The regression model that best fit the data set is : Y=10.35-0.0467X
Explanation:
The equation of a regression line is given by;
Y=a+bX where b is the slope of the line a is the y-intercept , Y is the dependent variable and X is the independent variable
The slope b is given by;
b = n(∑xy)-(∑x)(∑y) / n(∑x² )-(∑x)²
a=(∑y)(∑x²)-(∑x)(∑xy) /n(∑x²)-(∑x)²
n is the sample size = 4
Form a table as;
x y xy x² y²
2 13 26 4 169
4 8 32 16 64
5 7.5 37.5 25 56.25
8 12 96 64 144
19 40.5 191.5 109 433.25--------sum
a=(∑y)(∑x²)-(∑x)(∑xy) /n(∑x²)-(∑x)²
a=(40.5)(109) - (19)(191.5) / 4(109) - (19)²
a=(4414.5 - 3638.5) / (436-361)
a=776/75
a=10.35
b = n(∑xy)-(∑x)(∑y) / n(∑x² )-(∑x)²
b=4(191.5)-(19)(40.5) / 4 (109)-19²
b=766-769.5 /436-361
b=-3.5/75
b= - 0.04667
The model will be represented by the equation;
Y=10.35 -0.0466X
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Keyword : regression, model, best fit, data set
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