Final answer:
To find a basis for the subspace spanned by the given vectors, check if the vectors are linearly independent by forming a matrix and reducing it. The dimension of the subspace is the number of linearly independent vectors in the basis.
Step-by-step explanation:
To find a basis for the subspace spanned by the given vectors, we need to determine if the vectors are linearly independent. We can form a matrix using the given vectors as rows or columns, then row-reduce or column-reduce it to see if it has linearly independent rows or columns. If the matrix has full rank, then the vectors are linearly independent and form a basis for the subspace. If the matrix has a row or column of zeros, then the vectors are linearly dependent and we can remove the zero row or column to find a basis.
The dimension of the subspace is equal to the number of linearly independent vectors in the basis. So, if the vectors are linearly independent and form a basis, the dimension of the subspace is the number of given vectors. If the vectors are linearly dependent and we remove a zero row or column to find a basis, the dimension of the subspace is the number of nonzero vectors in the basis.