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<br> <u>'''Linear Independence'''</u>  
 
<br> <u>'''Linear Independence'''</u>  
  
*If end result of the rref(vectors) gives an identity matrix, it is '''linearly independent'''<br>
+
*If end result of the rref(vectors) gives an identity matrix, it is '''linearly independent'''<br>  
 
*If end result of the rref(vectors) gives you a parameter in the matrix, the vectors are '''linearly dependent.'''
 
*If end result of the rref(vectors) gives you a parameter in the matrix, the vectors are '''linearly dependent.'''
  
 
Tricks:  
 
Tricks:  
If #No of vectors &gt; Dimension ⇔ it is '''linearly dependent'''
 
If det(vectors)&nbsp;!= 0 ⇔ '''linearly independent'''
 
If det(vectors) = 0 ⇔ '''linearly dependent'''
 
  
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
+
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'''
 +
 
 +
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 end result of the rref(vectors) gives you a matrix with all rows having leading 1's, '''it spans'''.&nbsp
+
*If end result of the rref(vectors) gives you a matrix with all rows having leading 1's, '''it spans'''.&amp;nbsp  
 
*If end result of the rref(vectors) gives you a matrix with not all rows having a leading 1, it '''does not span.'''
 
*If end result of the rref(vectors) gives you a matrix with not all rows having a leading 1, it '''does not span.'''
  
Tricks:
+
Tricks:  
If Dimension &gt; #No of vectors -&gt; '''it CANNOT span'''
+
If det(vectors)&nbsp;!= 0 ⇔ '''it spans'''
+
If det(vectors) = 0 ⇔ '''does not span'''
+
  
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><br>
+
If Dimension &gt; #No of vectors -&gt; '''it CANNOT span''' <br>If det(vectors)&nbsp;!= 0 ⇔ '''it spans'''
  
<u>'''Basis'''</u><br>
+
If det(vectors) = 0 ⇔ '''does not span'''  
  
<br>If Dimension &gt; #No of vectors ⇔ cannot span ⇔ is not a basis
+
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>
 +
 
  
If #No of vectors &gt; Dimension -&gt; it is not a basis.  
+
<u>'''Basis'''</u><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>
  
 
[[Category:MA265Spring2011Momin]]
 
[[Category:MA265Spring2011Momin]]
 
<br>
 

Revision as of 10:43, 1 May 2011

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.&nbsp
  • 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
 

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


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