Do excel spreadsheet with this data. You will use excel to run a linear regression using this data.

We don't know what the real demand is for this good but we can use linear regression analysis to obtain a linear approximation of it. In other words, if the unknown demand for this good is

Q_D = F (P; P_R, M)

Where Q_D is the quantity demanded for this good, P is the price per unit, P_R is the price of the related good(s) in consumption (substitute or complement) and M is consumer income.

A linear approximation of this demand equation looks like

Q_D = a + b P + c P_R + d M

You will use the data provided and excel to estimate the unknown parameters a, b, c, and d.

Then, you will use these parameter estimates to analyze the regression results and produce useful information for decision making and provide recommendations to the suppliers of this good. Among other things, you will report the estimated "extended" and "reduced" equations of demand; draw the demand line; calculate and interpret the elasticities of demand; interpret the values of parameter estimates; discuss the statistical significance of the independent variables; make forecasts, build confidence intervals, etc.

DATA FOR COFFEE DEMAND ( 1991 - 2014 ) Exhibit 1 USA LB NY Robusta Calendar years In thousand Coffee Price (CP Four or More Earners 60LB bags LBJ Current dollars Tea Prices (CP LB) 1991 43,648 50 75,323 0.759 1992 50,466 44 77,910 0.728 1993 42,524 53 80,218 0.732 1994 35,576 120 83,863 0.677 1995 37,635 127 85,086 0.675 1996 42,779 83 89,585 0.754 1997 44,755 81 99,882 0.935 1998 46,266 84 100,147 0.928 1999 50,041 68 101,603 0.834 2000 52,287 42 104,729 0.851 2001 47,113 27 109,976 0.725 2002 47,606 31 110,871 0.684 2003 50,072 38 117,798 0.688 2004 51,005 37 119,190 0.764 2005 50,692 53 124,164 0.747 2006 52,160 70 129,511 0.850 2007 53,282 38 132,352 0.923 2008 53,409 106 130,498 1.098 2009 51,872 77 132,955 1.236 2010 53,632 84 137,176 1.308 2011 57,405 116 141,094 1.325 2012 57,323 111 145,817 1.314 2013 59,435 101 163,264 1.298 2014 60,643 106 154,995 1.234