1. The average gas price for 2010 is $2.22 according to the table provided.
2. To create a scatter plot representing the average gas prices from 2005-2015, plot the years on the x-axis and the corresponding gas prices on the y-axis. Each data point should be marked with a dot and connected to the adjacent points with a line to show the trend over time.
3. To find the linear regression equation that models the data, we can use a statistical software or Excel to perform a linear regression analysis on the data points. This will give us the equation of a line that best fits the data in the form y = mx + b, where y is the gas prices and x is the year.
4. The domain of the linear regression equation represents the range of years for which the equation is valid. In this case, it would be [2002, 2011] as that is the range of years provided in the table.
5. The range of the linear regression equation represents the range of possible gas prices. Since the equation is a straight line, the range would be all possible y-values (gas prices) within the given domain.
6. The average gas prices for 2010 can be determined by simply looking up the value in the table. To create a scatter plot, we plot the data points using the provided years and gas prices. For the linear regression equation, we use statistical tools to find the best-fitting line equation based on the data. The domain and range of the equation are determined based on the given range of years and the possible gas prices within that range.
Average gas prices in Columbia S.C. is listed in the following table.
YEAR GAS PRICES
2002 $ 0.70
2003 1.04
2004 1.15
2005 1.38
2006 1.86
2007 1.70
2008 2.55
2009 1.29
2010 2.22
2011 2.56
1. Using the table provided above list the average gas prices for 2010..
2. Describe or show a scatter plot accurately representing the average gas prices from 2005 - 2015
3. Find the linear regression equation that models the above data. Round to the nearest thousandth if needed.
4. List the domain of the linear regression equation in interval notation. Round to the nearest thousandth if needed.
5. List the range of the linear regression equation in interval notation. Round to the nearest thousand if needed.
6. Explain in 2-3 sentences in simple terms how you determined your answers.
3 answers
In number 4 can you show how you arrive at the years 2002, 2011?.
Apologies for the confusion in the previous response. In order to determine the domain of the linear regression equation, we consider the range of years for which data is available in the table. In this case, the available years are from 2002 to 2011.
Therefore, the domain of the linear regression equation would be [2002, 2011].
Therefore, the domain of the linear regression equation would be [2002, 2011].