document.write( "Question 1190381: A data series is given for a periodic process:
\n" ); document.write( "0 1 2 3 4 5 6 7 8 9 10
\n" ); document.write( "1, 7 1, 7 2, 3 2, 9 3, 0 3, 5 4, 0 11, 0 9, 5 9, 7 9, 9
\n" ); document.write( "Please find a linear regression.
\n" ); document.write( "Is the use of a linear regression okay \n" ); document.write( "

Algebra.Com's Answer #822004 by math_tutor2020(3817) $\"\"$ $\"About$

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\n" ); document.write( "The data table seems a bit garbled.
\n" ); document.write( "This is what I'm assuming it looks like\n" ); document.write( "\n" ); document.write( "

0	1	2	3	4	5	6	7	8	9	10
(1,7)	(1,7)	(2,3)	(2,9)	(3,0)	(3,5)	(4,0)	(11,0)	(9,5)	(9,7)	(9,9)

You could find the linear regression equation by hand, but it's a tedious process that may take a while.
\n" ); document.write( "I strongly recommend using a graphing calculator or computer software. There are many free options online if you don't have a graphing calculator.\r
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\n" ); document.write( "\n" ); document.write( "Whichever method you use, the linear regression equation is approximately this:
\n" ); document.write( "y = -0.0929x + 5.1832\r
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\n" ); document.write( "\n" ); document.write( "The correlation coefficient (r value) is a similar story to finding the regression equation. It's better to use a calculator.
\n" ); document.write( "You should find that r = -0.1004 approximately
\n" ); document.write( "Since this is much closer to r = 0 than it is to r = 1, this makes the negative linear correlation fairly weak.
\n" ); document.write( "It's not a good idea to use a linear model here.\r
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\n" ); document.write( "\n" ); document.write( "Because you mentioned the data is periodic, a sine or cosine model would likely provide a better fit.
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