document.write( "Question 1207185: Mrs. Robinson made the table below showing the yearly balance of her savings
\n" ); document.write( "account. Interest on the account compounds annually. Which of the following
\n" ); document.write( "describes the best model to be used for Mrs. Robinson’s data?
\n" ); document.write( "Year Balance in Dollars
\n" ); document.write( "0 $400
\n" ); document.write( "5 $463.71
\n" ); document.write( "10 $537.57
\n" ); document.write( "15 $623.19
\n" ); document.write( "20 $722.44
\n" ); document.write( "25 $837.51\r
\n" ); document.write( "\n" ); document.write( "A) a positive linear function
\n" ); document.write( "B) a positive quadratic function
\n" ); document.write( "C) an exponential growth function
\n" ); document.write( "D) a positive absolute value function
\n" ); document.write( "

Algebra.Com's Answer #844918 by math_tutor2020(3816)\"\" \"About 
You can put this solution on YOUR website!

\n" ); document.write( "Use technology of your choice to determine these regression equations
  • linear: f(x) = 17.4249142857x + 379.5919047619
  • quadratic: g(x) = 0.2559714286x^2 + 11.0256285714x + 400.9228571429
  • exponential: h(x) = 400.0011431092e^(0.0295586331x)
The decimal values are approximate.
\n" ); document.write( "The 'e' is a special constant roughly equal to 2.718
\n" ); document.write( "h(x) is roughly equivalent to 400.0011431092*1.0299998258^x\r
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\n" ); document.write( "\n" ); document.write( "From here, use spreadsheet software to construct the following table
\n" ); document.write( "\n" ); document.write( "\n" ); document.write( "
GivenAbsolute Error
xylinearquadraticexponential
040020.4080950.9228570.001143
5463.713.0064761.2597140.000563
10537.5716.2710480.7937140.002821
15623.1917.7756190.7108570.002834
20722.445.650191.3840.004115
25837.5122.2952380.9642860.000024

\n" ); document.write( "The first two columns are copy/pasted from the table your teacher gave you. Except of course the dollar sign symbols have been erased.
\n" ); document.write( "The remaining 3 columns represent the absolute error when subtracting the stated y value from each regression output.\r
\n" ); document.write( "
\n" ); document.write( "\n" ); document.write( "For example, when x = 0 the y value is y = 400.
\n" ); document.write( "If you plugged x = 0 into the linear regression function, then you should find f(0) = 379.5919047619
\n" ); document.write( "The error is approximately |y-f(x)| = |y-f(0)| = |400-379.5919047619| = 20.4080952381
\n" ); document.write( "Follow similar steps to compute the other error values. \r
\n" ); document.write( "
\n" ); document.write( "\n" ); document.write( "In a perfect world, the error would be 0. But of course nothing is ever perfect.
\n" ); document.write( "The next best thing is to try to get as close to 0 as possible.
\n" ); document.write( "This occurs with the exponential regression function.
\n" ); document.write( "Therefore, the exponential is the best fit.\r
\n" ); document.write( "
\n" ); document.write( "
\n" ); document.write( "\n" ); document.write( "Answer: choice C
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