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based on the data shown below, calculate the regression line (each valu…

Question

based on the data shown below, calculate the regression line (each value to at least two decimal places). x: 4, 5, 6, 7, 8, 9; y: 22.6, 20.48, 19.36, 16.84, 17.72, 15.8. question help: d post to forum

Explanation:

Step1: Calculate means of x and y

Let $x_i$ be the values of the $x -$ variable and $y_i$ be the values of the $y -$ variable.
$n = 6$
$\bar{x}=\frac{4 + 5+6+7+8+9}{6}=\frac{39}{6}=6.5$
$\bar{y}=\frac{22.6+20.48+19.36+16.84+17.72+15.8}{6}=\frac{112.8}{6}=18.8$

Step2: Calculate numerator and denominator for slope

The formula for the slope $b$ of the regression line $y = a+bx$ is $b=\frac{\sum_{i = 1}^{n}(x_i-\bar{x})(y_i - \bar{y})}{\sum_{i=1}^{n}(x_i-\bar{x})^2}$
$\sum_{i = 1}^{6}(x_i-\bar{x})(y_i - \bar{y})=(4 - 6.5)(22.6-18.8)+(5 - 6.5)(20.48 - 18.8)+(6 - 6.5)(19.36 - 18.8)+(7 - 6.5)(16.84 - 18.8)+(8 - 6.5)(17.72 - 18.8)+(9 - 6.5)(15.8 - 18.8)$
$=(- 2.5)\times3.8+( - 1.5)\times1.68+( - 0.5)\times0.56+0.5\times(-1.96)+1.5\times(-1.08)+2.5\times(-3)$
$=-9.5-2.52 - 0.28-0.98-1.62 - 7.5=-22.4$
$\sum_{i=1}^{6}(x_i-\bar{x})^2=(4 - 6.5)^2+(5 - 6.5)^2+(6 - 6.5)^2+(7 - 6.5)^2+(8 - 6.5)^2+(9 - 6.5)^2$
$=(-2.5)^2+( - 1.5)^2+( - 0.5)^2+0.5^2+1.5^2+2.5^2$
$=6.25 + 2.25+0.25+0.25+2.25+6.25 = 17.5$
$b=\frac{-22.4}{17.5}=-1.28$

Step3: Calculate intercept

The formula for the intercept $a$ is $a=\bar{y}-b\bar{x}$
$a = 18.8-(-1.28)\times6.5=18.8 + 8.32=27.12$

Answer:

$y=27.12-1.28x$