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The Quality of Oil Is Measured in API Gravity Degrees

question 140

Essay

The quality of oil is measured in API gravity degrees - the higher the degrees API, the higher the quality. The table shown below is produced by an expert in the field, who believes that there is a relationship between quality and price per barrel.  Oil degrees API  Price per barrel (in $ ) 27.012.0228.512.0430.812.3231.312.2731.912.4934.512.7034.012.8034.713.0037.013.0041.013.1741.013.1938.813.2239.313.27\begin{array} { | c | c | } \hline \text { Oil degrees API } & \text { Price per barrel (in } \$ \text { ) } \\\hline 27.0 & 12.02 \\\hline 28.5 & 12.04 \\\hline 30.8 & 12.32 \\\hline 31.3 & 12.27 \\\hline 31.9 & 12.49 \\\hline 34.5 & 12.70 \\\hline 34.0 & 12.80 \\\hline 34.7 & 13.00 \\\hline 37.0 & 13.00 \\\hline 41.0 & 13.17 \\\hline 41.0 & 13.19 \\\hline 38.8 & 13.22 \\\hline 39.3 & 13.27 \\\hline\end{array} A partial Minitab output follows.
Descriptive Statistics  Variable N Mean  StDev  SE Mean  Degrees 1334.604.6131.280 Frice 1312.7300.4570.127\begin{array} { | l | r | r | r | r | } \hline \text { Variable } & \mathrm { N } & \text { Mean } & \text { StDev } & \text { SE Mean } \\\hline \text { Degrees } & 13 & 34.60 & 4.613 & 1.280 \\\hline \text { Frice } & 13 & 12.730 & 0.457 & 0.127 \\\hline\end{array} Covariances  Degrees  Price  Degrees 21.281667 Price 2.0267500.208833\begin{array} { | l | r | r | } \hline & \text { Degrees } & \text { Price } \\\hline \text { Degrees } & 21.281667 & \\\hline \text { Price } & 2.026750 & 0.208833 \\\hline\end{array} Regression Analysis  Fredictor  Coef  StDev TP Constant 9.43490.286732.910.000 Degrees 0.0952350.00822011.590.000\begin{array} { | l | r | r | r | r | } \hline \text { Fredictor } & \text { Coef } & \text { StDev } & \mathrm { T } & \mathrm { P } \\\hline \text { Constant } & 9.4349 & 0.2867 & 32.91 & 0.000 \\\hline \text { Degrees } & 0.095235 & 0.008220 & 11.59 & 0.000 \\\hline\end{array} S = 0.1314 R-Sq = 92.46% R-Sq(adj) = 91.7%
Analysis of Variance  Source  DF  SS  MS  F  P  Regression 12.31622.3162134.240.000 Residual Error 110.18980.0173 Total 122.5060\begin{array} { | l | r | r | r | r | r | } \hline \text { Source } & \text { DF } & \text { SS } & \text { MS } & \text { F } & \text { P } \\\hline \text { Regression } & 1 & 2.3162 & 2.3162 & 134.24 & 0.000 \\\hline \text { Residual Error } & 11 & 0.1898 & 0.0173 & & \\\hline \text { Total } & 12 & 2.5060 & & & \\\hline\end{array} a. Determine the standard error of estimate and describe what this statistic tells you.
b. Determine the coefficient of determination and discuss what its value tells you about the two variables.
c. Calculate the Pearson correlation coefficient. What sign does it have? Why?

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