STAT 3006 Lecture Notes - Lecture 15: Robust Statistics, Dependent And Independent Variables
14 Oct 2018
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Two variables are associated if knowing the value for one variables gives you information about the value for the other. This is often discussed as a response variable against an explanatory variable. A response variable (x-axis) measures the outcome of interest, while an explanatory variable (y-axis) is the variable thought to explain the response. They provide a simple graphical basis for evaluating the extent of association. The correlation coefficient is a numerical measure of the association. (cid:2200)= ((cid:2206) (cid:2206) (cid:2201)(cid:2206) )(cid:4678)(cid:2207) (cid:2207) (cid:2201)(cid:2207) (cid:4679) r is always [ ,], where r > 0 indicates a positive relationship and r < 0 indicates a negative relationship. r = 0 indicates no relationship, and r. = -1 or r = 1 occurs if there is a perfect relationship. Beware that correlation requires that both variables are quantitative. It is not a complete summary of two-variable data.
