Necessary and Sufficient Conditions for a Basis in Finite-Dimensional Vector Spaces
Theorem1
Let be a -dimensional vector space. Suppose a subset has elements. A necessary and sufficient condition for to be a basis of is that or is linearly independent.
Explanation
Vector space, dimension, basis, span, independence - all these fundamental concepts of linear algebra appear here. For a set to be a basis of a vector space, it must be a linearly independent set that spans the vector space. Usually, both conditions must be shown separately, but for sets with a number of elements equal to the dimension, fulfilling one condition implies the fulfilment of the other.
Proof
Since one direction is trivial, proving that spans and that is linearly independent are practically equivalent to the necessary and sufficient condition.
This follows trivially from the definition of a basis. If is a basis of , then spans and is linearly independent.
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If spans , it is linearly independent
Assume spans . Now suppose is not linearly independent. Then some vector can be expressed as a linear combination of other vectors in .2 Then, excluding this from still spans the same space. But, a set with fewer elements than the dimension cannot span the vector space. This contradiction implies that the assumption of being not linearly independent is wrong. Therefore, is linearly independent.
If is linearly independent, it spans .
Suppose is linearly independent. Now suppose does not span . This means there exists some not included in . Then, adding this vector to still keeps linearly independent. However, a set with more elements than the dimension is linearly dependent. This contradiction implies that the assumption of not spanning is wrong. Therefore, spans .
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