Understanding Span, Basis, and Dimension: A Guide to Linear Algebra Concepts

In summary: How do you find a basis for the range of the given map?This is also answered in every linear algebra text. You can find the range, then the basis.
  • #1
jlucas134
22
0
I need some help to understand the concepts of span, basis, and dimension.

1-How do you determine if a set of vectors [in matrix form] span a region?
-Do you set the given matrix set to arbitary numbers and see if
there is a unique, infinite, or no solution?
ie, set a 4X4 matrix = to [a b c d] and determine the type of solution?

2. How do you find a basis for the kernel of the linear map L : R^4 goes to
R4 corresponding to multiplication of a given matrix?
-Do you do the same thing as above, but set the given matrix equal to
zero to find the kernal and after you find the kernal, do you find the
basis?

3. How do you find a basis for the range of this same map?
Do you find the range, then the basis?

I think if I understand these concepts, I can do the homework. Any assistance would be appreciated.

Thanks in advance!
 
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  • #2
jlucas134 said:
I need some help to understand the concepts of span, basis, and dimension.

1-How do you determine if a set of vectors [in matrix form] span a region?
-Do you set the given matrix set to arbitary numbers and see if
there is a unique, infinite, or no solution?
ie, set a 4X4 matrix = to [a b c d] and determine the type of solution?

Yes, you do. Note that the solution (i.e. representation) doesn't have to be unique if you're talking about a spanning set. Existance is important.

jlucas134 said:
2. How do you find a basis for the kernel of the linear map L : R^4 goes to
R4 corresponding to multiplication of a given matrix?
-Do you do the same thing as above, but set the given matrix equal to
zero to find the kernal and after you find the kernal, do you find the
basis?

Of course, you first have to find the kernel, i.e. you have to know what a set looks like in order to do anything with it.
 
  • #3
these questions are answered in every linear algebra text. indeed this is about all there is to basic concrete linear algebra. do you have a book? e.g. shifrin and adams?
 
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  • #4
use gaussian elimination.

given a set of vectors in R^n, put them in as either rows or columns in a matrix and row reduce. they did span iff the number of non zeroes rows remaining is n, iff the number of "pivot" columns is n.

to find a basis for the image of a matrix, reduce and take the pivot columns as your basis. use the usual solution procedure on the reduced matrix (back substitution) to write down a basis of the null space or kernel.

to see if a given vector lies in the span of the columns of a matrix, add it as another column, reduce and see if this new last column is a pivot, (if so it is not in the span).
 
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1. What is the span of a set of vectors?

The span of a set of vectors is the set of all possible linear combinations of those vectors. In other words, it is the set of all possible values that can be created by multiplying each vector by a scalar and adding them together.

2. How do you determine the basis of a vector space?

A basis of a vector space is a set of linearly independent vectors that span the entire space. To determine the basis, you can use the reduced row echelon form of the matrix formed by the vectors, and the non-zero rows will form the basis.

3. What is the difference between a basis and a spanning set?

A basis is a specific set of vectors that spans the entire vector space and is also linearly independent. A spanning set, on the other hand, can be any set of vectors that spans the space, but may not necessarily be linearly independent.

4. How does the dimension of a vector space relate to its basis?

The dimension of a vector space is equal to the number of vectors in its basis. This means that any set of linearly independent vectors that spans the space will have the same number of vectors as the dimension of the space.

5. Can a vector space have more than one basis?

Yes, a vector space can have multiple bases. In fact, any set of linearly independent vectors that span the space can be considered a basis. However, all bases for a given vector space will have the same number of vectors, which is equal to the dimension of the space.

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