average gas prices
columbia sc
year 2002 $0.70
year 2003 $1.04
year 2004 $1.15
year 2005 $1.38
year 2006 $ 1.86
year 2007 $1.70
year 2008 $ 2.55
year 2009 $1.29
year 2010 $2.22
year 2011 $2.56
y = 0.176x - -351.621
14. List the domain of the linear regression equation in interval notation. Round to the nearest thousandth if needed.
The domain of the linear regression equation represents the range of values for the independent variable, which in this case is represented by the year. Looking at the given data, the years range from 2002 to 2011, so the domain is the interval [2002, 2011].
15. List the range of the linear regression equation in interval notation. Round to the nearest thousandth if needed.
The range of the linear regression equation represents the range of values for the dependent variable, which in this case is represented by the gas prices. Based on the given data, the range of the linear regression equation can be determined by finding the minimum and maximum gas prices from the data set.
The minimum gas price is $0.70 in the year 2002, and the maximum gas price is $2.56 in the year 2011. Therefore, the range of the linear regression equation is [0.70, 2.56].
Explain in 2-3 sentences how you determined your answers
To determine the domain of the linear regression equation, I observed the given data and identified the range of years for which gas prices were provided, which was from 2002 to 2011. The domain represents the possible values for the independent variable, which in this case is the year.
To find the range of the linear regression equation, I examined the gas prices provided for each corresponding year and identified the minimum and maximum values. Based on this data, the range was determined to be the interval between the lowest and highest gas prices, which is from $0.70 to $2.56.
17. Is there a trend in the data? Does there seem to be a positive correlation, a negative correlation, or neither?
*
1 point
A. The data represents a positive correlation.
B. The data represents a negative correlation.
C. The data does not have any correlation
A. The data represents a positive correlation.
Use the linear regression equation to predict how much you expect gas to cost in 2025?
To predict how much gas is expected to cost in 2025 using the linear regression equation, you can substitute the year 2025 into the equation. Using the equation y = 0.176x - 351.621, where x represents the year and y represents the gas price, we can calculate the predicted gas price as follows:
y = 0.176 * 2025 - 351.621
y = 356.4 - 351.621
y ≈ $4.779
Therefore, it is predicted that gas will cost approximately $4.779 in 2025.