Refer to Exercise 14.63.

a. Fit a simple linear regression model to the stock price data.
b. Plot the fitted regression line on a scatterplot of the data.
c. Forecast the 2016 and 2017 closing prices using the regression model.
d. Construct 95% prediction intervals for the forecasts of part c. Interpret the intervals in the context of the problem.
e. Obtain the time series residuals for the simple linear model and use the Durbin-Watson d-statistic to test for the presence of autocorrelation.

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Closing Price Year Year Closing Price 1995 1996 1997 1998 2006 2007 2008 2009 48.71 56.15 53.37 53.99 41.05 50.75 65.50 49.00 36.31 48.44 55.75 40.00 46.60 46.65 39.43 2010 2011 2012 2013 2014 1999 2000 2001 2002 2003 47.91 56.23 65.50 38.33 45.02 44.91 2004 2015 2005