Every basis for R has exactly vectors. Suppose that a vector space V has a basis with 5 vectors. Then the dimension of V is and every basis for V has exactly vectors. Part III [1 1 2 Connidor tho motrix 4 1 The oolump c neee of A hae

Advanced Engineering Mathematics
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Author:Erwin Kreyszig
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Chapter2: Second-order Linear Odes
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Part II
Every basis for R³ has exactly
vectors. Suppose that a
vector space V has a basis with 5 vectors. Then the dimension of V
is
and every basis for V has exactly
vectors.
Part III
1 1 2
Consider the matrix A
2 2 1|. The column space of A has
3 3 3
dimension
The dimension of the nullspace of A is
Transcribed Image Text:Part II Every basis for R³ has exactly vectors. Suppose that a vector space V has a basis with 5 vectors. Then the dimension of V is and every basis for V has exactly vectors. Part III 1 1 2 Consider the matrix A 2 2 1|. The column space of A has 3 3 3 dimension The dimension of the nullspace of A is
Part I
1
and
-2
Consider the set of vectors vj =
1
V2 =
4
V3
1
The vectors vj and v2 are
Linearly Independent
O Linearly Dependent
The vectors vj and vz are
Linearly Independent
O Linearly Dependent
The vectors v2 and vz are
Linearly Dependent
Linearly Independent
The vectors v1,V2,V3 are
Linearly Independent
Linearly Dependent
O using
We can solve the equation c¡v1 + c2v2 + C3V3 =
coefficients that are not all zeros. For example, we could use c1
1,
C2 =
and c3 =
In general, if v1,V2 and v3 are the columns of a matrix A, then the set
of vectors v1, v2, V3 is linearly independent when the only solution of
Ax =
O is the matrix x =
Even more generally, if v1, v2, ..., Vn are the columns of a matrix A,
then the set of vectors v1, v2, ..., Vn is linearly independent when the
matrix A has rank
Transcribed Image Text:Part I 1 and -2 Consider the set of vectors vj = 1 V2 = 4 V3 1 The vectors vj and v2 are Linearly Independent O Linearly Dependent The vectors vj and vz are Linearly Independent O Linearly Dependent The vectors v2 and vz are Linearly Dependent Linearly Independent The vectors v1,V2,V3 are Linearly Independent Linearly Dependent O using We can solve the equation c¡v1 + c2v2 + C3V3 = coefficients that are not all zeros. For example, we could use c1 1, C2 = and c3 = In general, if v1,V2 and v3 are the columns of a matrix A, then the set of vectors v1, v2, V3 is linearly independent when the only solution of Ax = O is the matrix x = Even more generally, if v1, v2, ..., Vn are the columns of a matrix A, then the set of vectors v1, v2, ..., Vn is linearly independent when the matrix A has rank
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