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[[Bonus_point_projects_how_to_and_why|Bonus point project]] for [[MA265]].
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'''Tricks for checking Linear Independence, Span and Basis'''  
 
'''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.
  
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<br> <u>'''Linear Independence'''</u>
  
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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.'''
  
<u>'''Linear Independence'''</u>
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Tricks:
  
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'''.
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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'''  
  
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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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
 
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Tip: If #No of vectors &gt; Dimension ⇔ it is '''linearly dependent'''<br>
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<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>
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----
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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

Alumni Liaison

Ph.D. 2007, working on developing cool imaging technologies for digital cameras, camera phones, and video surveillance cameras.

Buyue Zhang