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Simple linear regression is a statistical method used to model the linear relationship between an independent variable and a dependent variable.
This is done so that the relationship (if any) between the variables is easily seen. [4] For example, bivariate data on a scatter plot could be used to study the relationship between stride length and length of legs. In a bivariate correlation, outliers can be incredibly problematic when they involve both extreme scores on both variables.
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Univariate distribution is a dispersal type of a single random variable described either with a probability mass function (pmf) for discrete probability distribution, or probability density function (pdf) for continuous probability distribution. [14] It is not to be confused with multivariate distribution.