Fitting Data with Linear Models

1.  Open the file CarsAndTrucks_By_Year2003.xls containing the following data from the Bureau of Labor Statistics.

a. Make an X-Y scatter plot of the data. For instructions on how to make an X-Y scatter plot of the data click here.

b. Add a trendline to your chart in a. Include the equation for the trendline and the R-squared value. For instructions on how to make add a trendline including the equation and R-squared value, click here.

c. Predict how many cars and trucks there will be in the US in the year 2008.

d. Predict when there were no passenger cars and trucks in the US. How accurate is the model in this prediction?  In 2-3 sentences justify whether or not the equation should be used to predict when there were no passenger cars and trucks.

e. Predict the number of cars in US in 2050.  Do you think your answer is a good estimate? In 2-3 sentences justify whether or not the equation should be used to predict how many passenger cars and trucks there will be in 2050.
 

2.  Open the file Coal_Consumption2003.xls containing data from the U.S. Energy Administration.  The unit of measure here is quads, a standard measure standing for quadrillion BTU's. (A British Thermal Unit is a unit of energy, the amount of energy needed to raise 1 pound of water 1 degree Fahrenheit when the water is about 39.2 degrees Fahrenheit.)

a. Make an X-Y scatterplot of the data. Add a trendline, including the equation of the line and the R-squared value.

b. Predict coal consumption in the year 2008. 

c. According to your model, when will the coal consumption be 30 quads?

d. In a short well-written paragraph, discuss social, political, or physical changes which might affect the accuracy of predictions using this model.