We are given the following coordinate pairs: (17,36), (27,25), (37,20), (47,12), (57,10), (67,7), and (77,5), where the x-coordinate represents the age in years and the y-coordinate the percent of fatal accidents with speeding as the major cause.
It might be easiest to create a table with the following headings: x, y, xy, x^2, and y^2. Then sum each of the columns:
x: y: xy: x^2: y^2:17 36 612 289 129627 25 675 729 62537 20 740 1369 40047 12 564 2209 14457 10 570 3249 10067 7 469 4489 4977 5 385 5929 25-----------------------------------329 115 4015 18263 2639
(1) Find the mean of x and y:
bar(x)=(sum x)/n=329/7=47
bar(y)=(sum y)/n=115/7 ~~ 16.43
(2) Find a and b for the linear regression line of best fit. (Note that you should check that the correlation is significant—with r about -.959 the correlation is significant at least for a 98% confidence.)
a=((sum y)(sum x^2)-(sum x)(sum xy))/(n(sum x^2)-(sum x)^2)
=(115*18263-329*4015)/(7*18263-329^2) ~~ 39.761
b=(n(sum xy)-(sum x)(sum y))/(n(sum x^2)-(sum x)^2)
=(7*4015-329*115)/(7*18263-329^2) ~~ -.496
(3) The equation of the regression line y'=a+bx is y'=39.760-0.496x
(4) The value of the regression line at x=25 (which is the estimate for the percentage of fatal accidents caused by speeding for 25 year olds) is
y'=39.760-0.496(25)=27.35
http://mathworld.wolfram.com/LeastSquaresFitting.html
Tuesday, June 28, 2016
Let x be the age in years of a licensed automobile driver. Let y be the percentage of all fatal accidents (for a given age) due to speeding. For example, the first data pair indicates that 36% of all fatal accidents involving 17 year olds are due to speeding. x=17,27,37,47,57,67,77 y=36,25,20,12,10,7,5 1.)find the sample mean for x (round to nearest whole number) and y (round to 2 decimal places). 2.)find a and b. round your answer to 3 decimal places 3.)write the equation of the least squares line y=a+bx 4.)Predict the percentage of all fatal accidents due to speeding for 25 year olds. (round to 2 decimal places)
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