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? 100-Meter Freestyle Men Women 54.79 55.92 1980 50 40 1984 49 80 1988 48.63 54.93 54.65 54.50 53 83 53 96 1992 49 02 The men's linear regression model is 1996 48.74 2000 48.30 (Round regression coefficients to three decimal places as needed) 2004 48 17 The women's linear regression model is y-D (Round regression coefficients to three decimal places as needed) 2008 47.38 53.12 Based on the regression models, will the women's times eventually catch up with the men's times? O Yes No

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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?
100-Meter Freestyle
Men
Women
1980
50 40
54.79
1984
49 80
55.92
1988
48.63
54.93
1992
49.02
54.65
The men's linear regression model is
y D]
(Round regression coefficients to three decimal places as needed)
1996
48 74
54.50
2000
48 30
53 83
2004
48.17
53.96
The women's linear regression model is
2008
53.12
47.38
(Round regression coefficients to three decimal places as needed )
Based on the regression models, will the women's times eventually catch up with
the men's times?
Yes
No
Transcribed Image Text: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? 100-Meter Freestyle Men Women 1980 50 40 54.79 1984 49 80 55.92 1988 48.63 54.93 1992 49.02 54.65 The men's linear regression model is y D] (Round regression coefficients to three decimal places as needed) 1996 48 74 54.50 2000 48 30 53 83 2004 48.17 53.96 The women's linear regression model is 2008 53.12 47.38 (Round regression coefficients to three decimal places as needed ) Based on the regression models, will the women's times eventually catch up with the men's times? Yes No
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