The data in Strategic represent the amount of oil, in billions of barrels, held in the U.S. strategic oil reserve, from 1981 through 2008.
Step 1: Copy the data and paste it into the Excel sheet.
Step 2: To create a scatter plot of the data, go to Insert -> Scatter -> Scatter with only markers. The scatter plot will instantly display on the screen.
Assign a variable t depicting the years. Calculate the values of t squared corresponding to the t series.
Considering oil reserves as y, compute log y. Go to Formulas -> Math and Trigo -> LOG10 In cell E2, enter the number as B2 under the LOG10 dialog box. Auto-fill this formula till cell E29.
Step 1: To calculate the linear trend, go to Data -> Data Analysis.
Select the tool of Regression from the Data Analysis dialog box.
Step 2: In the Regression dialog box, enter the following: Input y range: B1 to B29 Input x range: C1 to C29 Select the tick boxes: label, line fit plots.
Step 3: click on ok. The regression results are displayed:
Step 4: From the regression coefficients given in the summary output, we get the following linear forecasting equation:
Y= 396.19 + 11.03 x
The plot of the trend line is:
Step 1: To calculate the quadratic trend, go to Data -> Data Analysis.
Select the tool of Regression from the Data Analysis dialog box.
Step 2: In the Regression dialog box, enter the following:
Input y range: B1 to B29 Input x range: C1 to C29 Select the tick boxes: label, line fit plots.
Step 3: click on ok. The regression results are displayed:
Step 4: From the regression coefficients given in the summary output, we get the following
linear forecasting equation:
Y= 325.07 + 25.26 x -0.49 x2
The plot of the trend line is:
Step 1: To calculate the exponential trend, go to Data -> Data Analysis.
Select the tool of Regression from the Data Analysis dialog box.
Step 2: In the Regression dialog box, enter the following:
Input y range: E1 to C29
Input x range: C1 to C29
Select the tick boxes: label, line fit plots.
Step 3: click on ok. The regression results are displayed:
Step 4: compute the figure of 10^intercept.
The intercept comes out to be 388.59 Now, we get the following exponential forecasting equation: Y = 388.59*10^0.0098*t Step 5: The plot of the trend line is:
The coefficients of determination for the three time series models we developed are:
Linear model_R2 = 68.24% Quadratic model_R2 = 75.25% Exponential_R2 = 55.7%
Since the coefficient of determination is the highest for the quadratic trend, therefore, the quadratic model seems the most appropriate
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