The table below shows the shipments (in millions of dollars) of consumer durables and nondurables in Canada. Is there a linear relationship between the shipments of durables and nondurables? In other words, if we know the value of nondurables shipped in any one year, can we predict the value of durables during that year? (Hint: Make the value of nondurables the independent variable. ) According to the model, if at any given year the nondurables shipment is $208,000 million, what would the predicted amount for durables shipment be for the same year? Construct a confidence interval for the average y value for $208,000 million. Use the t statistic to test to determine whether the slope is significantly different from zero. Use @ = 0.05. Year Nondurables Durables 1997 $168,619 $65,619 1998 172,197 68,623 1999 176,917 74,234 2000 181,437 79,798 2001 183,404 82,857 2002 188,191 89,937 2003 191,910 92,945 2004 195,773 95,414 2005 198,610 100,138 2006 201,837 107,247 2007 207,919 114,703 2008 210,979 120,763 2009 212,628 117,706 2010 215,858 123,783 2011 218,637 126,250 2012 220,268 129,730*Round your answers to 4 decimal places. **Do not round the intermediate values. Round your answer to 6 decimal places. ** *Do not round the intermediate values. Round your answer to 2 decimal places. ** **Round the intermediate values to 4 decimal places. Round your answers to 0 decimal place. 0.9975 The / value denotes a strong positive correlation. V -148029.1915 1.2585 * * X (208,000) 113739 * * 112723 114756 Confidence Interval = * ** * to Observed t = 53.09996 * * * The decision is to reject the null hypothesis T