and 250 mm diameter hydrocyclones under different operating conditions and design parameters. The Levenberg–Marquardt training algorithm is found to be optimal based on the correlation coefficient and mean square error values. Pearson's correlation coefficient is used to assess the strength and direction between variables. The importance of input variables is es

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38

Kumar, Mohit. "Measuring Pearson's correlation coefficient of fuzzy numbers with different membership functions under weakest t-norm." International Journal of Data Analysis Techniques and Strategies 12, no. 2 (2020): 172. http://dx.doi.org/10.1504/ijdats.2020.10028008.

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Kumar, Mohit. "Measuring Pearson's correlation coefficient of fuzzy numbers with different membership functions under weakest t-norm." International Journal of Data Analysis Techniques and Strategies 12, no. 2 (2020): 172. http://dx.doi.org/10.1504/ijdats.2020.106642.

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Hawrył, Mirosław A., Ryszard Świeboda, Anna Hawrył, Małgorzata Niemiec, and Monika Waksmundzka-Hajnos. "Micro Thin-Layer Chromatography Fingerprints of Selected Basil Species and Their Chemometric Analysis." Journal of AOAC INTERNATIONAL 100, no. 4 (2017): 916–21. http://dx.doi.org/10.5740/jaoacint.17-0166.

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Abstract The dried aerial parts of 12 plants of Ocimum spp. were extracted with the Soxhlet apparatus using dichloromethane and methanol as solvents. A micro-TLC system with silica and a normal-phase solvent system (propan-2-ol–n-heptane–formic acid) was used for the chemometric analysis of 12 selected basil methanolic extracts. Some indices of similarity (Pearson's correlation coefficient, determination coefficient, congruence coefficient, and Euclidean, Manhattan (city-block), Chebyshev, and Hausdorff distances) were calculated on the basis of thin-layer chromatograms using ImageJ software.

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41

Liao, Yifeng. "Application of portfolio optimization." BCP Business & Management 38 (March 2, 2023): 1538–43. http://dx.doi.org/10.54691/bcpbm.v38i.3929.

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Portfolio optimization, as the basis for quantitative investment finance, has become a fundamental topic in modern finance. Consequently, the portfolio constructing, and optimization is always a hotspot in the modern finance area. This paper concentrates on the application and analysis of portfolio optimization. Asset diversification plays a crucial role in examining how to improve the performance of a portfolio. To achieve portfolio diversification, this paper calculate the correlation coefficient matrix of the seven selected assets and look for smaller correlation coefficients. By referring

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42

Devos, Anastasiia, Iryna Onofriichuk, Iryna Fedoryshyna, Tetiana Dubovyk, and Iryna Buchatska. "The Role of Language in the Effectiveness of Social Advertising." Forum for Linguistic Studies 6, no. 5 (2024): 737–48. http://dx.doi.org/10.30564/fls.v6i5.7036.

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The study aims to analyse and evaluate language's role in shaping social advertising's effectiveness from a linguistic perspective. Methods. The survey method, the method of linguistic analysis and classification of linguistic strategies and techniques, and the Weissman-Ricks Emotional State Inventory (WRESI) were used in the study. The statistical analysis was carried out using the Pearson criterion. The validity of the methods was tested using Cronbach's coefficient. Results. 52% of advertising materials contain emotional words. This result indicates a strong reaction from the audience, whic

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HUANHUAN, TIAN, XUE YU, LIANG YUJUAN, and KANG SANJUN. "STOCHASTIC DRIVING AND COUPLING CONTROL METHOD TO SUPPRESS SPIRAL WAVES AND SPATIOTEMPORAL CHAOS AND ANALYSIS OF CORRELATION." International Journal of Bifurcation and Chaos 19, no. 03 (2009): 1081–86. http://dx.doi.org/10.1142/s0218127409023500.

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In this paper, the stochastic driving and coupling method to effectively suppress the turbulence and spiral waves is proposed. It is confirmed that the drive system ensures the response achieves complete synchronization via the computation of the Pearson's coefficient γ. The minimum time units of achieving complete synchronization N versus the coupling proportion P takes on the power-law N ~ P-k.

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44

Orlandi, Aline Cristina, Fernanda Pontes Cardoso, Lucas Macedo Santos, et al. "Translation and cross-cultural adaptation of the Scleroderma Health Assessment Questionnaire to Brazilian Portuguese." Sao Paulo Medical Journal 132, no. 3 (2014): 163–69. http://dx.doi.org/10.1590/1516-3180.2014.1323621.

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CONTEXT AND OBJECTIVE:Systemic sclerosis is an autoimmune disease characterized by abnormalities of vascularization that may cause fibrosis of the skin and other organs and lead to dysfunction. It is therefore essential to have tools capable of evaluating function in individuals with this condition. The aim of this study was to translate the Scleroderma Health Assessment Questionnaire (SHAQ) into Portuguese, adapt it to Brazilian culture and test its validity and reliability.DESIGN AND SETTING:The validation of SHAQ followed internationally accepted methodology, and was performed in university

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45

Querino, Carlos Alexandre Santos, Marcelo Sacardi Biudes, Nadja Gomes Machado, Juliane Kayse Albuquerque da Silva Querino, Marcos Antônio Lima Moura, and Péricles Vale Alves. "Modelling parametrization to estimate atmospheric long wave radiation in the Northern Mato Grosso, Brazil." Ciência e Natura 42 (May 9, 2020): e105. http://dx.doi.org/10.5902/2179460x41205.

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The measures of Atmospheric Long Wave radiation are onerous, which brings the necessity to use alternative methods. Thus, the main aim of this paper was to test and parameterize some models that exist in the literature to estimate atmospheric long wave. The data were collected at Fazenda São Nicolau (2002 - 2003), located in Northwestern of Mato Grosso State. Data were processed hourly, monthly, and seasonal (dry and wet) besides clear and partly cloudy days on the average. The models of Swinbank, Idso Jackson, Idso, Prata and Duarte. were applied. The performance of the models was based on th

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46

Wang, Jianji, and Nanning Zheng. "A Novel Fractal Image Compression Scheme With Block Classification and Sorting Based on Pearson's Correlation Coefficient." IEEE Transactions on Image Processing 22, no. 9 (2013): 3690–702. http://dx.doi.org/10.1109/tip.2013.2268977.

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47

Jumaah, Mustafa, Ali A. Yassin, Zaid Ameen Abduljabbar, Muwafaq Jawad, Vincent Omollo Nyangaresi, and Ali Hassan Ali. "Amalgamating Ensemble Machine Learning Soft Voting Classifier, SMOTE, and Pearson's Correlation Coefficient for Enhanced Malware Detection." Engineering, Technology & Applied Science Research 15, no. 3 (2025): 22746–52. https://doi.org/10.48084/etasr.10420.

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Obfuscated malware poses a significant threat to personal and IoT devices, and traditional detection methods often face significant challenges and weaknesses in their capabilities and performance. This study proposes a malware detection approach using Machine Learning (ML) algorithms and a soft voting ensemble technique, enhanced by the Pearson's correlation coefficient for feature selection on the CIC-MalMem-2022 dataset. It addresses data imbalances with the Synthetic Minority Oversampling Technique (SMOTE) method and employs various ML classifiers. The results demonstrate improved accuracy,

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48

Shantal, Mohamed, Zalinda Othman, and Azuraliza Abu Bakar. "Impact of Missing Data on Correlation Coefficient Values: Deletion and Imputation Methods for Data Preparation." Malaysian Journal of Fundamental and Applied Sciences 19, no. 6 (2023): 1052–67. http://dx.doi.org/10.11113/mjfas.v19n6.3098.

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The correlation coefficient is one of the essential statistical techniques used to discover relationships among variables. Various techniques can quantify correlation, such as Pearson's, Spearman's, and Kendall's correlation coefficients, depending on the data type. As with any use of data, missing data will impact the availability of data, reducing it and potentially affecting the results. Furthermore, the removal of missing-value data from the study when using complete case analysis or available case analysis may result in selection biases. In this paper, we investigate the impact of missing

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Ejegwa, Paul Augustine, Nasreen Kausar, John Abah Agba, Francis Ugwuh, Emre Özbilge, and Ebru Ozbilge. "Determination of medical emergency via new intuitionistic fuzzy correlation measures based on Spearman's correlation coefficient." AIMS Mathematics 9, no. 6 (2024): 15639–70. http://dx.doi.org/10.3934/math.2024755.

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<abstract><p>Uncertainty in medical diagnosis is the main challenge in medical emergencies (MEs) experienced by triage nurses and physicians in the emergency department (ED). The intuitionistic fuzzy correlation coefficient (IFCC) approach is used to analyze and interpret the relationship between variables in an uncertain environment. Assorted methods that involve applying a correlation coefficient under intuitionistic fuzzy sets (IFSs) were constructed based on Pearson's correlation model with various drawbacks. In this work, we construct two new intuitionistic fuzzy correlation m

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JANG, EUN-SUK, and CHUN-WON KANG. "SHORT NOTES: CAN THE PHYSICAL PROPERTIES OF WOOD SAMPLES BE PREDICTED FROM PHOTOGRAPHS DISPLAYED ON A MONITOR?" WOOD RESEARCH 67(5) 2022 67, no. 5 (2022): 888–93. http://dx.doi.org/10.37763/wr.1336-4561/67.5.888893.

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This study focused on evaluatingthe physical properties of wood from photographs displayed on a monitor. Sample photos of 475 hardwoods and their physical information were collected from a wood database. R, G, and B values were extracted from the wood photos using color picker software.Statistical techniques such as Pearson's correlation coefficient and multiple regression analysis were applied to investigate relationships between wood color and physical properties. From results of Pearson's correlation coefficient, R, G, and B values were most affected by specific gravity. In a multiple regre

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