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'''Tricks for checking Linear Independence, Span and Basis'''
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[[Bonus_point_projects_how_to_and_why|Bonus point project]] for [[MA265]].
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----
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'''Tricks for checking Linear Independence, Span and Basis'''  
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Note: For this article, I am assuming number of vectors is equal to the dimension of the vector space for calculating the determinant. If it is not, you need to do rref.
  
 
<br> <u>'''Linear Independence'''</u>  
 
<br> <u>'''Linear Independence'''</u>  
  
If det(vectors)&nbsp;!= 0 ⇔ '''linearly independent'''<br> If end result of the rref(vectors) gives you a matrix with all rows having leading 1's it is '''linearly independent'''. <math>$M = \left( \begin{smallmatrix} a&b\\ c&d \end{smallmatrix} \right)$</math>
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*If end result of the rref(vectors) gives an identity matrix, it is '''linearly independent'''<br>  
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*If end result of the rref(vectors) gives you a parameter in the matrix, the vectors are '''linearly dependent.'''
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Tricks:
  
If det(vectors) = 0 ⇔ '''linearly dependent'''<br>If end result of the rref(vectors) gives you a parameter in the equation, the vectors are '''linearly dependent.'''  
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If #No of vectors &gt; Dimension ⇔ it is '''linearly dependent''' <br>If det(vectors)&nbsp;!= 0 ⇔ '''linearly independent''' <br> If det(vectors) = 0 ⇔ '''linearly dependent'''  
  
Tip: If #No of vectors &gt; Dimension ⇔ it is '''linearly dependent'''<br>  
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Example: <math>rref(\left( \begin{smallmatrix} 1&2&3\\ 2&3&4 \end{smallmatrix} \right)) = \left( \begin{smallmatrix} 1&0&-1\\ 0&1&2 \end{smallmatrix} \right)</math> is '''linearly dependent''' in R<sup>2</sup> because the last column [-1 2]<sup>T</sup> i.e z is a parameter as there can be no leading 1 for that column. You can express x = z and y = -2z
  
 
<u>'''Span'''</u>  
 
<u>'''Span'''</u>  
  
If Dimension &gt; #No of vectors -&gt; '''it CANNOT span'''  
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*If end result of the rref(vectors) gives you a matrix with all rows having leading 1's, '''it spans'''.
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*If end result of the rref(vectors) gives you a matrix with not all rows having a leading 1, it '''does not span.'''
  
If det(vectors)&nbsp;!= 0 ⇔ it spans<br>If end result of the rref(vectors) gives you a matrix with all rows having leading 1's, '''it spans'''.
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Tricks:
  
If det(vectors) = 0 ⇔ '''does not span'''<br>If end result of the rref(vectors) gives you a matrix with not all rows having a leading 1, it '''does not span.'''  
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If Dimension &gt; #No of vectors -&gt; '''it CANNOT span''' <br>If det(vectors)&nbsp;!= 0 ⇔ '''it spans'''<br>If det(vectors) = 0 ⇔ '''does not span'''  
  
<u>'''Basis'''</u><br>  
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For example: <math>rref(\left( \begin{smallmatrix} 1&2&3\\ 2&3&4 \end{smallmatrix} \right)) = \left( \begin{smallmatrix} 1&0&-1\\ 0&1&2 \end{smallmatrix} \right)</math> spans R<sup>2</sup> because both rows have leading 1's.
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<br>If Dimension &gt; #No of vectors ⇔ cannot span ⇔ is not a basis
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<u>'''Basis'''</u>  
  
If #No of vectors &gt; Dimension -&gt; it has to be linearly dependent to span (check the tip)
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<br>If Dimension &gt; #No of vectors ⇔ cannot span ⇔ is not a basis<br>If #No of vectors &gt; Dimension -&gt; it is not a basis.<br>If #No of vectors = Dimension -&gt; it has to be linearly independent to span  
  
If #No of vectors = Dimension -&gt; it has to be linearly independent to span<br> <span class="texhtml">''I''''n''''s''''e''''r''''t''''f''''o''''r''''m''''u''''l''''a''''h''''e''''r''''e''</span>
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[[2010_Fall_MA_265_Momin|Back to MA265, Fall 2010, Prof. Momin]]
  
[[Category:MA265Spring2011Momin]]
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[[Category:math]]
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[[Category:linear algebra]]
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[[Category:MA265]]
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[[Category:MA265Fall2010Momin]]
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[[Category:bonus point project]]

Latest revision as of 06:21, 3 July 2012

Bonus point project for MA265.


Tricks for checking Linear Independence, Span and Basis

Note: For this article, I am assuming number of vectors is equal to the dimension of the vector space for calculating the determinant. If it is not, you need to do rref.


Linear Independence

  • If end result of the rref(vectors) gives an identity matrix, it is linearly independent
  • If end result of the rref(vectors) gives you a parameter in the matrix, the vectors are linearly dependent.

Tricks:

If #No of vectors > Dimension ⇔ it is linearly dependent
If det(vectors) != 0 ⇔ linearly independent
If det(vectors) = 0 ⇔ linearly dependent

Example: $ rref(\left( \begin{smallmatrix} 1&2&3\\ 2&3&4 \end{smallmatrix} \right)) = \left( \begin{smallmatrix} 1&0&-1\\ 0&1&2 \end{smallmatrix} \right) $ is linearly dependent in R2 because the last column [-1 2]T i.e z is a parameter as there can be no leading 1 for that column. You can express x = z and y = -2z

Span

  • If end result of the rref(vectors) gives you a matrix with all rows having leading 1's, it spans.
  • If end result of the rref(vectors) gives you a matrix with not all rows having a leading 1, it does not span.

Tricks:

If Dimension > #No of vectors -> it CANNOT span
If det(vectors) != 0 ⇔ it spans
If det(vectors) = 0 ⇔ does not span

For example: $ rref(\left( \begin{smallmatrix} 1&2&3\\ 2&3&4 \end{smallmatrix} \right)) = \left( \begin{smallmatrix} 1&0&-1\\ 0&1&2 \end{smallmatrix} \right) $ spans R2 because both rows have leading 1's.

Basis


If Dimension > #No of vectors ⇔ cannot span ⇔ is not a basis
If #No of vectors > Dimension -> it is not a basis.
If #No of vectors = Dimension -> it has to be linearly independent to span


Back to MA265, Fall 2010, Prof. Momin

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