Linear Independence and Intersections of Sets

In summary, the conversation discusses proving that the intersection of two linearly independent sets of vectors in V is also linearly independent. The proof provided uses a proof by contradiction, showing that if the intersection is linearly dependent, then it leads to a contradiction. Additionally, it is mentioned that the proof can be shortened by using the fact that a non-empty subset of a linearly independent set is also linearly independent.
  • #1
TranscendArcu
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Homework Statement


Let E' and E'' be linearly independent sets of vectors in V. Show that [itex]E' \cap E''[/itex] is linearly independent.

The Attempt at a Solution

To show a contradiction, let [itex]E' \cap E''[/itex] be linearly dependent. Also let A be all of the vectors in [itex]E' \cap E''[/itex]. Thus, [itex]A \subseteq E'[/itex] and [itex]A \subseteq E''[/itex]. Because A is linearly dependent, there exists [itex]A_1,...,A_n[/itex] distinct vectors in A such that

[itex]a_1 A_1 + ... + a_n A_n = \vec0[/itex], where [itex]a_1,...,a_n[/itex] are not all zero. But if such a nontrivial linear combination of vectors in A exists, then E' must be linearly dependent since [itex]A \subseteq E'[/itex]. But this is contrary to our definition that E' is linearly independent. This is similarly contradictory for E''. Thus, it is shown that [itex]E' \cap E''[/itex] cannot be linearly dependent and must rather be linearly independent.

First of all, I don't know if this proof is correct (although it seems conceivable to me). Also, I didn't know how to prove the problem statement directly, so I had to do it by contradiction. If anyone could give me a hint as to how to do this directly, I would be grateful.
 
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  • #2
Your proof seems to do the job, though I recommend you consider the case when [itex]E'\cap E''[/itex] is empty separately first.

If you have some theorems at your disposal then you can shorten up your proof considerably by simply noting that a non-empty subset of a linearly independent set is itself linearly independent.
 

1. What is the definition of linear independence?

Linear independence refers to a set of vectors in a vector space that are not dependent on each other. This means that none of the vectors in the set can be written as a linear combination of the other vectors. In other words, no vector in the set can be created by adding or subtracting a multiple of another vector in the set.

2. How do you determine if a set of vectors is linearly independent?

To determine if a set of vectors is linearly independent, you can use the technique of Gaussian elimination. This involves creating an augmented matrix with the vectors as columns and performing row operations to reduce the matrix to row-echelon form. If there are no free variables in the resulting matrix, the vectors are linearly independent.

3. What is the relationship between linear independence and span?

A set of linearly independent vectors forms a basis for the space they span. This means that they can be used to create any vector in that space through linear combinations. Conversely, a set of vectors that span a space must be linearly independent in order to form a basis for that space.

4. Can a set of vectors be both linearly independent and dependent?

No, a set of vectors can only be either linearly independent or dependent. If a set of vectors is dependent, it means that at least one vector in the set can be written as a linear combination of the other vectors. This would violate the definition of linear independence, which requires that no vector can be written in terms of the others.

5. How do you find the intersection of two sets?

To find the intersection of two sets, you can list out the elements of each set and compare them. The intersection is the set of elements that are common to both sets. Alternatively, you can use set operations such as intersection or intersection by complement to find the intersection of two sets.

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