Finite Math Examples

$\begin{array}{c} x & y \\ 100 & 2 \\ 71 & 4 \\ 36 & 46 \\ 96 & 7 \\ 98 & 2 \\ 80 & 9 \\ 91 & 6 \\ 50 & 24 \\ 99 & 3 \\ 53 & 24 \\ 67 & 19 \end{array}$

Step 1

The linear correlation coefficient measures the relationship between the paired values in a sample.

$r = \frac{n (\sum_{}^{} x y) - \sum_{}^{} x \sum_{}^{} y}{\sqrt{n (\sum_{}^{} x^{2}) - {(\sum_{}^{} x)}^{2}} \cdot \sqrt{n (\sum_{}^{} y^{2}) - {(\sum_{}^{} y)}^{2}}}$

Step 2

Sum up the $x$ values.

$\sum_{}^{} x = 100 + 71 + 36 + 96 + 98 + 80 + 91 + 50 + 99 + 53 + 67$

Step 3

Simplify the expression.

$\sum_{}^{} x = 841$

Step 4

Sum up the $y$ values.

$\sum_{}^{} y = 2 + 4 + 46 + 7 + 2 + 9 + 6 + 24 + 3 + 24 + 19$

Step 5

Simplify the expression.

$\sum_{}^{} y = 146$

Step 6

Sum up the values of $x \cdot y$ .

$\sum_{}^{} x y = 100 \cdot 2 + 71 \cdot 4 + 36 \cdot 46 + 96 \cdot 7 + 98 \cdot 2 + 80 \cdot 9 + 91 \cdot 6 + 50 \cdot 24 + 99 \cdot 3 + 53 \cdot 24 + 67 \cdot 19$

Step 7

Simplify the expression.

$\sum_{}^{} x y = 8316$

Step 8

Sum up the values of $x^{2}$ .

$\sum_{}^{} x^{2} = {(100)}^{2} + {(71)}^{2} + {(36)}^{2} + {(96)}^{2} + {(98)}^{2} + {(80)}^{2} + {(91)}^{2} + {(50)}^{2} + {(99)}^{2} + {(53)}^{2} + {(67)}^{2}$

Step 9

Simplify the expression.

$\sum_{}^{} x^{2} = 69437$

Step 10

Sum up the values of $y^{2}$ .

$\sum_{}^{} y^{2} = {(2)}^{2} + {(4)}^{2} + {(46)}^{2} + {(7)}^{2} + {(2)}^{2} + {(9)}^{2} + {(6)}^{2} + {(24)}^{2} + {(3)}^{2} + {(24)}^{2} + {(19)}^{2}$

Step 11

Simplify the expression.

$\sum_{}^{} y^{2} = 3828$

Step 12

Fill in the computed values.

$r = \frac{11 (8316) - 841 \cdot 146}{\sqrt{11 (69437) - {(841)}^{2}} \cdot \sqrt{11 (3828) - {(146)}^{2}}}$

Step 13

Simplify the expression.

$r = - 0.91329442$