Linear Algebra: Linear Combination

Linear combinations of vectors are sums of a set of vectors multilpied by constants. For example, if we had a = (0,2) and b = (4,1), a linear combination of them could be 5 a + 2 b = (0,10) + (8,2) = (8,8).

Linear Algebra: Linear Independence

We can imagine two vectors that point in the same direction, that their is a constant c that when multiplied by one of the vectors gets us the other vector. a = (1,1),b = (2,2),2 a = b is an example of linearly dependent vectors. They lie on the same line. Linearly independent vectors require more than just a scaling, and therefore define two lines. The test for linear independence/dependence is applicable in any number of dimensions: {v1,v2,,vn}c1v1 + c2v2 + + cnvn = 0 where at least one c is non-zero means the vectors are linearly dependant.

a = (1,1),b = (2,2)
c1a + c2b = 0 = (0,0)
c1 + 2c2 = 0
c1 = 2c2
c1 = 5, arbitrary choice for c1
2c2 = 5
c2 = 5 2
c1 + 2c2 = 0
5 + 2(5 2 = 0)
5 + (5) = 0

Any non-zero constant can satisfy this equation c1 + 2c2 = 0, so we know a,b are linearly dependent.

c = (2,1),d = (3,2)
2c1 + 3c2 = 0
c1 + 2c2 = 0
2c1 = 3c2
c1 = 3c2 2
3c2 2 + 2c2 = 0
c2 2 = 0
c2 = 0
c1 + 2(0) = 0
c1 + 0 = 0
c1 = 0

0’s are the only values that satisfy these equations, so we know c = (2,1),d = (3,2) are linearly independent

Linear Algebra: Span and Basis

C = {a c1 + b c2|c1,c2 } defines all the linear combinations of a, b and is the ”span” of a and b. A Span will either define a single line if the vectors are linearly dependent or a vector space n if all vectors S = {v1,v2,,vn} are linearly independent. Span({a,b}) = 2a,b are linearly independent. If they are linearly independent, then the vectors a,b form a basis of 2, meaning the linear combinations of a,b describe EVERY vector in 2.