Rank, dimension, basis

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2
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I think I am a little bit confused with the terms in the title, so I hope you can correct me if I got it wrong...



$$
leftlbrace beginbmatrix x_1\0\0 endbmatrix : x_1 in mathbbR rightrbrace
$$
is a vector space. So far so good.



The dimension of the vector space is the number of vectors in the basis.



In class, I wrote down that a basis is



$$
B=(beginbmatrix1\0\0endbmatrix, beginbmatrix0\0\0endbmatrix, beginbmatrix0\0\0endbmatrix)
$$



But this does not seem logical to me now, as it should be the smallest number of independent vectors that span the vector space. And shouldn’t that be just
$
(beginbmatrix1\0\0endbmatrix)
$



So this is the place where I'm not sure: what is the dimension of the vector space? It is a line in $mathbb R^3$, and it would seem logical that the dimension of a line is $1$.



And what would the rank be? I totally confused myself.



Or is it like the dimension is $3$ and the rank is $1$. so the above solution for the basis would be correct...



Many thanks for your help










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  • A basis must be linearly independent, so it can't contain the zero vector. Your $B$ does (twice).
    – Bungo
    4 hours ago










  • Yes sorry i will add it
    – Lillys
    4 hours ago










  • "it should be the smallest number...shouldn't that just be $left(left[beginsmallmatrix1\0\0endsmallmatrixright]right)$" Yes, it should just be that. As mentioned, the zero vectors should not have been included. The dimension of the subspace spanned by your one vector is indeed one, despite the fact that the parent space is three-dimensional. When talking about dimension or percentage or whatever, you have to keep in mind "dimension of what", here we are talking about dimension of the subspace, not of the parent space.
    – JMoravitz
    4 hours ago















up vote
2
down vote

favorite












I think I am a little bit confused with the terms in the title, so I hope you can correct me if I got it wrong...



$$
leftlbrace beginbmatrix x_1\0\0 endbmatrix : x_1 in mathbbR rightrbrace
$$
is a vector space. So far so good.



The dimension of the vector space is the number of vectors in the basis.



In class, I wrote down that a basis is



$$
B=(beginbmatrix1\0\0endbmatrix, beginbmatrix0\0\0endbmatrix, beginbmatrix0\0\0endbmatrix)
$$



But this does not seem logical to me now, as it should be the smallest number of independent vectors that span the vector space. And shouldn’t that be just
$
(beginbmatrix1\0\0endbmatrix)
$



So this is the place where I'm not sure: what is the dimension of the vector space? It is a line in $mathbb R^3$, and it would seem logical that the dimension of a line is $1$.



And what would the rank be? I totally confused myself.



Or is it like the dimension is $3$ and the rank is $1$. so the above solution for the basis would be correct...



Many thanks for your help










share|cite|improve this question























  • A basis must be linearly independent, so it can't contain the zero vector. Your $B$ does (twice).
    – Bungo
    4 hours ago










  • Yes sorry i will add it
    – Lillys
    4 hours ago










  • "it should be the smallest number...shouldn't that just be $left(left[beginsmallmatrix1\0\0endsmallmatrixright]right)$" Yes, it should just be that. As mentioned, the zero vectors should not have been included. The dimension of the subspace spanned by your one vector is indeed one, despite the fact that the parent space is three-dimensional. When talking about dimension or percentage or whatever, you have to keep in mind "dimension of what", here we are talking about dimension of the subspace, not of the parent space.
    – JMoravitz
    4 hours ago













up vote
2
down vote

favorite









up vote
2
down vote

favorite











I think I am a little bit confused with the terms in the title, so I hope you can correct me if I got it wrong...



$$
leftlbrace beginbmatrix x_1\0\0 endbmatrix : x_1 in mathbbR rightrbrace
$$
is a vector space. So far so good.



The dimension of the vector space is the number of vectors in the basis.



In class, I wrote down that a basis is



$$
B=(beginbmatrix1\0\0endbmatrix, beginbmatrix0\0\0endbmatrix, beginbmatrix0\0\0endbmatrix)
$$



But this does not seem logical to me now, as it should be the smallest number of independent vectors that span the vector space. And shouldn’t that be just
$
(beginbmatrix1\0\0endbmatrix)
$



So this is the place where I'm not sure: what is the dimension of the vector space? It is a line in $mathbb R^3$, and it would seem logical that the dimension of a line is $1$.



And what would the rank be? I totally confused myself.



Or is it like the dimension is $3$ and the rank is $1$. so the above solution for the basis would be correct...



Many thanks for your help










share|cite|improve this question















I think I am a little bit confused with the terms in the title, so I hope you can correct me if I got it wrong...



$$
leftlbrace beginbmatrix x_1\0\0 endbmatrix : x_1 in mathbbR rightrbrace
$$
is a vector space. So far so good.



The dimension of the vector space is the number of vectors in the basis.



In class, I wrote down that a basis is



$$
B=(beginbmatrix1\0\0endbmatrix, beginbmatrix0\0\0endbmatrix, beginbmatrix0\0\0endbmatrix)
$$



But this does not seem logical to me now, as it should be the smallest number of independent vectors that span the vector space. And shouldn’t that be just
$
(beginbmatrix1\0\0endbmatrix)
$



So this is the place where I'm not sure: what is the dimension of the vector space? It is a line in $mathbb R^3$, and it would seem logical that the dimension of a line is $1$.



And what would the rank be? I totally confused myself.



Or is it like the dimension is $3$ and the rank is $1$. so the above solution for the basis would be correct...



Many thanks for your help







linear-algebra






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edited 3 hours ago









user587192

7187




7187










asked 4 hours ago









Lillys

236




236











  • A basis must be linearly independent, so it can't contain the zero vector. Your $B$ does (twice).
    – Bungo
    4 hours ago










  • Yes sorry i will add it
    – Lillys
    4 hours ago










  • "it should be the smallest number...shouldn't that just be $left(left[beginsmallmatrix1\0\0endsmallmatrixright]right)$" Yes, it should just be that. As mentioned, the zero vectors should not have been included. The dimension of the subspace spanned by your one vector is indeed one, despite the fact that the parent space is three-dimensional. When talking about dimension or percentage or whatever, you have to keep in mind "dimension of what", here we are talking about dimension of the subspace, not of the parent space.
    – JMoravitz
    4 hours ago

















  • A basis must be linearly independent, so it can't contain the zero vector. Your $B$ does (twice).
    – Bungo
    4 hours ago










  • Yes sorry i will add it
    – Lillys
    4 hours ago










  • "it should be the smallest number...shouldn't that just be $left(left[beginsmallmatrix1\0\0endsmallmatrixright]right)$" Yes, it should just be that. As mentioned, the zero vectors should not have been included. The dimension of the subspace spanned by your one vector is indeed one, despite the fact that the parent space is three-dimensional. When talking about dimension or percentage or whatever, you have to keep in mind "dimension of what", here we are talking about dimension of the subspace, not of the parent space.
    – JMoravitz
    4 hours ago
















A basis must be linearly independent, so it can't contain the zero vector. Your $B$ does (twice).
– Bungo
4 hours ago




A basis must be linearly independent, so it can't contain the zero vector. Your $B$ does (twice).
– Bungo
4 hours ago












Yes sorry i will add it
– Lillys
4 hours ago




Yes sorry i will add it
– Lillys
4 hours ago












"it should be the smallest number...shouldn't that just be $left(left[beginsmallmatrix1\0\0endsmallmatrixright]right)$" Yes, it should just be that. As mentioned, the zero vectors should not have been included. The dimension of the subspace spanned by your one vector is indeed one, despite the fact that the parent space is three-dimensional. When talking about dimension or percentage or whatever, you have to keep in mind "dimension of what", here we are talking about dimension of the subspace, not of the parent space.
– JMoravitz
4 hours ago





"it should be the smallest number...shouldn't that just be $left(left[beginsmallmatrix1\0\0endsmallmatrixright]right)$" Yes, it should just be that. As mentioned, the zero vectors should not have been included. The dimension of the subspace spanned by your one vector is indeed one, despite the fact that the parent space is three-dimensional. When talking about dimension or percentage or whatever, you have to keep in mind "dimension of what", here we are talking about dimension of the subspace, not of the parent space.
– JMoravitz
4 hours ago











3 Answers
3






active

oldest

votes

















up vote
3
down vote













The differences:



A basis is a subset of the vector space with special properties: it has to span the vector space, and it has to be linearly independent.



The initial set of three elements you gave fails to be linearly independent, but it does span the space you specified. In that case you just call it a generating set.



The dimension of a finite dimensional vector space is a cardinal number: it is the cardinality of a basis (any basis!)



The rank of a linear transformation is the dimension of its image. That is, if you have a linear transformation $f:Vto W$, the rank of $f$ is $dim(f(V))$. This is the most common usage of the word "rank" in regular linear algebra. I can also imagine some authors unfortunately using "rank" as a synonym for dimension, but hopefully that is not very common.



So the three things refer to each other (dimension is the size of a basis, rank is the dimension of the image) but you can see they are different things.




So there where im not sure bc what is the dimension of the vectorspace, it is a line in R^3, and it would seem logical that the dimension of a line is 1.




The vector space you mentioned does indeed have dimension $1$. It is a subspace of a vector space of dimension $3$ ($mathbb R^3$), but it does not have dimension $3$ itself. Its bases only have $1$ element, but every basis of $mathbb R^3$ has three elements. The only relationship between the dimension of a vector space $V$ and a subspace $Wsubseteq V$ is that $dim(W)leq dim(V)$, which your example demonstrates.






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  • I also have a problem where i was asked to determine the rank auf a set of vectors. Am i correct to say it is the number of linear independent vectors? Many thanks for your answer
    – Lillys
    3 hours ago






  • 1




    @Lillys I have never heard of that, but I would interpret it as the dimension of the span of those vectors, as you say.
    – rschwieb
    3 hours ago


















up vote
2
down vote













You are correct in finding just one vector in your basis.



The vectors in a basis should be linearly independent and $0$ vectors are not allowed in your basis for the same reason.



Usually the rank is defined if you have a linear transformation or a matrix.



I did not see a matrix or a linear transformation in your statement to find the rank of it.






share|cite|improve this answer



























    up vote
    2
    down vote













    You don't want to think of
    $$beginbmatrix x_1\0\0 endbmatrix$$
    being a vector space. A vector space is a set of vectors (that satisfy certain conditions), so you want
    $$leftlbrace beginbmatrix x_1\0\0 endbmatrix : x_1 in mathbbR rightrbrace$$



    Second, a basis is a collection of linearly independent vectors that span the vector space. So you should not have any zero vectors in your basis.



    Then your basis for this vector space will contain a single vector, and so is one-dimensional.



    As for rank, you don't typically talk about the rank of a vector space; the rank of a matrix is the dimension of the column space of that matrix.






    share|cite|improve this answer




















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      3 Answers
      3






      active

      oldest

      votes








      3 Answers
      3






      active

      oldest

      votes









      active

      oldest

      votes






      active

      oldest

      votes








      up vote
      3
      down vote













      The differences:



      A basis is a subset of the vector space with special properties: it has to span the vector space, and it has to be linearly independent.



      The initial set of three elements you gave fails to be linearly independent, but it does span the space you specified. In that case you just call it a generating set.



      The dimension of a finite dimensional vector space is a cardinal number: it is the cardinality of a basis (any basis!)



      The rank of a linear transformation is the dimension of its image. That is, if you have a linear transformation $f:Vto W$, the rank of $f$ is $dim(f(V))$. This is the most common usage of the word "rank" in regular linear algebra. I can also imagine some authors unfortunately using "rank" as a synonym for dimension, but hopefully that is not very common.



      So the three things refer to each other (dimension is the size of a basis, rank is the dimension of the image) but you can see they are different things.




      So there where im not sure bc what is the dimension of the vectorspace, it is a line in R^3, and it would seem logical that the dimension of a line is 1.




      The vector space you mentioned does indeed have dimension $1$. It is a subspace of a vector space of dimension $3$ ($mathbb R^3$), but it does not have dimension $3$ itself. Its bases only have $1$ element, but every basis of $mathbb R^3$ has three elements. The only relationship between the dimension of a vector space $V$ and a subspace $Wsubseteq V$ is that $dim(W)leq dim(V)$, which your example demonstrates.






      share|cite|improve this answer






















      • I also have a problem where i was asked to determine the rank auf a set of vectors. Am i correct to say it is the number of linear independent vectors? Many thanks for your answer
        – Lillys
        3 hours ago






      • 1




        @Lillys I have never heard of that, but I would interpret it as the dimension of the span of those vectors, as you say.
        – rschwieb
        3 hours ago















      up vote
      3
      down vote













      The differences:



      A basis is a subset of the vector space with special properties: it has to span the vector space, and it has to be linearly independent.



      The initial set of three elements you gave fails to be linearly independent, but it does span the space you specified. In that case you just call it a generating set.



      The dimension of a finite dimensional vector space is a cardinal number: it is the cardinality of a basis (any basis!)



      The rank of a linear transformation is the dimension of its image. That is, if you have a linear transformation $f:Vto W$, the rank of $f$ is $dim(f(V))$. This is the most common usage of the word "rank" in regular linear algebra. I can also imagine some authors unfortunately using "rank" as a synonym for dimension, but hopefully that is not very common.



      So the three things refer to each other (dimension is the size of a basis, rank is the dimension of the image) but you can see they are different things.




      So there where im not sure bc what is the dimension of the vectorspace, it is a line in R^3, and it would seem logical that the dimension of a line is 1.




      The vector space you mentioned does indeed have dimension $1$. It is a subspace of a vector space of dimension $3$ ($mathbb R^3$), but it does not have dimension $3$ itself. Its bases only have $1$ element, but every basis of $mathbb R^3$ has three elements. The only relationship between the dimension of a vector space $V$ and a subspace $Wsubseteq V$ is that $dim(W)leq dim(V)$, which your example demonstrates.






      share|cite|improve this answer






















      • I also have a problem where i was asked to determine the rank auf a set of vectors. Am i correct to say it is the number of linear independent vectors? Many thanks for your answer
        – Lillys
        3 hours ago






      • 1




        @Lillys I have never heard of that, but I would interpret it as the dimension of the span of those vectors, as you say.
        – rschwieb
        3 hours ago













      up vote
      3
      down vote










      up vote
      3
      down vote









      The differences:



      A basis is a subset of the vector space with special properties: it has to span the vector space, and it has to be linearly independent.



      The initial set of three elements you gave fails to be linearly independent, but it does span the space you specified. In that case you just call it a generating set.



      The dimension of a finite dimensional vector space is a cardinal number: it is the cardinality of a basis (any basis!)



      The rank of a linear transformation is the dimension of its image. That is, if you have a linear transformation $f:Vto W$, the rank of $f$ is $dim(f(V))$. This is the most common usage of the word "rank" in regular linear algebra. I can also imagine some authors unfortunately using "rank" as a synonym for dimension, but hopefully that is not very common.



      So the three things refer to each other (dimension is the size of a basis, rank is the dimension of the image) but you can see they are different things.




      So there where im not sure bc what is the dimension of the vectorspace, it is a line in R^3, and it would seem logical that the dimension of a line is 1.




      The vector space you mentioned does indeed have dimension $1$. It is a subspace of a vector space of dimension $3$ ($mathbb R^3$), but it does not have dimension $3$ itself. Its bases only have $1$ element, but every basis of $mathbb R^3$ has three elements. The only relationship between the dimension of a vector space $V$ and a subspace $Wsubseteq V$ is that $dim(W)leq dim(V)$, which your example demonstrates.






      share|cite|improve this answer














      The differences:



      A basis is a subset of the vector space with special properties: it has to span the vector space, and it has to be linearly independent.



      The initial set of three elements you gave fails to be linearly independent, but it does span the space you specified. In that case you just call it a generating set.



      The dimension of a finite dimensional vector space is a cardinal number: it is the cardinality of a basis (any basis!)



      The rank of a linear transformation is the dimension of its image. That is, if you have a linear transformation $f:Vto W$, the rank of $f$ is $dim(f(V))$. This is the most common usage of the word "rank" in regular linear algebra. I can also imagine some authors unfortunately using "rank" as a synonym for dimension, but hopefully that is not very common.



      So the three things refer to each other (dimension is the size of a basis, rank is the dimension of the image) but you can see they are different things.




      So there where im not sure bc what is the dimension of the vectorspace, it is a line in R^3, and it would seem logical that the dimension of a line is 1.




      The vector space you mentioned does indeed have dimension $1$. It is a subspace of a vector space of dimension $3$ ($mathbb R^3$), but it does not have dimension $3$ itself. Its bases only have $1$ element, but every basis of $mathbb R^3$ has three elements. The only relationship between the dimension of a vector space $V$ and a subspace $Wsubseteq V$ is that $dim(W)leq dim(V)$, which your example demonstrates.







      share|cite|improve this answer














      share|cite|improve this answer



      share|cite|improve this answer








      edited 3 hours ago

























      answered 4 hours ago









      rschwieb

      103k1299237




      103k1299237











      • I also have a problem where i was asked to determine the rank auf a set of vectors. Am i correct to say it is the number of linear independent vectors? Many thanks for your answer
        – Lillys
        3 hours ago






      • 1




        @Lillys I have never heard of that, but I would interpret it as the dimension of the span of those vectors, as you say.
        – rschwieb
        3 hours ago

















      • I also have a problem where i was asked to determine the rank auf a set of vectors. Am i correct to say it is the number of linear independent vectors? Many thanks for your answer
        – Lillys
        3 hours ago






      • 1




        @Lillys I have never heard of that, but I would interpret it as the dimension of the span of those vectors, as you say.
        – rschwieb
        3 hours ago
















      I also have a problem where i was asked to determine the rank auf a set of vectors. Am i correct to say it is the number of linear independent vectors? Many thanks for your answer
      – Lillys
      3 hours ago




      I also have a problem where i was asked to determine the rank auf a set of vectors. Am i correct to say it is the number of linear independent vectors? Many thanks for your answer
      – Lillys
      3 hours ago




      1




      1




      @Lillys I have never heard of that, but I would interpret it as the dimension of the span of those vectors, as you say.
      – rschwieb
      3 hours ago





      @Lillys I have never heard of that, but I would interpret it as the dimension of the span of those vectors, as you say.
      – rschwieb
      3 hours ago











      up vote
      2
      down vote













      You are correct in finding just one vector in your basis.



      The vectors in a basis should be linearly independent and $0$ vectors are not allowed in your basis for the same reason.



      Usually the rank is defined if you have a linear transformation or a matrix.



      I did not see a matrix or a linear transformation in your statement to find the rank of it.






      share|cite|improve this answer
























        up vote
        2
        down vote













        You are correct in finding just one vector in your basis.



        The vectors in a basis should be linearly independent and $0$ vectors are not allowed in your basis for the same reason.



        Usually the rank is defined if you have a linear transformation or a matrix.



        I did not see a matrix or a linear transformation in your statement to find the rank of it.






        share|cite|improve this answer






















          up vote
          2
          down vote










          up vote
          2
          down vote









          You are correct in finding just one vector in your basis.



          The vectors in a basis should be linearly independent and $0$ vectors are not allowed in your basis for the same reason.



          Usually the rank is defined if you have a linear transformation or a matrix.



          I did not see a matrix or a linear transformation in your statement to find the rank of it.






          share|cite|improve this answer












          You are correct in finding just one vector in your basis.



          The vectors in a basis should be linearly independent and $0$ vectors are not allowed in your basis for the same reason.



          Usually the rank is defined if you have a linear transformation or a matrix.



          I did not see a matrix or a linear transformation in your statement to find the rank of it.







          share|cite|improve this answer












          share|cite|improve this answer



          share|cite|improve this answer










          answered 4 hours ago









          Mohammad Riazi-Kermani

          38.3k41957




          38.3k41957




















              up vote
              2
              down vote













              You don't want to think of
              $$beginbmatrix x_1\0\0 endbmatrix$$
              being a vector space. A vector space is a set of vectors (that satisfy certain conditions), so you want
              $$leftlbrace beginbmatrix x_1\0\0 endbmatrix : x_1 in mathbbR rightrbrace$$



              Second, a basis is a collection of linearly independent vectors that span the vector space. So you should not have any zero vectors in your basis.



              Then your basis for this vector space will contain a single vector, and so is one-dimensional.



              As for rank, you don't typically talk about the rank of a vector space; the rank of a matrix is the dimension of the column space of that matrix.






              share|cite|improve this answer
























                up vote
                2
                down vote













                You don't want to think of
                $$beginbmatrix x_1\0\0 endbmatrix$$
                being a vector space. A vector space is a set of vectors (that satisfy certain conditions), so you want
                $$leftlbrace beginbmatrix x_1\0\0 endbmatrix : x_1 in mathbbR rightrbrace$$



                Second, a basis is a collection of linearly independent vectors that span the vector space. So you should not have any zero vectors in your basis.



                Then your basis for this vector space will contain a single vector, and so is one-dimensional.



                As for rank, you don't typically talk about the rank of a vector space; the rank of a matrix is the dimension of the column space of that matrix.






                share|cite|improve this answer






















                  up vote
                  2
                  down vote










                  up vote
                  2
                  down vote









                  You don't want to think of
                  $$beginbmatrix x_1\0\0 endbmatrix$$
                  being a vector space. A vector space is a set of vectors (that satisfy certain conditions), so you want
                  $$leftlbrace beginbmatrix x_1\0\0 endbmatrix : x_1 in mathbbR rightrbrace$$



                  Second, a basis is a collection of linearly independent vectors that span the vector space. So you should not have any zero vectors in your basis.



                  Then your basis for this vector space will contain a single vector, and so is one-dimensional.



                  As for rank, you don't typically talk about the rank of a vector space; the rank of a matrix is the dimension of the column space of that matrix.






                  share|cite|improve this answer












                  You don't want to think of
                  $$beginbmatrix x_1\0\0 endbmatrix$$
                  being a vector space. A vector space is a set of vectors (that satisfy certain conditions), so you want
                  $$leftlbrace beginbmatrix x_1\0\0 endbmatrix : x_1 in mathbbR rightrbrace$$



                  Second, a basis is a collection of linearly independent vectors that span the vector space. So you should not have any zero vectors in your basis.



                  Then your basis for this vector space will contain a single vector, and so is one-dimensional.



                  As for rank, you don't typically talk about the rank of a vector space; the rank of a matrix is the dimension of the column space of that matrix.







                  share|cite|improve this answer












                  share|cite|improve this answer



                  share|cite|improve this answer










                  answered 4 hours ago









                  Morgan Rodgers

                  9,50121338




                  9,50121338



























                       

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