Use a graphing calculator to find a linear regression model for the men's 100-meter freestyle data given in the table on the right, where x is years since 1980 and y is winning time (in seconds). Do the same for the women's 100-meter freestyle data. Do these models indicate that the women will eventually catch up with the men? The men's linear regression model is y = (Round regression coefficients to three decimal places as needed.) C 1980 1984 1988 1992 1996 2000 2004 2008 100-Meter Freestyle Men 50.40 49.95 48.63 49.02 48.74 48.30 48.17 47.21 Women 54.79 55.92 55.00 54.65 54.50 53.83 53.84 53.12

Use a graphing calculator to find a linear regression model for the men's 100-meter freestyle data given in the table on the right, where x is years since 1980 and y is winning time (in seconds). Do the same for the women's 100-meter freestyle data. Do these models indicate that the women will eventually catch up with the men? The men's linear regression model is y = (Round regression coefficients to three decimal places as needed.) C 1980 1984 1988 1992 1996 2000 2004 2008 100-Meter Freestyle Men 50.40 49.95 48.63 49.02 48.74 48.30 48.17 47.21 Women 54.79 55.92 55.00 54.65 54.50 53.83 53.84 53.12

Functions and Change: A Modeling Approach to College Algebra (MindTap Course List)

6th Edition

ISBN:9781337111348

Author:Bruce Crauder, Benny Evans, Alan Noell

Publisher:Bruce Crauder, Benny Evans, Alan Noell

Chapter5: A Survey Of Other Common Functions

Section5.6: Higher-degree Polynomials And Rational Functions

Problem 1TU: The following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t=...

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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?
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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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