Please answer all.

The annual time series gives the index values of industrial production (IP) in the U.S. a. Graph the data using Excel (or any other software you may be able to use). Mark the correct graph among the following by placing a "y" (without the quotes) in the blank, and mark the incorrect graphs with a " n " (again, without the quotes). Graph 2: Graph 3: Graph 4: b. Use simple linear regression analysis to fit the following model: IPt=0+1t+t. Write down the estimated model, rounding to two (2) decimal places. The following linear trend expression was estimated using a time series with 17 time periods (that is, the values of t are 1,2,,17 ). yt=129.2+3.8t Calculate a 95% prediction interval for the value of Y at time period t=18 (i.e., h=1 period ahead). Use the fact that the average of the time values is x=9, the standard deviation of the time values is sX=5.05, and the regression standard error se=0.841. Take all calculations and the final answer to three (3) decimal places. Lower Bound = Upper Bound = The annual time series gives the index values of industrial production (IP) in the U.S. a. Graph the data using Excel (or any other software you may be able to use). Mark the correct graph among the following by placing a "y" (without the quotes) in the blank, and mark the incorrect graphs with a " n " (again, without the quotes). Graph 2: Graph 3: Graph 4: b. Use simple linear regression analysis to fit the following model: IPt=0+1t+t. Write down the estimated model, rounding to two (2) decimal places. The following linear trend expression was estimated using a time series with 17 time periods (that is, the values of t are 1,2,,17 ). yt=129.2+3.8t Calculate a 95% prediction interval for the value of Y at time period t=18 (i.e., h=1 period ahead). Use the fact that the average of the time values is x=9, the standard deviation of the time values is sX=5.05, and the regression standard error se=0.841. Take all calculations and the final answer to three (3) decimal places. Lower Bound = Upper Bound =