Finite Math Examples

$\begin{array}{c} x & y \\ 0 & 0.897 \\ 0 & 0.886 \\ 1 & 0.891 \\ 1 & 0.881 \\ 2 & 0.888 \\ 2 & 0.871 \\ 3 & 0.868 \\ 3 & 0.876 \\ 4 & 0.873 \\ 5 & 0.875 \\ 5 & 0.871 \\ 6 & 0.867 \\ 7 & 0.862 \\ 7 & 0.872 \\ 8 & 0.865 \end{array}$

Step 1

The slope of the best fit regression line can be found using the formula.

$m = \frac{n (\sum_{}^{} x y) - \sum_{}^{} x \sum_{}^{} y}{n (\sum_{}^{} x^{2}) - {(\sum_{}^{} x)}^{2}}$

Step 2

The y-intercept of the best fit regression line can be found using the formula.

$b = \frac{(\sum_{}^{} y) (\sum_{}^{} x^{2}) - \sum_{}^{} x \sum_{}^{} x y}{n (\sum_{}^{} x^{2}) - {(\sum_{}^{} x)}^{2}}$

Step 3

Sum up the

$x$ values.

$\sum_{}^{} x = 0 + 0 + 1 + 1 + 2 + 2 + 3 + 3 + 4 + 5 + 5 + 6 + 7 + 7 + 8$

Step 4

Simplify the expression.

$\sum_{}^{} x = 54$

Step 5

Sum up the

$y$ values.

$\sum_{}^{} y = 0.897 + 0.886 + 0.891 + 0.881 + 0.888 + 0.871 + 0.868 + 0.876 + 0.873 + 0.875 + 0.871 + 0.867 + 0.862 + 0.872 + 0.865$

Step 6

Simplify the expression.

$\sum_{}^{} y = 13.143$

Step 7

Sum up the values of

$x \cdot y$ .

$\sum_{}^{} x y = 0 \cdot 0.897 + 0 \cdot 0.886 + 1 \cdot 0.891 + 1 \cdot 0.881 + 2 \cdot 0.888 + 2 \cdot 0.871 + 3 \cdot 0.868 + 3 \cdot 0.876 + 4 \cdot 0.873 + 5 \cdot 0.875 + 5 \cdot 0.871 + 6 \cdot 0.867 + 7 \cdot 0.862 + 7 \cdot 0.872 + 8 \cdot 0.865$

Step 8

Simplify the expression.

$\sum_{}^{} x y = 47.003998$

Step 9

Sum up the values of

$x^{2}$ .

$\sum_{}^{} x^{2} = {(0)}^{2} + {(0)}^{2} + {(1)}^{2} + {(1)}^{2} + {(2)}^{2} + {(2)}^{2} + {(3)}^{2} + {(3)}^{2} + {(4)}^{2} + {(5)}^{2} + {(5)}^{2} + {(6)}^{2} + {(7)}^{2} + {(7)}^{2} + {(8)}^{2}$

Step 10

Simplify the expression.

$\sum_{}^{} x^{2} = 292$

Step 11

Sum up the values of

$y^{2}$ .

$\sum_{}^{} y^{2} = {(0.897)}^{2} + {(0.886)}^{2} + {(0.891)}^{2} + {(0.881)}^{2} + {(0.888)}^{2} + {(0.871)}^{2} + {(0.868)}^{2} + {(0.876)}^{2} + {(0.873)}^{2} + {(0.875)}^{2} + {(0.871)}^{2} + {(0.867)}^{2} + {(0.862)}^{2} + {(0.872)}^{2} + {(0.865)}^{2}$

Step 12

Simplify the expression.

$\sum_{}^{} y^{2} = 11.5173688$

Step 13

Fill in the computed values.

$m = \frac{15 (47.003998) - 54 \cdot 13.143}{15 (292) - {(54)}^{2}}$

Step 14

Simplify the expression.

$m = - 0.00318445$

Step 15

Fill in the computed values.

$b = \frac{(13.143) (292) - 54 \cdot 47.003998}{15 (292) - {(54)}^{2}}$

Step 16

Simplify the expression.

$b = 0.88766396$

Step 17

Fill in the values of slope

$m$ and y-intercept

$b$ into the slope-intercept formula.

$y = - 0.00318445 x + 0.88766396$