ANSWER and EXPLANATION
a) First we have to make a scatter plot. We do this by plotting the calues of High Temperature on the x axis and Number of cans sold on the y axis:
b) We want to find and graph the linear regression equation that models the data.
The linear regression equation will be in the form:
y = a + bx
[tex]\begin{gathered} \text{where} \\ a\text{= }\frac{(\sum ^{}_{}y)(\sum ^{}_{}x^2)\text{ - (}\sum ^{}_{}x)(\sum ^{}_{}xy)}{n(\sum ^{}_{}x^2)\text{ }-\text{ (}\sum ^{}_{}x)^2} \\ \text{and b = }\frac{n(\sum ^{}_{}xy)\text{ - (}\sum ^{}_{}x)(\sum ^{}_{}y)}{n(\sum ^{}_{}x^2)\text{ }-\text{ (}\sum ^{}_{}x)^2} \end{gathered}[/tex]
We have from the question that:
x = High Temperature
y = Number of cans added
So, we have to find xy and x^2. We will form a new table:
Now, we will find a and b:
[tex]\begin{gathered} a\text{ = }\frac{(4120)(39090)\text{ - (}554)(297220)}{8(39090)\text{ }-554^2} \\ a\text{ = }\frac{\text{ 161050800 - 164659880}}{312720\text{ - 306916}} \\ a\text{ = }\frac{-3609080}{5804} \\ a\text{ }\cong\text{-62}2 \end{gathered}[/tex][tex]\begin{gathered} b\text{ = }\frac{8(297220)\text{ - (554})(4120)}{5804} \\ b\text{ = }\frac{2377760\text{ - 2282480}}{5804} \\ b\text{ = }\frac{95280}{5804} \\ b\text{ }\cong\text{ 16} \end{gathered}[/tex]
Therefore, the linear regression equation is:
y = -622 + 16x
Now, let us graph it using values of x (High Temperature):
That is the Linear Regression Graph.
c) To predict soft drink sales if the temperature is 95 degrees Farenheit, we will put the x value as 95 and find y. That is:
y = -622 + 16(95)
y = 898
The model predicts that 898 cans of soft drinks will be sold when the High Temperature is 95 degrees Farenheit.
