Pearson Correlation Coefficient

Benesty, Jacob; Chen, Jingdong; Huang, Yiteng; Cohen, Israel

doi:10.1007/978-3-642-00296-0_5

Cited by 2,271 publications

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“…Similarly to the Intergovernmental Panel on Climate Change 5th assessment report [Flato et al, 2013], we quantitatively evaluate simulated orographic rainfall over the HM and GB (Figure 1b denoted by the purple box) using the Pearson Correlation Coefficient (PCC) [Benesty et al, 2009]. Our correlations are based on the mean of APHRODITE and TRMM.…”

Section: Methodsmentioning

confidence: 99%

The neglected Indo‐Gangetic Plains low‐level jet and its importance for moisture transport and precipitation during the peak summer monsoon

Acosta

Huber

2017

Geophysical Research Letters

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Accurately simulating the Indo‐Asian monsoon (IAM) using atmospheric general circulation models (AGCMs) is challenging but crucial. This study uses reanalysis products European Centre of Medium‐Range Forecast Interim reanalysis, Japanese Reanalysis year 55, and High Asia Reanalysis to highlight an easterly, low‐level barrier jet along the Indo‐Gangetic Plain (referred from here as IG LLJ), which we identify as the primary moisture transport mechanism for the northeastern branch of the IAM. We show that the NCAR family of AGCMs (Community Atmospheric Model (CAM)) does not capture this circulation until 1/2° or greater spatial horizontal resolution is used. The IG LLJ develops due to a persistent low‐pressure system centered over the Ganges basin and is enhanced by the Himalayas. Using diabatic heating rates and the moist Froude number as diagnostics, we find that in CAM, this branch of the IAM displays two different dynamical regimes as a function of resolution. At low resolution, the atmosphere near the Himalayas is statically unstable, diabatic heating is strong, and the moisture flow is southwesterly from the Arabian Sea and moves over the terrain (unblocked). At high resolution, the moist static stability near the Himalayan Mountains is stable, diabatic heating is weak, and the flow primarily enters easterly from the Bay of Bengal and moves parallel to the terrain (blocked). During the summer season, the low‐resolution CAM is locked into the unblocked mode, which has serious implications for interpreting topography‐monsoon interactions. For a broader context, we demonstrate that more than half of the CMIP5 models do not capture the IG LLJ, which further highlights model‐data mismatch across the IAM region.

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Section: Methodsmentioning

confidence: 99%

The neglected Indo‐Gangetic Plains low‐level jet and its importance for moisture transport and precipitation during the peak summer monsoon

Acosta

Huber

2017

Geophysical Research Letters

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“…The value of correlation coefficient varies from +1 to −1 corresponding to a high positive correlation to a high negative linear correlation. While the coefficient relates to 0, it means there is nearly no linear correlation between X and Y [34]. Conventional ordinary least squared multiple linear regression (OLS) model and Spatial Autoregressive (SAR) model are selected to compare with ESF model.…”

Section: Validationmentioning

confidence: 99%

A Segmented Processing Approach of Eigenvector Spatial Filtering Regression for Normalized Difference Vegetation Index in Central China

Yang

Chen

et al. 2018

IJGI

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Abstract:A segmented processing approach of eigenvector spatial filtering (ESF) regression is proposed to detect the relationship between NDVI and its environmental factors like DEM, precipitation, relative humidity, precipitation days, soil organic carbon, and soil base saturation in central China. An optimum size of 32 × 32 is selected through experiments as the basic unit for image segmentation to resolve the large datasets to smaller ones that can be performed in parallel and processed more efficiently. The eigenvectors from the spatial weights matrix (SWM) of each segmented image block are selected as synthetic proxy variables accounting for the spatial effects and aggregated to construct a global ESF regression model. Results show precipitation and humidity are more influential than other factors and spatial autocorrelation plays a vital role in vegetation cover in central China. Despite the increase in model complexity; the parallel ESF regression model performs best across all performance criteria compared to the ordinary least squared linear regression (OLS) and spatial autoregressive (SAR) models. The proposed parallel ESF approach overcomes the computational barrier for large data sets and is very promising in applying spatial regression modeling to a wide range of real world problem solving and forecasting.

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“…This experiment used the Pearson correlation analysis [16] to explore whether or not a linear relationship exists between academic performance and personality. Statistically, if the absolute value of the coefficient is greater than 0.7, it is believed that a linear relationship exists.…”

Section: B Pearson Correlationmentioning

confidence: 99%

Influence of Introversion and Extraversion Using MBTI Personality Model on Academic Performance

Li¹,

Sardinas²,

Shih³

et al. 2018

IJIET

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Abstract-To date, research work in exploring the influence of personality on performance in programming courses has often been neglected due to the difficulty of quantitatively defining and measuring human factors. In this paper an empirical experiment was conducted in: (1) measuring Introversion/Extraversion personality types based on Myers-Briggs Type Indicator(MBTI); (2) defining scores of students' assignments as academic performance; and (3) using statistical analysis to verify our hypotheses about the linear relationship between personality types and academic performance. With the support of Independent T-test analysis, conclusions were found that introversion programmers outperformed extroversion programmers in their respective programming courses. In addition, the Pearson Correlation and regression analysis were utilized in order to assist educators in conducting more effective teaching styles in their programming courses.Index Terms-Academic performance, empirical study, extraversion, introversion, Myers-Briggs type indicator.

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Pearson Correlation Coefficient

Cited by 2,271 publications

References 0 publications

The neglected Indo‐Gangetic Plains low‐level jet and its importance for moisture transport and precipitation during the peak summer monsoon

The neglected Indo‐Gangetic Plains low‐level jet and its importance for moisture transport and precipitation during the peak summer monsoon

A Segmented Processing Approach of Eigenvector Spatial Filtering Regression for Normalized Difference Vegetation Index in Central China

Influence of Introversion and Extraversion Using MBTI Personality Model on Academic Performance

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