Notes for hw 6 and 7

Notes for hw 6 and 7 - Notes for HW 6: When theres a strong...

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Notes for HW 6: When there’s a strong correlation between x and y (i.e., the coefficient of correlation, r , is greater than .7), we use the equation of the regression line to predict y for a given x -value. Otherwise, we use the average of y for any given x -values. o For example, given a set of x and y values, say the average of the y values is 10 and the equation of the regression line is ˆ 2 4 y x = + . If r is .8, then to predict y when x is 5 will be y = 2(5) + 4 = 13. On the other hand, when r is .6, then to predict y when x is 5 (or any value of x ) will be 10 since 10 is the average of the y -values. Even there’s a strong correlation between x and y , we use the equation of the regression line to predict y for x -values that are within a “workable” scope. o For example, say the equation of the regression line is ˆ 2 30 y x = + where x is the age of a man and y is his height. We can use this equation to predict his height as long as the man is growing at a certain age. That is, we probably can use still use this equation for any
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This note was uploaded on 10/28/2011 for the course MATH 155 taught by Professor Hahe during the Spring '11 term at CUNY Hunter.

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Notes for hw 6 and 7 - Notes for HW 6: When theres a strong...

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