STAT 111 Lecture Notes - Lecture 6: Summary Statistics, Scatter Plot

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Section 2. 5 2 quantitative variables: scatterplot and correlation. The graph of the relationship between 2 quantitative variables. Positive association: values of one variable tend to be higher when the values of the other variable tend to be higher. Negative association: values of one variable tend to be lower when values of other variable are higher. Not associated: 2 variables are not associated if knowing the value of one variable does not give you any info about the value of the other variable. Atte(cid:373)pt to des(cid:272)(cid:396)i(cid:271)e (cid:862)ho(cid:449) (cid:272)lose(cid:863) the (cid:448)a(cid:396)ia(cid:271)les a(cid:396)e asso(cid:272)iated. The closer the points are on a scatterplot the stronger the association. A measure of the strength and direction of linear association between 2 quantitative variables: sample correlation: r, population correlation: (cid:894)(cid:862)(cid:396)ho(cid:863)(cid:895) Correlation cautions: correlation can be heavily affected by outliers. Always plot data: r = 0 means no linear association. The variables could still be otherwise associated: correlation does not imply causation.

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