Use the following data set to answer the Questions: $\begin{array} { | l | l | l | l | l | l | l | l | l }
\hline \begin{array} { l }
\text { Length of } \
\text { commute in } \
\text { miles } ( x )
\end{array} & 2 & 10 & 8 & 30 & 12 & 70 & 15 & 20 \
\hline \begin{array} { l }
\text { Time of } \
\text { commute in } \
\text { minutes (y) }
\end{array} & 5 & 25 & 20 & 45 & 25 & 80 & 30 & 35 \
\hline
\end{array}$
-What is the slope of the regression line?
A) 0.9
B) 1.0
C) 1.1
D) 1.5

Question

Use the following data set to answer the  Questions:  $\begin{array} { | l | l | l | l | l | l | l | l | l } 
\hline \begin{array} { l } 
\text { Length of } \
\text { commute in } \
\text { miles } ( x )
\end{array} & 2 & 10 & 8 & 30 & 12 & 70 & 15 & 20 \
\hline \begin{array} { l } 
\text { Time of } \
\text { commute in } \
\text { minutes (y) }
\end{array} & 5 & 25 & 20 & 45 & 25 & 80 & 30 & 35 \
\hline
\end{array}$
-What is the slope of the regression line?
A) 0.9
B) 1.0
C) 1.1
D) 1.5

Quizplus · Accepted Answer

The slope of the regression line ($m$) can be calculated using the formula $m = \frac{n(\sum xy) - (\sum x)(\sum y)}{n(\sum x^2) - (\sum x)^2}$, where $n$ is the number of data points. Calculating the sums: $\sum x = 167$, $\sum y = 265$, $\sum xy = 6055$, $\sum x^2 = 6149$, and $n = 8$. Plugging these into the formula gives $m \approx 1.1$.

Use the Following Data Set to Answer the Questions