The accompanying data was read from a graph that appeared in a recent study. The independent variable is $\mathrm { SO } _ { 2 } \text { deposition rate } \left( \mathrm { mg } / \mathrm { m } ^ { 2 } / \right. \text { day) }$ and the dependent variable is steel weight loss (g/m $2$ ). $$\begin{array} { c c c c c c c }
\hline x & 14 & 18 & 40 & 43 & 45 & 112 \
\hline y & 280 & 350 & 470 & 500 & 560 & 1200 \
\hline
\end{array}$$
a. Construct a scatter plot. Does the simple linear regression model appear to be reasonable in this situation?
b. Calculate the equation of the estimated regression line.
c. What percentage of observed variation in steel weight loss can be attributed to the model relationship in combination with variation in deposition rate?
d. Because the largest x value in the sample greatly exceeds the others, this observation may have been very influential in determining the equation of the estimated line. Delete this observation and recalculate the equation. Does the new equation appear to differ substantially from the original one (you might consider predicted values)?

Question

The accompanying data was read from a graph that appeared in a recent study. The independent variable is $\mathrm { SO } _ { 2 } \text { deposition rate } \left( \mathrm { mg } / \mathrm { m } ^ { 2 } / \right. \text { day) }$ and the dependent variable is steel weight loss (g/m $2$ ). $$\begin{array} { c c c c c c c } 
\hline x & 14 & 18 & 40 & 43 & 45 & 112 \
\hline y & 280 & 350 & 470 & 500 & 560 & 1200 \
\hline
\end{array}$$ 
a. Construct a scatter plot. Does the simple linear regression model appear to be reasonable in this situation?
b. Calculate the equation of the estimated regression line.
c. What percentage of observed variation in steel weight loss can be attributed to the model relationship in combination with variation in deposition rate?
d. Because the largest x value in the sample greatly exceeds the others, this observation may have been very influential in determining the equation of the estimated line. Delete this observation and recalculate the equation. Does the new equation appear to differ substantially from the original one (you might consider predicted values)?

Quizplus · Accepted Answer

The Answer of The accompanying data was read from a graph that appeared in a recent study. The independent variable is $\mathrm { SO } _ { 2 } \text { deposition rate } \left( \mathrm { mg } / \mathrm { m } ^ { 2 } / \right. \text { day) }$ and the dependent variable is steel weight loss (g/m $2$ ). $$\begin{array} { c c c c c c c } 
\hline x & 14 & 18 & 40 & 43 & 45 & 112 \
\hline y & 280 & 350 & 470 & 500 & 560 & 1200 \
\hline
\end{array}$$ 
a. Construct a scatter plot. Does the simple linear regression model appear to be reasonable in this situation?
b. Calculate the equation of the estimated regression line.
c. What percentage of observed variation in steel weight loss can be attributed to the model relationship in combination with variation in deposition rate?
d. Because the largest x value in the sample greatly exceeds the others, this observation may have been very influential in determining the equation of the estimated line. Delete this observation and recalculate the equation. Does the new equation appear to differ substantially from the original one (you might consider predicted values)?

The Accompanying Data Was Read from a Graph That Appeared SO2 deposition rate (mg/m2/ day) \mathrm { SO } _ { 2 } \text { deposition rate } \left( \mathrm { mg } / \mathrm { m } ^ { 2 } / \right. \text { day) }SO2​ deposition rate (mg/m2/ day)

The Accompanying Data Was Read from a Graph That Appeared $\mathrm { SO } _ { 2 } \text { deposition rate } \left( \mathrm { mg } / \mathrm { m } ^ { 2 } / \right. \text { day) }$