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book College Algebra in Context with Applications for the Managerial, Life, and Social Sciences 3rd Edition by Ronald J Harshbarger, Lisa Yocco cover

College Algebra in Context with Applications for the Managerial, Life, and Social Sciences 3rd Edition by Ronald J Harshbarger, Lisa Yocco

Edition 3ISBN: 032157060X
book College Algebra in Context with Applications for the Managerial, Life, and Social Sciences 3rd Edition by Ronald J Harshbarger, Lisa Yocco cover

College Algebra in Context with Applications for the Managerial, Life, and Social Sciences 3rd Edition by Ronald J Harshbarger, Lisa Yocco

Edition 3ISBN: 032157060X
Exercise 39
Step-by-step solution
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Step 1 of 5

Convert the data from the chart into the table as follows:

Year

Years past 65 Men

1950

12.8

1960

12.9

1970

13.1

1980

14

1990

15

2000

15.9

2010

16.4

2020

16.9

2030

17.5

(a) Let us find a linear function    <div class=answer> Convert the data from the chart into the table as follows: <table style=border-collapse:collapse; border=1>     <tbody>      <tr>       <td> Year </td>       <td> Years past 65 Men </td>      </tr>      <tr>       <td> 1950 </td>       <td> 12.8 </td>      </tr>      <tr>       <td> 1960 </td>       <td> 12.9 </td>      </tr>      <tr>       <td> 1970 </td>       <td> 13.1 </td>      </tr>      <tr>       <td> 1980 </td>       <td> 14 </td>      </tr>      <tr>       <td> 1990 </td>       <td> 15 </td>      </tr>      <tr>       <td> 2000 </td>       <td> 15.9 </td>      </tr>      <tr>       <td> 2010 </td>       <td> 16.4 </td>      </tr>      <tr>       <td> 2020 </td>       <td> 16.9 </td>      </tr>      <tr>       <td> 2030 </td>       <td> 17.5 </td>      </tr>     </tbody>    </table> (a) Let us find a linear function   that models the data, with <i>x</i> equal to the number of years after 1950 and <i>y</i> equal to the number of years the average 65-year-old man is estimated to live beyond age 65. Enter the data from the above table in the lists of a graphing utility. The figure below shows a partial list of the data points.     The equation that fits the data, found using linear regression with a graphing calculator.   Thus, a linear function   that models the data, rounded to three decimals is   . that models the data, with x equal to the number of years after 1950 and y equal to the number of years the average 65-year-old man is estimated to live beyond age 65.

Enter the data from the above table in the lists of a graphing utility.

The figure below shows a partial list of the data points.

    <div class=answer> Convert the data from the chart into the table as follows: <table style=border-collapse:collapse; border=1>     <tbody>      <tr>       <td> Year </td>       <td> Years past 65 Men </td>      </tr>      <tr>       <td> 1950 </td>       <td> 12.8 </td>      </tr>      <tr>       <td> 1960 </td>       <td> 12.9 </td>      </tr>      <tr>       <td> 1970 </td>       <td> 13.1 </td>      </tr>      <tr>       <td> 1980 </td>       <td> 14 </td>      </tr>      <tr>       <td> 1990 </td>       <td> 15 </td>      </tr>      <tr>       <td> 2000 </td>       <td> 15.9 </td>      </tr>      <tr>       <td> 2010 </td>       <td> 16.4 </td>      </tr>      <tr>       <td> 2020 </td>       <td> 16.9 </td>      </tr>      <tr>       <td> 2030 </td>       <td> 17.5 </td>      </tr>     </tbody>    </table> (a) Let us find a linear function   that models the data, with <i>x</i> equal to the number of years after 1950 and <i>y</i> equal to the number of years the average 65-year-old man is estimated to live beyond age 65. Enter the data from the above table in the lists of a graphing utility. The figure below shows a partial list of the data points.     The equation that fits the data, found using linear regression with a graphing calculator.   Thus, a linear function   that models the data, rounded to three decimals is   .     <div class=answer> Convert the data from the chart into the table as follows: <table style=border-collapse:collapse; border=1>     <tbody>      <tr>       <td> Year </td>       <td> Years past 65 Men </td>      </tr>      <tr>       <td> 1950 </td>       <td> 12.8 </td>      </tr>      <tr>       <td> 1960 </td>       <td> 12.9 </td>      </tr>      <tr>       <td> 1970 </td>       <td> 13.1 </td>      </tr>      <tr>       <td> 1980 </td>       <td> 14 </td>      </tr>      <tr>       <td> 1990 </td>       <td> 15 </td>      </tr>      <tr>       <td> 2000 </td>       <td> 15.9 </td>      </tr>      <tr>       <td> 2010 </td>       <td> 16.4 </td>      </tr>      <tr>       <td> 2020 </td>       <td> 16.9 </td>      </tr>      <tr>       <td> 2030 </td>       <td> 17.5 </td>      </tr>     </tbody>    </table> (a) Let us find a linear function   that models the data, with <i>x</i> equal to the number of years after 1950 and <i>y</i> equal to the number of years the average 65-year-old man is estimated to live beyond age 65. Enter the data from the above table in the lists of a graphing utility. The figure below shows a partial list of the data points.     The equation that fits the data, found using linear regression with a graphing calculator.   Thus, a linear function   that models the data, rounded to three decimals is   .

The equation that fits the data, found using linear regression with a graphing calculator.

    <div class=answer> Convert the data from the chart into the table as follows: <table style=border-collapse:collapse; border=1>     <tbody>      <tr>       <td> Year </td>       <td> Years past 65 Men </td>      </tr>      <tr>       <td> 1950 </td>       <td> 12.8 </td>      </tr>      <tr>       <td> 1960 </td>       <td> 12.9 </td>      </tr>      <tr>       <td> 1970 </td>       <td> 13.1 </td>      </tr>      <tr>       <td> 1980 </td>       <td> 14 </td>      </tr>      <tr>       <td> 1990 </td>       <td> 15 </td>      </tr>      <tr>       <td> 2000 </td>       <td> 15.9 </td>      </tr>      <tr>       <td> 2010 </td>       <td> 16.4 </td>      </tr>      <tr>       <td> 2020 </td>       <td> 16.9 </td>      </tr>      <tr>       <td> 2030 </td>       <td> 17.5 </td>      </tr>     </tbody>    </table> (a) Let us find a linear function   that models the data, with <i>x</i> equal to the number of years after 1950 and <i>y</i> equal to the number of years the average 65-year-old man is estimated to live beyond age 65. Enter the data from the above table in the lists of a graphing utility. The figure below shows a partial list of the data points.     The equation that fits the data, found using linear regression with a graphing calculator.   Thus, a linear function   that models the data, rounded to three decimals is   .

Thus, a linear function    <div class=answer> Convert the data from the chart into the table as follows: <table style=border-collapse:collapse; border=1>     <tbody>      <tr>       <td> Year </td>       <td> Years past 65 Men </td>      </tr>      <tr>       <td> 1950 </td>       <td> 12.8 </td>      </tr>      <tr>       <td> 1960 </td>       <td> 12.9 </td>      </tr>      <tr>       <td> 1970 </td>       <td> 13.1 </td>      </tr>      <tr>       <td> 1980 </td>       <td> 14 </td>      </tr>      <tr>       <td> 1990 </td>       <td> 15 </td>      </tr>      <tr>       <td> 2000 </td>       <td> 15.9 </td>      </tr>      <tr>       <td> 2010 </td>       <td> 16.4 </td>      </tr>      <tr>       <td> 2020 </td>       <td> 16.9 </td>      </tr>      <tr>       <td> 2030 </td>       <td> 17.5 </td>      </tr>     </tbody>    </table> (a) Let us find a linear function   that models the data, with <i>x</i> equal to the number of years after 1950 and <i>y</i> equal to the number of years the average 65-year-old man is estimated to live beyond age 65. Enter the data from the above table in the lists of a graphing utility. The figure below shows a partial list of the data points.     The equation that fits the data, found using linear regression with a graphing calculator.   Thus, a linear function   that models the data, rounded to three decimals is   . that models the data, rounded to three decimals is    <div class=answer> Convert the data from the chart into the table as follows: <table style=border-collapse:collapse; border=1>     <tbody>      <tr>       <td> Year </td>       <td> Years past 65 Men </td>      </tr>      <tr>       <td> 1950 </td>       <td> 12.8 </td>      </tr>      <tr>       <td> 1960 </td>       <td> 12.9 </td>      </tr>      <tr>       <td> 1970 </td>       <td> 13.1 </td>      </tr>      <tr>       <td> 1980 </td>       <td> 14 </td>      </tr>      <tr>       <td> 1990 </td>       <td> 15 </td>      </tr>      <tr>       <td> 2000 </td>       <td> 15.9 </td>      </tr>      <tr>       <td> 2010 </td>       <td> 16.4 </td>      </tr>      <tr>       <td> 2020 </td>       <td> 16.9 </td>      </tr>      <tr>       <td> 2030 </td>       <td> 17.5 </td>      </tr>     </tbody>    </table> (a) Let us find a linear function   that models the data, with <i>x</i> equal to the number of years after 1950 and <i>y</i> equal to the number of years the average 65-year-old man is estimated to live beyond age 65. Enter the data from the above table in the lists of a graphing utility. The figure below shows a partial list of the data points.     The equation that fits the data, found using linear regression with a graphing calculator.   Thus, a linear function   that models the data, rounded to three decimals is   . .


Step 2 of 5


Step 3 of 5


Step 4 of 5


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College Algebra in Context with Applications for the Managerial, Life, and Social Sciences 3rd Edition by Ronald J Harshbarger, Lisa Yocco
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