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Trava [24]
2 years ago
15

The accompanying data on x = current density (mA/cm2) and y = rate of deposition (µm/min) appeared in an article. Do you agree w

ith the claim by the article's author that "a linear relationship was obtained from the tin-lead rate of deposition as a function of current density"?
col1 x 20 40 60 80
col2 y 0.24 1.10 1.71 2.12
Find the value of r2. (Round your answer to three decimal places.)
Mathematics
1 answer:
Sever21 [200]2 years ago
3 0

Answer:

r=\frac{4(321)-(200)(5.17)}{\sqrt{[4(12000) -(200)^2][4(8.6861) -(5.17)^2]}}=0.98726  

So then the correlation coefficient would be r =0.98726

And the determination coeffcient would be:

r^2 = 0.98726^2 = 0.975

And that means that the a linear model will explain about 97.5% of the variability in the data. So for this case we can conclude that we have a strong linear relationship.

Step-by-step explanation:

Data given

col1 x 20 40 60 80

col2 y 0.24 1.10 1.71 2.12

Solution to the problem

We can find the correlation coefficient we can use this formula:  

r=\frac{n(\sum xy)-(\sum x)(\sum y)}{\sqrt{[n\sum x^2 -(\sum x)^2][n\sum y^2 -(\sum y)^2]}}  

For our case we have this:

n=4 \sum x = 200, \sum y = 5.17, \sum xy = 321, \sum x^2 =12000, \sum y^2 =8.6861  

r=\frac{4(321)-(200)(5.17)}{\sqrt{[4(12000) -(200)^2][4(8.6861) -(5.17)^2]}}=0.98726  

So then the correlation coefficient would be r =0.98726

And the determination coeffcient would be:

r^2 = 0.98726^2 = 0.975

And that means that the a linear model will explain about 97.5% of the variability in the data. So for this case we can conclude that we have a strong linear relationship.

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