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? CE The men's linear regression model is y= (Round regression coefficients to three decimal places as needed.) The women's linear regression model is y= (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? O No OYes 1980 1984 1988 1992 1996 2000 2004 2008 100-Meter Freestyle Men 50.40 49.80 48.63 49.02 48.74 48.30 48.17 47.38 Women 54.79 55.92 54.93 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? CE The men's linear regression model is y= (Round regression coefficients to three decimal places as needed.) The women's linear regression model is y= (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? O No OYes 1980 1984 1988 1992 1996 2000 2004 2008 100-Meter Freestyle Men 50.40 49.80 48.63 49.02 48.74 48.30 48.17 47.38 Women 54.79 55.92 54.93 54.65 54.50 53.83 53.84 53.12
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Question
![K
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= 0
(Round regression coefficients to three decimal places as needed.)
The women's linear regression model is
y =
(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?
O No
OYes
STTTTTTT
1980
1984
1988
1992
1996
2000
2004
2008
100-Meter Freestyle
Men
50.40
49.80
48.63
49.02
48.74
48.30
48.17
47.38
Women
54.79
55.92
54.93
54.65
54.50
53.83
53.84
53.12](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F2ccfc1af-dbdd-40d7-8d59-254a1eab9106%2F95660127-3355-4681-8408-d53d3b4692dd%2F0uqqynk_processed.jpeg&w=3840&q=75)
Transcribed Image Text:K
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= 0
(Round regression coefficients to three decimal places as needed.)
The women's linear regression model is
y =
(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?
O No
OYes
STTTTTTT
1980
1984
1988
1992
1996
2000
2004
2008
100-Meter Freestyle
Men
50.40
49.80
48.63
49.02
48.74
48.30
48.17
47.38
Women
54.79
55.92
54.93
54.65
54.50
53.83
53.84
53.12
Expert Solution
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Step 1
The given data for the men's and women's -meter freestyle.
Men | Women | |
1980 1984 1988 1992 1996 2000 2004 2008 |
50.40 49.80 48.63 49.02 48.74 48.30 48.17 47.38 |
54.79 55.92 54.93 54.65 54.50 53.83 53.84 53.12 |
We have to find the linear regression model for both men and women's -meter freestyle.
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