(18 intermediate revisions by 2 users not shown)
Line 1: Line 1:
'''Tricks for checking Linear Independence, Span and Basis'''
+
[[Bonus_point_projects_how_to_and_why|Bonus point project]] for [[MA265]].
 +
----
 +
'''Tricks for checking Linear Independence, Span and Basis'''  
  
<u>'''Linear Independence'''</u>
+
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.
  
If det(vectors)&nbsp;!= 0 ⇔ '''linearly independent'''<br>If end result of the rref(vectors) gives [0 0 0 1] -&gt; it is linearly independent because the system is '''inconsistent'''
+
<br> <u>'''Linear Independence'''</u>
  
If det(vectors) = 0 ⇔ linearly dependent<br>If end result of the rref(vectors) is in the order of [0 0 0 0] and provided the system is consistent, the vectors are '''linearly dependent.'''  
+
*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.'''
  
Tip: If #No of vectors &gt; Dimension ⇔ it is '''linearly dependent'''<br>
+
Tricks:  
  
<u>'''Span'''</u><br>Tip: If the question asks if a vector “belongs to span” of other vectors, then it means it is asking if it’s '''linearly dependent'''
+
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 Dimension &gt; #No of vectors -&gt; '''it CANNOT span'''
+
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 det(vectors)&nbsp;!= 0 ⇔ it spans<br>If end result of the rref(vectors) is in the order of [0 0 0 | 0] and provided the system is consistent, the vectors '''span.'''
+
<u>'''Span'''</u>
  
If det(vectors) = 0 ⇔ '''does not span'''<br>If end result of the rref(vectors) gives [0 0 0 | 1] -&gt; it does not span because the system is inconsistent
+
*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.'''
  
<u>'''Basis'''</u><br>
+
Tricks:
  
<br>If Dimension &gt; #No of vectors ⇔ cannot span ⇔ is not a basis
+
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'''
  
If #No of vectors &gt; Dimension -&gt; it has to be linearly dependent to span (check the tip)  
+
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.
 +
  
If #No of vectors = Dimension -&gt; it has to be linearly independent to span<br>
+
<u>'''Basis'''</u>  
  
[[Category:MA265Spring2011Momin]]
+
<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
 +
 
 +
----
 +
[[2010_Fall_MA_265_Momin|Back to MA265, Fall 2010, Prof. Momin]]
 +
 
 +
[[Category:math]]
 +
[[Category:linear algebra]]
 +
[[Category:MA265]]
 +
[[Category:MA265Fall2010Momin]]
 +
[[Category:bonus point project]]

Latest revision as of 07:21, 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