The span of vectors are all vectors that can be written as linear combinations of other vectors

The span of vectors are all vectors that can be written as linear combinations of other vectors

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The span of vectors are all vectors that can be written as linear combinations of other vectors. The span of the set of vectors, is the collinear line of the vectors involved. If the vectors are collinear, then the span reduces to the collinear line which is the result of the linear combination of the two vectors before. A vector is linearly dependent if you can write a linear combination of that vector (It depends an independent vector that cannot be written as a linear combination of the other vector). The span of (v1, v2) = R^2 (in R2 dimensional real number space). The inverse of matrix A multiplied by the matrix A, will give you the identity matrix. The identity matrix multiplied/divided by any other matrix, will be the same matrix itself. Order matters when you are taking the inverse of one of the matrices present in an equation. If A = [3 , 2/-6 , 6], How to take the inverse of a matrix A: A^-1 = (1 / detA)(6 , -2/ 6 , 3] Det A = (3)(6) – (2)(-6) = 18 + 12 = 30. A ^-1 = (1/30) [6 , -2/6 , 3]
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The span of vectors are all vectors that can be written as linear combinations of other vectors

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