FuadEhmedli

4. – The number of vectors in a basis of a vector space.
5. – Two vectors are orthogonal if their dot product is zero (they are perpendicular).
8. – A nonzero vector v such that
11. Combination – A sum of scalar multiples of vectors.
12. – A single number used to scale a vector or matrix.
13. – The dimension of the column space of a matrix; the number of linearly independent columns.
14. – A rectangular array of numbers arranged in rows and columns.

1. – The operation of flipping a matrix over its diagonal (rows become columns).
2. –A scalar λ such that
3. – The set of all possible linear combinations of a set of vectors.
4. – A scalar value that can be computed from a square matrix and determines invertibility.
6. Independence – A set of vectors is linearly independent if no vector is a linear combination of the others.
7. – An ordered list of numbers representing a point or direction in space.
9. Space – The set of all solutions to the homogeneous equation
10. – A set of linearly independent vectors that span a vector space.