Correlation and Linear Regression

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I'm tasked with this question but unable to proceed on.

Q: Calculate the linear product moment correlation coefficient between x and m for these samples:

$$ \Sigma x=205,\\ \Sigma m=1240, \\ \Sigma m^2=78,320,\\ \Sigma xm=13,020, \\ \Sigma(x−\bar x)^2=126 $$

However when I was given the formula in the MF15 (http://www.seab.gov.sg/content/syllabus/alevel/2016Syllabus/ListMF15.pdf), I couldn't use $\Sigma(x−\bar x)^2$ for the second formula as in the above link.

Hence I was thinking of manipulating it but unsure of how I can do so. Would really appreciate your help. Thanks.

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It is $\sum (x_i-\overline x)^2$

First you have multiply out the brackets: $\sum (x_i^2- 2\left( x_i\right)\overline x+\overline x ^2)$

Each summand in the brackets gets a sigma sign. The constants $2, \overline x$ and $\overline x^2$ can factored out.

$= \sum x_i^2-2\overline x\sum x_i+\overline x^2\sum 1$

  • $\sum x_i=n\cdot \overline x$ and $\sum 1=n$

$= \sum x_i^2-2\overline x\cdot n\cdot \overline x+n\overline x^2= \sum x_i^2-2\cdot n \overline x ^2+n\overline x^2=\sum x_i^2+n\overline x^2=\sum x_i^2-\frac1n\cdot \left( \sum x_i \right)^2$

$=126$

Now you can use the second formula straight forward.