Markenführung auf Augenhöhe

Bruce, Annette

doi:10.1365/s35173-012-0273-7

Cited by 1 publication

(2 citation statements)

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“…Thus, variables X and Y are said to be positively correlated if high values of X are associated with high values of Y, and low values of X are associated with low values of Y. In contrast, if high values of X are associated with low values of Y, and vice versa, the variables are negatively correlated [ 21 ]. Correlation coefficients range from −1 (for a negative correlation) to +1 (for a positive correlation)—correlations close to 0 indicate the absence of a linear correlation between two variables [ 22 ].…”

Section: Methodsmentioning

confidence: 99%

“…As a general rule, linear correlation studies precede the generation of linear regression models, after the confirmation of a correlation between variables. The difference is that while correlation measures the strength of an association between two variables, regression quantifies the nature of the relationship [ 21 ]. Therefore, it is useful to calculate a correlation matrix showing all the variables in rows and columns, in which the intersection values quantify the correlation between them.…”

Section: Methodsmentioning

confidence: 99%

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The Relationship between VO2max, Power Management, and Increased Running Speed: Towards Gait Pattern Recognition through Clustering Analysis

Pardo

Mir-Jimenez

Moreno³

et al. 2021

Sensors

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Triathlon has become increasingly popular in recent years. In this discipline, maximum oxygen consumption (VO2max) is considered the gold standard for determining competition cardiovascular capacity. However, the emergence of wearable sensors (as Stryd) has drastically changed training and races, allowing for the more precise evaluation of athletes and study of many more potential determining variables. Thus, in order to discover factors associated with improved running efficiency, we studied which variables are correlated with increased speed. We then developed a methodology to identify associated running patterns that could allow each individual athlete to improve their performance. To achieve this, we developed a correlation matrix, implemented regression models, and created a heat map using hierarchical cluster analysis. This highlighted relationships between running patterns in groups of young triathlon athletes and several different variables. Among the most important conclusions, we found that high VO2max did not seem to be significantly correlated with faster speed. However, faster individuals did have higher power per kg, horizontal power, stride length, and running effectiveness, and lower ground contact time and form power ratio. VO2max appeared to strongly correlate with power per kg and this seemed to indicate that to run faster, athletes must also correctly manage their power.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%