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The amount can only reflect a linear correlation of variables and ignores a variety of relationships or correlations with covariance. Being an example- Someone would want the height and age of the teen from an adult age to have a correlation coeffective knowingly better than 0, but fewer than one.
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It is clear to determine cases that seem like outliers. The multivariable correlations system is made to abridge two or even more areas of numeric data. It figures out the summary for every variable that is definitely correlated and covariances involving the variables.
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