Notes 8 - Cautions about Correlation and Regression Submitted by gfj100 on Fri 09:50 Influence Outliers In most practical circumstances an outlier

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Cautions about Correlation and Regression Submitted by gfj100 on Fri, 10/30/2009 - 09:50 Influence Outliers In most practical circumstances an outlier decreases the value of a correlation coefficient and weakens the regression relationship, but it’s also possible that in some circumstances an outlier may increase a correlation value and improve regression. Figure 1 below provides an example of an influential outlier. Influential outliers are points in a data set that influence the regression equation and improve correlation. Figure 1 represents data gather on a persons Age and Blood Pressure, with Age as the explanatory variable. [Note: the regression plots were attained in Minitab by Stat > Regression > Fitted Line Plot.] The top graph in Figure 1 represents the complete set of 10 data points. You can see that one point stands out in the upper right corner, point of (75, 220). The bottom graph is the regression with this point removed. The correlation between the original 10 data points is 0.694 found by taking the square root of 0.481 (the R-sq of
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This note was uploaded on 05/31/2011 for the course STAT 200 taught by Professor Andyregards during the Spring '11 term at World College.

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Notes 8 - Cautions about Correlation and Regression Submitted by gfj100 on Fri 09:50 Influence Outliers In most practical circumstances an outlier

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