Linear Independence of Vectors Spanning $\mathbb{R}^n$

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SUMMARY

If a set of vectors {x1, x2, ..., xn} spans the vector space $\mathbb{R}^n$, then these vectors are linearly independent. This conclusion arises from the fact that fewer than n vectors cannot span $\mathbb{R}^n$. Therefore, a set of n vectors that spans $\mathbb{R}^n$ forms a basis for this space, confirming their linear independence.

PREREQUISITES
  • Understanding of vector spaces, specifically $\mathbb{R}^n$
  • Knowledge of linear independence and spanning sets
  • Familiarity with the concept of basis in linear algebra
  • Basic proficiency in mathematical notation and terminology
NEXT STEPS
  • Study the properties of vector spaces in linear algebra
  • Learn about the criteria for linear independence of vectors
  • Explore the concept of bases and dimension in vector spaces
  • Investigate applications of linear independence in solving linear equations
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Students of linear algebra, mathematicians, and educators seeking to deepen their understanding of vector spaces and linear independence.

Dustinsfl
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If x1, x2,..., xn span \mathbb{R}^n, then they are linearly independent.

This is true since n-1 vectors can't span R^n.

How can this be written in a more meaningful way?
 
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\mathbb{R}^n is an n-dimensional vector space. {x1,x2,...,xn} is a spanning set of \mathbb{R}^n of length n. This makes {x1,x2,...,xn} a basis of \mathbb{R}^n, which means it must be linearly independent.
 

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