Pearson's or Spearman's Correlation Coefficient - Which One to Use?

Rebekić, Andrijana; Lončarić, Zdenko; Petrović, Sonja; Marić, Sonja

doi:10.18047/poljo.21.2.8

Cited by 87 publications

(52 citation statements)

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“…Con respecto al coeficiente de correlación de Spearman es una medida no paramétrica de relaciones entre variables usando rangos para calcular la correlación. La correlación de Spearman afirma que la relación entre dos variables puede ser descrita utilizando funciones monotónicas (Rebekić et al, 2015).…”

Section: Análisis De Resultadosunclassified

Compromiso activo y valor de marca en el sector del lujo

Ramos

Camahort

Durán

2019

Redmarka Rev Mark Apl

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El presente artículo pretende analizar la relación entre diversas dimensiones (notoriedad, lealtad, imagen y compromiso) y cómo éstas afectan al valor de marca en el sector del lujo. Para ello se realizaron un total de 310 encuestas válidas a personas que hubieran adquirido o consumido marcas de lujo. En este estudio se presentan cinco hipótesis distintas con las que se busca establecer la existencia de las relaciones entre dimensiones planteadas, sus intensidades, y cómo afectan al valor de marca en el sector del lujo. El artículo contribuye, principalmente, a clarificar los efectos del compromiso activo, una dimensión novedosa en el estudio del valor de marca. Posteriormente, se presentarán las conclusiones obtenidas y sugerencias para futuras investigaciones empíricas.

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Section: Análisis De Resultadosunclassified

Compromiso activo y valor de marca en el sector del lujo

Ramos

Camahort

Durán

2019

Redmarka Rev Mark Apl

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“…The study also used Spearman's rank correlation coefficient, which has been defined as the Pearson correlation coefficient calculated for the variable ranks [43] (the rank is the number that corresponds to the place in the order of each feature). The difference also applies to the fact that it measures any monotonous dependence [44], including if the features are qualitative. It is designated by the following formula [45]:…”

Section: Selection Of the Sample In The Study And The Methodology Of mentioning

confidence: 99%

Analysis of the Risk Impact of Implementing Digital Innovations for Logistics Management

2019

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The emergence of digital technology is a paradigmatic historical change. As a process of transforming social engineering structures, digitization has had a ubiquitous impact on the organization of structures and business logic, as well as on economic principles and rules. The fertile ground for digital technology applications is logistics management, which manifests itself in the dynamic development of logistics 4.0. Increasingly, it is pointed out that digital technology has some distinct features that have fundamental implications for innovation. The aim of the present study is to determine the impact of the risk of implementing digital technologies for logistics management. The study was conducted using the standardized questionnaire interview method with representatives of the management of enterprises. The attempt was random. The sampling was made up of micro, small, medium, and large enterprises from the production and services sectors, having a logistics unit or a logistics division, located in the “Bisnode Poland” database. In total, 360 full interviews were carried out. For the study, we defined macro-environment, operational, functional, and microenvironment risks. The basic conclusion is that between each type of risk and the type of digital technologies used in the studied entities and their partners in the supply chain, there is a high and very high dependence in the case of three-dimensional printing (3D printing), artificial intelligence, blockchain, drones, augmented reality, and self-propelled vehicles.

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“…Spearman's coefficients were calculated to evaluate the magnitude and significance of the correlations between the remotely sensed covariates and the nMDS axis-1 scores (α = 0.05). We have chosen this association measure considering that our response variable was calculated with a rank based method (nMDS), and likewise, it was used to mitigate the outliers effect, and facilitate the application to non-normal data distributions [73].…”

Section: Correlation Testmentioning

confidence: 99%

Beta-Diversity Modeling and Mapping with LiDAR and Multispectral Sensors in a Semi-Evergreen Tropical Forest

Ochoa-Franco

Valdez-Lazalde

Ángeles‐Pérez

et al. 2019

Forests

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Tree beta-diversity denotes the variation in species composition at stand level, it is a key indicator of forest degradation, and is conjointly required with alpha-diversity for management decision making but has seldom been considered. Our aim was to map it in a continuous way with remote sensing technologies over a tropical landscape with different disturbance histories. We extracted a floristic gradient of dissimilarity through a non-metric multidimensional scaling ordination based on the ecological importance value of each species, which showed sensitivity to different land use history through significant differences in the gradient scores between the disturbances. After finding strong correlations between the floristic gradient and the rapidEye multispectral textures and LiDAR-derived variables, it was linearly regressed against them; variable selection was performed by fitting mixed-effect models. The redEdge band mean, the Canopy Height Model, and the infrared band variance explained 68% of its spatial variability, each coefficient with a relative importance of 49%, 32.5%, and 18.5% respectively. Our results confirmed the synergic use of LiDAR and multispectral sensors to map tree beta-diversity at stand level. This approach can be used, combined with ground data, to detect effects (either negative or positive) of management practices or natural disturbances on tree species composition.

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Pearson's or Spearman's Correlation Coefficient - Which One to Use?

Cited by 87 publications

References 0 publications

Compromiso activo y valor de marca en el sector del lujo

Compromiso activo y valor de marca en el sector del lujo

Analysis of the Risk Impact of Implementing Digital Innovations for Logistics Management

Beta-Diversity Modeling and Mapping with LiDAR and Multispectral Sensors in a Semi-Evergreen Tropical Forest

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