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Asuss Airline would like to forecast the number of passengers who will fly from Singapore to Shanghai in 2018. The data is given in Table 3-1. The consultant first developed a time series regression model, using time as the independent variable and the number of passengers as the dependent variable to fit the data. The fitted line is shown in Figure 3-1, and the autocorrelation function for the residuals obtained from the regression model is shown in Figure 3-2. Table 3-1: Number of passengers flying from Singapore to Shanghai Number of passengers (1,000) Number of passengers (1,000) Year 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 Passengers 160 100 22.8 26.1 29.4 34.5 37.6 40.3 39.5 46.3 45.8 48.0 54.6 61.9 Year 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 15 Figure 3-1: Fitted line plot Ha 79.9 96.3 109.0 116.0 117.2 124.9 136.6 144.8 147.9 150.1 151.9

Asuss Airline would like to forecast the number of passengers who will fly from Singapore to Shanghai in 2018. The data is given in Table 3-1. The consultant first developed a time series regression model, using time as the independent variable and the number of passengers as the dependent variable to fit the data. The fitted line is shown in Figure 3-1, and the autocorrelation function for the residuals obtained from the regression model is shown in Figure 3-2. Table 3-1: Number of passengers flying from Singapore to Shanghai Number of passengers (1,000) Number of passengers (1,000) Year 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 Passengers 160 100 22.8 26.1 29.4 34.5 37.6 40.3 39.5 46.3 45.8 48.0 54.6 61.9 Year 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 15 Figure 3-1: Fitted line plot Ha 79.9 96.3 109.0 116.0 117.2 124.9 136.6 144.8 147.9 150.1 151.9

Linear Algebra: A Modern Introduction
Linear Algebra: A Modern Introduction
4th Edition
ISBN:9781285463247
Author:David Poole
Publisher:David Poole
Chapter7: Distance And Approximation
Section7.3: Least Squares Approximation
Problem 31EQ
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Write down the regression model with the unknown coefficients.

Question 3 Asuss Airline would like to forecast the number of passengers who will fly from Singapore to Shanghai in 2018. The data is given in Table 3-1. The consultant first developed a time series regression model, using time as the independent variable and the number of passengers as the dependent variable to fit the data. The fitted line is shown in Figure 3-1, and the autocorrelation function for the residuals obtained from the regression model is shown in Figure 3-2. Table 3-1: Number of passengers flying from Singapore to Shanghai Number of Number of Year passengers (1,000s) Year passengers (1,000s) 1993 22.8 2006 69.9 79.9 26.1 29.4 34.5 1994 2007 1995 2008 96.3 1996 2009 109.0 1997 37.6 2010 116.0 1998 40.3 2011 117.2 1999 39.5 2012 1249 2000 45.4 2013 136.6 2001 46.3 2014 144.8 2002 45.8 2015 147.9 2003 48.0 2016 150.1 2004 54.6 2017 1519 2005 61.9 160 140 120 100 20 10 15 20 Time Figure 3-1: Fitted line plot sabuassed
Transcribed Image Text:Question 3 Asuss Airline would like to forecast the number of passengers who will fly from Singapore to Shanghai in 2018. The data is given in Table 3-1. The consultant first developed a time series regression model, using time as the independent variable and the number of passengers as the dependent variable to fit the data. The fitted line is shown in Figure 3-1, and the autocorrelation function for the residuals obtained from the regression model is shown in Figure 3-2. Table 3-1: Number of passengers flying from Singapore to Shanghai Number of Number of Year passengers (1,000s) Year passengers (1,000s) 1993 22.8 2006 69.9 79.9 26.1 29.4 34.5 1994 2007 1995 2008 96.3 1996 2009 109.0 1997 37.6 2010 116.0 1998 40.3 2011 117.2 1999 39.5 2012 1249 2000 45.4 2013 136.6 2001 46.3 2014 144.8 2002 45.8 2015 147.9 2003 48.0 2016 150.1 2004 54.6 2017 1519 2005 61.9 160 140 120 100 20 10 15 20 Time Figure 3-1: Fitted line plot sabuassed
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