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ECO220Y1 (33)
Chapter 6

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Migiwa Tanaka

Chapter 6: Scatterplots, Association and Correlation Scatterplotplots one quantitative variable against another (best way to see relationships (or association) bw 2 quantitative variables) 3 Features of Scatterplots: DIRECTION: -if it rises to the right it is positive FORM- is it straight, curved, something exotic, or no pattern? STRENGTH: -are points tightly clustered in a single stream? Outlier: stands away from the overall pattern (sometimes accurate to dismiss them) (ie) if there is something exceptional about them (Bill Gates-income) -however, you may see entire clusters/subgroups standing away from rest of data this should raise questions -scatterplots are traced back to Rene Descartes Cartesian plane Bivariate Analysis: we are now investigating 2 variables -One variable plays the role of explanatory variable(x-axis), while the other is the response variable (y-axis) -idea that the y-variable depends on the x-variable and the x acts indep. To make y respond To standardize values*, we subtract the mean of each variable and then divide by its standard deviation: -resulting scatterplot looks roughly the same (now @ the origin) -Means of both variables are = to 0 now -this takes away the units –scales are standardized -since standardizing the variables doesn’t change the strength of the association, we work with the x-scores to understand
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