Answer:
[tex]y=1.98 x -24.34[/tex]
Step-by-step explanation:
Assuming the following data
X: 44, 44, 11, 11, 55
Y: 66, 55, -1, -3, 88
We want to find a linear model [tex] Y= mx +b[/tex]
For this case we need to calculate the slope with the following formula:
[tex]m=\frac{S_{xy}}{S_{xx}}[/tex]
Where:
[tex]S_{xy}=\sum_{i=1}^n x_i y_i -\frac{(\sum_{i=1}^n x_i)(\sum_{i=1}^n y_i)}{n}[/tex]
[tex]S_{xx}=\sum_{i=1}^n x^2_i -\frac{(\sum_{i=1}^n x_i)^2}{n}[/tex]
So we can find the sums like this:
[tex]\sum_{i=1}^n x_i =44+44+11+11+55=165[/tex]
[tex]\sum_{i=1}^n y_i =66+55-1-3+88=205[/tex]
[tex]\sum_{i=1}^n x^2_i =7139[/tex]
[tex]\sum_{i=1}^n y^2_i =15135[/tex]
[tex]\sum_{i=1}^n x_i y_i =10120[/tex]
With these we can find the sums:
[tex]S_{xx}=\sum_{i=1}^n x^2_i -\frac{(\sum_{i=1}^n x_i)^2}{n}=7139-\frac{165^2}{5}=1694[/tex]
[tex]S_{xy}=\sum_{i=1}^n x_i y_i -\frac{(\sum_{i=1}^n x_i)(\sum_{i=1}^n y_i)}{n}=10120-\frac{165*205}{5}=3355[/tex]
And the slope would be:
[tex]m=\frac{3355}{1694}=1.98[/tex]
Nowe we can find the means for x and y like this:
[tex]\bar x= \frac{\sum x_i}{n}=\frac{165}{5}=33[/tex]
[tex]\bar y= \frac{\sum y_i}{n}=\frac{205}{5}=41[/tex]
And we can find the intercept using this:
[tex]b=\bar y -m \bar x=41-(1.98*33)=-24.34[/tex]
So the line would be given by:
[tex]y=1.98 x -24.34[/tex]