What is the Definition of a Basis in a Vector Space?

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SUMMARY

The dimension of a vector space, such as ℝ³, is defined as the number of vectors in a basis, which consists of vectors that both span the space and are linearly independent. In the case of ℝ³, the canonical basis is given by the vectors {[1, 0, 0], [0, 1, 0], [0, 0, 1]}, confirming that its dimension is 3. A basis must contain the same number of vectors as the dimension of the space, and any two sets of vectors that are both spanning and independent will have the same cardinality.

PREREQUISITES
  • Understanding of vector spaces and their properties
  • Familiarity with the concepts of linear independence and spanning sets
  • Knowledge of canonical basis vectors in ℝⁿ
  • Basic grasp of mathematical notation and terminology
NEXT STEPS
  • Study the properties of linear independence in vector spaces
  • Explore the concept of spanning sets and their significance
  • Learn about different types of bases in various vector spaces
  • Investigate the relationship between dimension and basis in higher-dimensional spaces
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Students of linear algebra, mathematicians, and educators looking to deepen their understanding of vector spaces and their dimensions.

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Homework Statement


Is it correct to say that the dimension of a given vector space is equal to the number of vectors of the canonic solution? For example:

Vector space |R3
Canonic solution = {[1 0 0],[0 1 0],[0 0 1]}

Therefore its dimension is 3.

Homework Equations





The Attempt at a Solution



I thought about it, and it made sense. I just want to make sure that I can solve my problems based on this assumption.

By the way, I'm not an english native speaker, therefore I don't know the word for the canonic solution.

Thanks in advance.
D.
 
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I'm not familiar with the term "canonical solution" for a vector space. But certainly for a finite dimensional space like ##\mathcal R^n##, the number ##n## of the standard basis vectors is the dimension of the space.

[Edit]I didn't see your comment in the second section about canonical solution. Anyway, yes, they form a basis.
 
A basis for a vector space is defined as set of vectors that both span the space and are independent. Essentially, one can show that a really "big" set will span the space and you if they are not independent, you can drop vectors and still span the space. On the other hand, a set containing a single (non-zero) vector must be independent so, it it doesn't span the space, you can add more vectors to the set and it will still be independent.

You can keep removing vectors from spanning sets and adding vector to independent sets until they "meet in the middle". Any two sets of vectors that both span the set and are independent- a basis- must contain the same number of vectors- the "dimension" of the space is defined as the number of vectors in a basis.
 

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