Effective use of Pearson's product–moment correlation coefficient

Puth, Marie-Therese; Neuhäuser, Markus; Ruxton, Graeme D.

doi:10.1016/j.anbehav.2014.05.003

Cited by 323 publications

(193 citation statements)

References 11 publications

Supporting

Mentioning

184

Contrasting

Unclassified

Order By: Relevance

“…The Yingkou road segment contained the highest concentrations of Cu and Zn. High concentrations of Cu in this segment may be attributed to Pearson's correlation coefficient is frequently used to express the correlation between elements and indicate their potential sources [27]. The correlation coefficients between the heavy metals in this study are listed in Sample strips were divided into three classes according to land use type: Class A is cultivated land, with crops such as rice and corn; Class B is orchard and forested land, with trees being the dominant vegetation type; and Class C contains orchard and forested land, as well as some industrial land on the eastern side of the sample strip.…”

Section: Heavy Metal Concentrations In Soilsmentioning

confidence: 99%

Assessment of Heavy Metal Contamination in Roadside Soils Along the Shenyang-Dalian Highway in Liaoning Province, China

Zhang

Caiqiu²,

Gong

et al. 2017

Pol. J. Environ. Stud.

View full text Add to dashboard Cite

Heavy metal contaminations were assessed through a detailed soil survey in roadside soils along the Shenyang-Dalian Highway of Liaoning Province, China. Pb, Cu, Cd, Ni, and Zn were analyzed using atomic absorption spectrophotometry. The average concentrations of Pb, Cu, Cd, Ni, and Zn in roadside soils were 43.8, 26.5, 0.119, 32.1, and 71.3 mg/kg, respectively, and all concentrations exceeded the background values. Different heavy metal distribution patterns were found under different land use types. In farmland, a peak metal concentration occurred 25 m from the roadside soil, while in the forest and orchard soil all heavy metals decreased with distance from the roadside, which conformed to the exponential model. Heavy metal concentrations were markedly higher than those measured in 1999 and 2007, except for Cd. Concentrations in soils along the Shenyang-Dalian Highway were medium or low in comparison with roadside soils in other cities around the world. Overall, this assessment illustrates that heavy metal pollution in these soils is generally low, and we recommend that more attention should be given to Pb contamination in roadside soils along the Shenyang-Dalian Highway.

show abstract

Section: Heavy Metal Concentrations In Soilsmentioning

confidence: 99%

Assessment of Heavy Metal Contamination in Roadside Soils Along the Shenyang-Dalian Highway in Liaoning Province, China

Zhang

Caiqiu²,

Gong

et al. 2017

Pol. J. Environ. Stud.

View full text Add to dashboard Cite

show abstract

“…The value ranges from 1 (indicating perfect positive correlation) to -1 (indicating perfect negative correlation) (Puth et al 2014). The regression analysis proposes to verify the existence of a functional relationship between a dependent variable and an independent variable.…”

Section: Statistical Analyzesmentioning

confidence: 99%

ALTIMETRY ASSESSMENT OF ASTER GDEM v2 AND SRTM v3 DIGITAL ELEVATION MODELS: A CASE STUDY IN URBAN AREA OF BELO HORIZONTE, MG, BRAZIL

et al. 2017

View full text Add to dashboard Cite

Abstract:This work is an altimetry evaluation study involving Digital Elevation Models ASTER GDEM version 2 and SRTM version 3. Both models are readily available free of charge, however as they are built from different remote sensing methods it is also expected that they present different data qualities. LIDAR data with 25 cm vertical accuracy were used as reference for assessment validation. The evaluation study, carried out in urbanized area, investigated the distribution of the residuals and the relationship between the observed errors with land slope classes. Remote sensing principles, quantitative statistical methods and the Cartographic Accuracy Standard of Digital Mapping Products (PEC-PCD) were considered. The results indicated strong positive linear correlation and the existence of a functional relationship between the evaluated models and the reference model. Residuals between -4.36 m and 3.11 m grouped 47.7% of samples corresponding to ASTER GDEM and 63.7% of samples corresponding to SRTM. In both evaluated models, Root Mean Square Error values increased with increasing of land slope. Considering 1: 50,000 mapping scale the PEC-PCD classification indicated class B standard for SRTM and class C for ASTER GDEM. In all analyzes, SRTM presented smaller altimetry errors compared to ASTER GDEM, except in areas with steep relief.Keywords: Digital Elevation Models; ASTER GDEM v2; SRTM v3; Altimetry Assessment.

show abstract

“…Movements performed in previous studies that were found to be affected by the presence of LBP were simulated to confirm that Kinect could distinguish ROM and velocity features during these tasks. Except for the ROM of LS and MAV of RS without limitation, Kinect's performance was sufficient for the tasks [19,20]. The PCC values of ROM of RS and EE in both states were larger than 0.9 with significant correlations, showing that Kinect was able to obtain accurate measurements in data acquisition of the human skeleton.…”

Section: Discussionmentioning

confidence: 80%

Evaluation of Kinect as an Analysis Tool for Kinematic Variables of Shoulder and Spine Motions

Duan¹,

Xiao²,

Wang³

2015

JMRD

View full text Add to dashboard Cite

Abstract-Specific kinematic actions of the spine and shoulder are useful for low back pain (LBP) assessment and treatment. However, the widespread application of motion capture systems in clinical settings is limited by the tedious process and expensive equipment. As a cost-effective and portable device, Kinect has the potential to be used in clinical analysis and rehabilitation for patients with LBP. Using Kinect and a motion capture system, 10healthysubjectsperformed left/right bending and extension tasks five times successively with and without simulated motion limitations. The mean range of motion (ROM)and maximum angular velocity (MAV) were then calculated. The results revealed that the Pearson's correlation coefficient was more than 0.7 with ROM. The root-meansquare error (RMSE) of the ROM difference, with and without motion limitation, was1.2  -3  (for MAV: 4.7  /s-14.6  /s). In conclusion, Kinect can be used as an analysis tool for kinematic variability of shoulder and trunk motion, which could help obtain low back information regarding movement patterns and strategies under various movement tasks.

show abstract

Effective use of Pearson's product–moment correlation coefficient

Cited by 323 publications

References 11 publications

Assessment of Heavy Metal Contamination in Roadside Soils Along the Shenyang-Dalian Highway in Liaoning Province, China

Assessment of Heavy Metal Contamination in Roadside Soils Along the Shenyang-Dalian Highway in Liaoning Province, China

ALTIMETRY ASSESSMENT OF ASTER GDEM v2 AND SRTM v3 DIGITAL ELEVATION MODELS: A CASE STUDY IN URBAN AREA OF BELO HORIZONTE, MG, BRAZIL

Evaluation of Kinect as an Analysis Tool for Kinematic Variables of Shoulder and Spine Motions

Contact Info

Product

Resources

About