Individual Question #2 Living Green

Your Individual Question:

Examine relationships between renewable energy and oil prices using regression analysis. Do the variables exhibit strong relationships? Are these relationships linear?

Steps:

• Make sure to read about examining relationships between variables, confidence intervals and significance tests in the assigned readings for this week module.

• Estimate the linear regression model using the data in the "Data" worksheet. Ignore Year and Month variables! Make sure to watch the instructional video to see a demonstration of how to estimate regression model in Excel.

• If the crude oil prices and renewable energy consumption are related, the slope of the Crude Oil variable in the regression model will be significant. To verify whether this is in fact true, test the hypothesis about slope significance. HINT: locate the slope estimate in the regression output, its p -value and confidence bounds. Remember that you reject null hypotheses about the estimate insignificance if its p -value is less than desired significance level or if the confidence interval does not include 0.0. Use 5% significance and 95% confidence interval. Alternatively, you may use t -statistic and t -test to test the slope significance.
• Summarize your results. Do oil prices have an impact on renewable energy consumption? Is the assumption of linearity met in this sample?
• What is the sign of the slope? Do oil price increases tend to reduce or increase the renewable energy consumption in the U.S.? Can you say by how much the $1 dollar change in oil prices would reduce or increase the energy consumption?

Price: $12.89

Solution: The downloadable solution consists of 7 pages, 589 words and 1 charts.
Deliverable: Word Document