Consider the economy and voting example from Section 7.1 Fit the linear regression model to the data through 2012; these are available in the folder ElectionsEconomy. Make a forecast for the incumbent party's share of the two-party vote in a future election where economic growth is 2%.

1. (a)Compute the point forecast the standard deviation of the predicted expectation from (9.1), and the standard deviation of the predicted value from (9.2)
2. (b)Now compute these using the relevant prediction functions discussed in section 9.2. Check that you get the same values as in (a).
3. (c)The formulas used in (a) are for a frequentist approach, meaning no distribution is assumed on the parameters. What are the modeling assumptions used in the functions in (b)?

Example: Elections and the economy 7.1 Example: predicting presidential vote share from the economy Figure 7.1 tells a story of elections and the economy. It's based on the \"bread and peace" model created by political scientist Douglas Hibbs to forecast elections based solely on economic growth (with corrections for wartime, notably Adlai Stevenson's exceptionally poor performance in 1952 and Hubert Humphrey's loss in 1968, years when Democratic presidents were presiding over unpopular wars). Better forecasts are possible using additional information (most notably, incumbency and opinion polls), but what is impressive here is that this simple model does pretty well. Fitting a linear model to data Figure 7.2 displays the economy and elections data as a prediction problem, with a tted line predicting y (vote share) from x (economic performance). The data are in the le hibbs . da t, with the incumbent party's vote percentage of the twoparty vote coded as vote and average personal income growth in the previous years coded as growth. We rst read in and display the data:1 hibbs