The regression equation is y = 16.585x - 639.769 and the linear correlation coefficient indicates a strong linear relationship
<h3>How to determine the regression equation?</h3>
To do this, we make use of a statistical calculator;
Using the statistical calculator, we have the following summary:
- Sum of X = 554
- Sum of Y = 4070
- Mean X = 69.25
- Mean Y = 508.75
- Sum of squares (SSX) = 725.5
- Sum of products (SP) = 12032.5
- Correlation coefficient, r = 0.9768
The regression equation is
ŷ = bx + a
Where:
b = SP/SSX = 12032.5/725.5 = 16.58511
a = MY - bMX = 508.75 - (16.59*69.25) = -639.76912
Hence, the regression equation is y = 16.585x - 639.769
<h3>The number of cans sold at 90 degrees F</h3>
This means that"
x = 90
So, we have:
y = 16.585 * 90 - 639.769
Evaluate
y = 852.881
Approximate
y = 853
Hence, 853 cans were sold at 90 degrees F
<h3>The linear correlation coefficient</h3>
In (a), we have:
r = 0.9768
This means that the linear correlation coefficient is 0.9768
<h3>The conclusion</h3>
We have:
r = 0.9768
The above value is closer to 1 because
|r| > 0.9
i.e.
0.9768 > 0.9
Hence, the linear correlation coefficient indicates a strong linear relationship
Read more about regression at:
brainly.com/question/17844286
#SPJ1
