answer: 33 ( approx)
step-by-step explanation:
since, in the linear regression formula, the slope is the a in the equation y = b + ax ( by comparing it with the general equation of line y = mx + c )
where, ![a = \frac{\sum y \sum x^2 - \sum x\sum xy}{n\sum x^2 - (\sum x)^2}](/tex.php?f=a = \frac{\sum y \sum x^2 - \sum x\sum xy}{n\sum x^2 - (\sum x)^2})
here given table is,
price ($), x : 18 23 25 29 30 33
pairs sold, y : 16 13 10 8 6 2
so,
,
,
,
and
,
thus, slop of the given line is,
![a = \frac{55\times 4308-158\times 1315}{6\times 4308-(158)^2}](/tex.php?f=a = \frac{55\times 4308-158\times 1315}{6\times 4308-(158)^2})
β ![a = \frac{29170}{884}](/tex.php?f=a = \frac{29170}{884})
β
β 33