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We have developed a data mining and visualization software package we call SpectraMiner that makes it possible to handle hundreds of clusters, limiting loss of information and thus overcoming the boundaries set by traditional statistical data analysis approaches.
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These gene-gene interactions are also denoted as epitasis in which this phenomenon cannot be solved by traditional statistical method due to the high dimensionality of the data and the occurrence of multiple polymorphism.
However, the computation of a correlation coefficient between high-dimensional data and such parameters is not covered by traditional statistical methods.
This relatively new technology helps geographers address issues which have been poorly handled by traditional statistical techniques in the past, such as scale, space time dependencies, nonlinear relationships, and data outliers.
These studies highlight the benefits of applying more robust techniques in solving problems previously resolved by traditional statistical modelling.
Such differences may be missed by traditional statistical testing methods such as an F-test.
Uncertainty due to sampling variation was handled by traditional statistical methods in most evaluations.
This approach overcomes problems faced by traditional statistical models of colinearity and overfitting.
Various studies have been done on road accident data analysis using traditional statistical techniques and data mining techniques.
The amounts of data collected and processed by these new-generation instruments have increased dramatically, rendering insufficient the traditional methods of statistical data analysis.
The significance of race as a powerful factor among the young is supported by statistical data.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com