How can a system of equations be used to predict media use?

Suppose we have collected data about media use, as follows:

Prnt media:
- year 0 (1994) #-># 3 hrs per person per day
- year 1 (1995) #-># 2.5 hrs per person per day
- ...

Online media:
- year 0 (1994) #-># 0.5 hrs per person per day
- year 1 (1995) #-># 0.75 hrs per person per day - ...
- ...

We assume a simple, linear model, so that we can easily fill in the yearly data and we already have sufficient information to determine the equations.

Let's denote by #x# the number of years passed since 1994 and by #y# the average number of hours per person per day spent on media use .

Our linear equations will have the general form #y=ax+b#

For print media use we have:
#ax+b = 3# when #x = 0# #-># #b = 3#
and #ax+b = 2.5# when #x=1# #-># #a+b=2.5# #-># #a=-0.5#
Therefore, our equation for print media use is #y = -0.5x+3#

For online media use we have:
#ax+b=0.5# when #x=0# #-># #b=0.5#
and #ax+b=0.75# when #x=1# #-># #a+b=0.75# #-># #a=0.25#
Therefore, our equation for online media use is #y=0.25x+0.5#

Now, we have a system of two linear equations allowing predictions of media use at various data points. (Of course, this is a fictitious example and an oversimplification meant just to illustrate the general idea. We can build a more realistic model by using exponential instead of linear functions).