Reference no: EM13734078
1. Using regression analysis, (i.e. do not use the forecast function in Excel) forecast the average annual consumption of natural gas for each group in 2014. That is, how much natural gas is consumed during an average month? How confident would you be in concluding the coefficient estimates are not equal to zero? Why? How do you know? Interpret the coefficient estimates.
2. Using regression analysis, forecast the monthly consumption of natural gas for commercial consumers in 2013 using the data from 1989-2012. How confident would you be in concluding the coefficient estimates are not equal to zero? Why? How do you know? Interpret the coefficient estimates
3. Compare the forecasted values in 2 to the actual 2013 values for commercial consumers. See the hint below for how to do this. How confident would you be in concluding the coefficient estimates are not equal to zero? Why? How do you know? Discuss these results in terms of the accuracy of your forecast.
4. Estimate the demand for natural gas by each group over the entire period using a simple linear regression.How confident would you be in concluding the coefficient estimates are not equal to zero? Why? How do you know? Interpret the estimated coefficients. Are the signs of the estimated coefficients as you would expect?
5. Improve your estimate of demand for residential consumers by finding and including in your analysis other data that will help estimate the demand for natural gas. Recall the determinants of demand. Describe the additional data you included and note where you obtained it. How confident would you be in concluding the coefficient estimates are not equal to zero? Why? How do you know? Interpret the estimated coefficients. Are the signs of the estimated coefficients as you would expect?
6. Write a summary paragraph(s) describing this project. This part will be graded only on style. For example, describe what the project involved, what you found out about prices and consumption of natural gas in your state, what you learned about the accuracy of forecasting, etc.
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