About vector space and subspaces

In summary, a vector subspace is a subset of a vector space, and they both are vectors spaces with the same operations and over the same field. However, most people intuitively think of \mathbb{R}^2 as a subset of \mathbb{R}^3, which is incorrect.
  • #1
applechu
10
0
Hi:
I am a newbie to linear algebra; I have a problem about
vector space and subspaces. How to distinguish these two
subject. what I know from books is subspace is going through
zero, but I still can not figure out what is the difference between
vector space and subspaces, thanks.
 
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  • #2
applechu said:
Hi:
I am a newbie to linear algebra; I have a problem about
vector space and subspaces. How to distinguish these two
subject. what I know from books is subspace is going through
zero, but I still can not figure out what is the difference between
vector space and subspaces, thanks.



Simple: a vector subspace is a vector space in its own, but the particle "sub" indicates that it is a subset of a vector space that

contains it, and they both are vectors spaces wrt the very same operations and, of course, over the same field.

Thus, for example, the set [itex]\,\,\{t(1,0) \,;\,t\in\mathbb{R}\}\,[/itex] is a v. subspace of [itex]\,\mathbb{R}^2\,[/itex], but [itex]\,\mathbb{R}^2\,[/itex] is

not a subspace of [itex]\,\mathbb{R}^3[/itex] is the former as not a subset of the latter.

DonAntonio
 
  • #3
DonAntonio is correct, but I think his example is confusing.

[itex]\mathbb{R}^2[/itex] is not a subspace of [itex]\mathbb{R}^3[/itex] because the former are vectors with two entries, and the latter are vectors with three entries. They are just different animals altogether, and so cannot be subsets of one or another.

However, in practice we tend to think of [itex]\mathbb{R}^2[/itex] as a subset of [itex]\mathbb{R}^3[/itex] with the tacit understanding that every vector in [itex]\mathbb{R}^2[/itex] gets a zero appended to it.

So [itex][4,2]\in\mathbb{R^2}[/itex] becomes [itex][4,2,0]\in\mathbb{R^3}[/itex]

With this understanding, [itex]\mathbb{R}^2[/itex] is a subspace of [itex]\mathbb{R}^3[/itex]

I add this not to nit pick or be confusing. I add this because this is how most people see [itex]\mathbb{R}^2[/itex] and it's important to make explicit why it is wrong to do so (like in DonAntonio's post) and what we implicitly do in our intuition.
 
Last edited:
  • #4
Thanks a lot
 
  • #5


Hello,

Vector space and subspaces are both fundamental concepts in linear algebra. A vector space is a set of vectors that can be added together and multiplied by scalars to produce new vectors within the same set. This set must also follow certain properties, such as closure under addition and scalar multiplication, and must contain a zero vector.

On the other hand, a subspace is a subset of a vector space that also satisfies the properties of a vector space. This means that a subspace is also closed under addition and scalar multiplication and contains a zero vector. However, a subspace is not necessarily the entire vector space itself.

To distinguish between the two, you can think of a vector space as a larger set that contains all possible combinations of vectors, while a subspace is a smaller set within that vector space that still follows the rules of a vector space. Another way to think about it is that a vector space is the entire universe, while a subspace is a galaxy within that universe.

I hope this helps clarify the difference between vector space and subspaces. Keep studying and practicing, and you will become more comfortable with these concepts. Good luck!
 

1. What is a vector space?

A vector space is a mathematical structure that consists of a set of vectors and two operations, addition and scalar multiplication, that satisfy a set of axioms. These axioms include closure under addition and scalar multiplication, associativity, commutativity, and the existence of an identity and inverse element for addition.

2. What are the properties of a vector space?

The properties of a vector space include closure under addition and scalar multiplication, associativity, commutativity, the existence of an identity and inverse element for addition, and the distributivity of scalar multiplication over vector addition.

3. What is a subspace?

A subspace is a subset of a vector space that also satisfies the axioms of a vector space. This means that a subspace is closed under addition and scalar multiplication, and it contains an identity and inverse element for addition. Additionally, a subspace must also contain the zero vector and be closed under scalar multiplication.

4. How can you determine if a set is a subspace?

To determine if a set is a subspace, you must check if it satisfies the axioms of a vector space. This includes checking if it is closed under addition and scalar multiplication, contains an identity and inverse element for addition, and contains the zero vector. If all of these properties hold, then the set is a subspace.

5. What is the dimension of a vector space?

The dimension of a vector space is the number of vectors in a basis for that space. A basis is a set of linearly independent vectors that can be used to represent any vector in the space. The dimension of a vector space is often denoted by the symbol "n" and is used to describe the number of components needed to represent a vector in that space.

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