The following table shows data for the cost of natural gas in Maryland (in dollars per Million Btu) for x years since 1990. Year x Price in $ per Million Btu 1990 6.31 1991 6.14 1992 6.32 1993 6.75 1994 6.8 1995 6.34 1996 7.46 1997 8.12 1998 8.04 1999 8.25 2000 9.58 2001 11.28 2002 9.25 a. Define the explanatory and response variables for this problem. b. Use the calculator to obtain the linear regression line of best fit for the original prices; round to three decimal places. Write this prediction equation in the form: a. In a brief sentence, interpret the slope in the context of the problem.
The following table shows data for the cost of natural gas in Maryland (in dollars per Million Btu) for x years since 1990. Year x Price in $ per Million Btu 1990 6.31 1991 6.14 1992 6.32 1993 6.75 1994 6.8 1995 6.34 1996 7.46 1997 8.12 1998 8.04 1999 8.25 2000 9.58 2001 11.28 2002 9.25 a. Define the explanatory and response variables for this problem. b. Use the calculator to obtain the linear regression line of best fit for the original prices; round to three decimal places. Write this prediction equation in the form: a. In a brief sentence, interpret the slope in the context of the problem.
Chapter6: Exponential And Logarithmic Functions
Section6.8: Fitting Exponential Models To Data
Problem 3TI: Table 6 shows the population, in thousands, of harbor seals in the Wadden Sea over the years 1997 to...
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The following table shows data for the cost of natural gas in Maryland (in dollars per Million Btu) for x years since 1990.
|
Year |
|
Price in $ per Million Btu |
|
1990 |
|
6.31 |
|
1991 |
|
6.14 |
|
1992 |
|
6.32 |
|
1993 |
|
6.75 |
|
1994 |
|
6.8 |
|
1995 |
|
6.34 |
|
1996 |
|
7.46 |
|
1997 |
|
8.12 |
|
1998 |
|
8.04 |
|
1999 |
|
8.25 |
|
2000 |
|
9.58 |
|
2001 |
|
11.28 |
|
2002 |
|
9.25 |
a. Define the explanatory and response variables for this problem.
b. Use the calculator to obtain the linear regression line of best fit for the original prices; round to three decimal places.
Write this prediction equation in the form:
a. In a brief sentence, interpret the slope in the context of the problem.
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