Consider the following results of a multiple regression model of dollar price of unleaded gas (dependent variable) and a set of independent variables: price of crude oil, value of S&P500, price U.S. Dollars against Euros, personal disposal income (in million of dollars) :
| Coefficient | t-statistics | |
| Intercept | 0.5871 | 68.90 |
| Crude Oil | 0.0651 | 32.89 |
| S&P 500 | -0.0020 | 18.09 |
| Price of $ | -0.0415 | 14.20 |
| PDI | 0.0001 | 17.32 |
R-Square = 97%
What is the interpretation of coefficient for Price of $?
| a) |
Every 1 unit increase in the value of $ again euros will cause unleaded gas price to increase by 4.15 cents. |
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| b) |
Every 1 unit increase in the value of $ again euros will cause unleaded gas price to decrease by 4.15%. |
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| c) |
Every 1% increase in the value of $ again euros will cause unleaded gas price to decrease by 4.15 cents. |
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| d) |
Every 1 unit increase in the value of $ again euros will cause unleaded gas price to decrease by 4.15 cents. |
correct answer : (d ) Every 1 unit increase in the value of $ again euros will cause unleaded gas price to decrease by 4.15 cents.
Regression coefficients also known as slope : represent the mean change in the response variable for one unit of change in the predictor variable
As the value of regreesion coefficient between unleaded gas price and value of $ against euro is negative, it implies that for every 1 unit increase in price of $ against euro will bring opposite change, that is, decrease in value of gas by $0.0415 or 4.15 cents
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