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Introduction tp the t Statistic (The t statistic (:red_cross: it is used…
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Correlation
:green_cross: A correlation measures the relationship between two variables, X and Y.
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Pearson correlation
:green_cross: the most commonly used correlation
:green_cross: it measures the degree of linear relationship.
:green_cross: the Pearson correlation is identified by the letter r
:green_cross: SP is the sum of products of deviations and can be calculated with either a definitional formula or a computational formula
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The Spearman correlation
:green_cross: measures the consistency of direction in the relationship between X and Y—that is, the degree to which the relationship is one-directional, or monotonic
The Spearman correlation is computed by a two-stage process:
:green_cross: Rank the X scores and the Y scores separately
:green_cross: Compute the Pearson correlation using the ranks.
:green_cross: a correlation between two variables should not be interpreted as implying a causal relationship.
:green_cross: simply because X and Y are related does not mean that X causes Y or that Y causes X.
:green_cross: to evaluate the strength of a relationship, you square the value of the correlation.
:green_cross: the resulting value, r squared , is called the coefficient of determination because it measures the portion of the variability in one variable that can be determined using the relationship with the second variable.