12) Use computer software to find the best multiple regression equation to explain the variation inthe dependent variable, Y, in terms of the independent variables, X1, X2, X3.9896 29.11421 968042.3 2653 10449 29.8 3573 10811 26.0 4CORRELATION COEFFICIENTS546 1001434.3 5499 1029322.7 6%3D60% 0.00Y/ X2=0.280Y/ X3 = 0.930504 941324.2 7%3D611 9860 31.6 8%3D646 9782 25.6 9789 12139 37.9 10COEFFICIENTS OF DETERMINATION773 12166 33.9 11YI X1 = 0.259Y/ X2 = 0.079YI X3 = 0.864Y/ X1, X3 = 0.880YI X1, X2, X3 = 0.884753 9976 37.4 12%3D852 10645 27.0 13%3D755 9738 31.5 14%3D815 9933 39.9 15%3D902 10132 25.3 16986 11145 30.4 17909 9775 32.7 18945 9549 35.0 19866 10077 33.8 201178 11550 29.4 211230 10600 37.1 221207 11280 42.9 23968 12100 32.2 241118 12420 30.5 25A) Î = 57.8+0.036X, +28.1X3B) Ý = -21.1+0.36X, +2.62X, +27.6X3%3DC) Ý = 201.7+0.40X, +22.3X3D) Y = 308.6+ 29.9X3%3D

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Answered: 12) Use computer software to find the…

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter10: Statistics

Section10.1: Measures Of Center

Problem 9PPS

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Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?
The following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t= Years since 2006 0 1 2 3 4 5 6 7 8 9 10 K= Price 56 51 50 55 58 52 45 43 44 48 51 Make a quartic model of these data. Round the regression parameters to two decimal places.
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The following table shows the annual number of PhD graduates in a country in various fields. NaturalSciences Engineering SocialSciences Education 1990 70 10 60 30 1995 130 40 120 40 2000 330 130 280 120 2005 490 370 460 210 2010 590 550 830 520 2012 690 590 1,000 900 (a)With x = the number of social science doctorates and y = the number of education doctorates, use technology to obtain the regression equation. (Round coefficients to three significant digits.) y(x) =
The following table shows the annual number of PhD graduates in a country in various fields. NaturalSciences Engineering SocialSciences Education 1990 70 10 70 30 1995 130 40 110 40 2000 330 130 280 120 2005 490 370 460 210 2010 590 550 830 520 2012 690 590 1,000 900 (a) With x = the number of social science doctorates and y = the number of education doctorates, use technology to obtain the regression equation. (Round coefficients to three significant digits.) y(x) = (b) Use technology to obtain the coefficient of correlation r. (Round your answer to three decimal places.) r =
he following table shows the annual number of PhD graduates in a country in various fields. NaturalSciences Engineering SocialSciences Education 1990 70 10 60 30 1995 130 40 100 50 2000 330 130 280 140 2005 490 370 460 210 2010 590 550 830 520 2012 690 590 1,000 900 (a)With x = the number of social science doctorates and y = the number of education doctorates, use technology to obtain the regression equation. (Round coefficients to three significant digits.) y(x) = Use technology to obtain the coefficient of correlation r. (Round your answer to three decimal places.) r =

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