Y= mx +c ( y is a function of x and some constant)
According to theory , all y should obey the function formula so if we plot all y then we will get a straight line . But in practical, we always get Y which are slightly deviated from what their values are supposed to be. So if we plot then instead of getting all values of y on a straight line we are getting scattered y points nearby a straight line but not exact on straight line. so our goal is how can we fit the all y near to a straight line means how we can minimize the difference between actual y value( after observation) and corresponding y value of the fitted straight line.
That is the main reason to find out SSE which is minimum .( considering different m value of an equation).
How to compute SSE:
1. First check which is function of other.( which is y)
It will definitely mentioned in question. For example, P(T) was mentioned in graded question. so P is function of T. It means P=y and T=x
2. If the table ( different x,y - observations value)is given, that means m is already given in equation.
Y=mx+c. [c may be constant or 0].
example:
1. Activity 3.5
If a line fit y=x+1 is given for the data as shown in Table AQ-3.1, then compute the Sum Squares Error (SSE).
Here, m=1, c=1