12c_Ch15_Regression_Outline

12c_Ch15_Regression_Outline - 1 2 3 Regression You should...

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Regression You should. . . • understand how to make predictions based on a: –Scatterplot –regression line –Least squares regression line • understand proportion of variance accounted for — in terms of regression Regression • Once we establish a relationship between two variables, it is often useful to make predictions that go beyond the available data. • Given a correlation between two variables, can we predict values on one variable given values on the other variable? Example • Can we predict height from salary? Height and Salary Regression • Two "rough" approaches to prediction: scatterplot regression line Prediction Using a Scatterplot Height and Salary • If a person is 74 inches tall, what will her/his salary be? • We know that: • a 73 inch person makes \$46,200 • a 77 inch person makes \$47,100 • Note: There is no 74 inch person in our data Scatterplot for Height and Salary We predict that a person 74 inches tall will make between 1 2 3 4 5 6 7 8 9 10

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\$46,200 and \$47,100 (approximately) Prediction Using a regression line “Fit by eye” Regression line • A regression line is a line that “best fits” the points in a scatterplot Fit a regression line by eye
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12c_Ch15_Regression_Outline - 1 2 3 Regression You should...

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