Daily LinAlg T/F Questions @LinAlgDaily
Posting daily true/false questions relating to undergraduate linear algebra. Please comment proofs/counterexamples. Link below for question and solution bank. docs.google.com/spreadsheets/d… Joined December 2022-
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T/F: it is possible that A is an invertible matrix and A is the standard matrix for a non-injective function
Hard mode: T/F: suppose A and B are matrices such that AB is defined. Any vector in col(AB) is also in col(A)?
T/F: a vector may be in colA and also in Null A?
T/F: if subspace V is defined V=span{v1, …, vn} then {v1, …, vn} is a basis for V?
T/F: any basis for R^n must have exactly n vectors.
T/F: if Ax = b and b is not the zero vector then x is certainly not in the null space of A.
T/F: if A is mxn and m > n then A^T may not have independent columns
T/F: BAx must be in col(A)? Must be in col(B)?
T/F: any matrix whose columns form a basis for R^n has pivots every row and every columns.
T/F: Let A be mxn. Then Ax is in Col(A) for every x in R^n.
If A is size mxn, and b is in Col(A) for every b in R^m, the the transformation T: R^n |-> R^m defined by T(x)=Ax is onto (surjective).
T/F: let A be a 3x4 matrix. Then the transformation whose standard matrix is A cannot be onto.
Counterexample: [[1, 0], [0, 1]] can’t wait until we get to eigenvectors unit this semester
T/F: if Ax=x for some then A must not be invertible.
This is a tough one for my students but if w were in fact a LC of u and v then c1u+c2v-w=0 for some weights c1 and c2 and thus the set {u, v, w} must be dependent. Are my followers familiar with contrapositive arguments?
T/F: if {u, v, w} is a linearly independent set of vectors then w is certainly not a linear combination of u and v
counterexample: A=[[1 0], [0, 0]] and b = [0, 1]
T/F: suppose Ax=b is inconsistent for some b where A is size mxn. We must therefore have m>n.
This is true because if the cols are LI (call them a1, …, an) then the only solution to c1a1+…+cnan=0 Is the trivial one (this is the textbook definition of LI) And so Ax=0 has only the trivial solution x=0.
T/F: If the columns of A are linearly independent then the null space of A contains only the zero vector?
This is true because the range of the transformation is nothing but all of the linear combinations of the columns of A, all of which are vectors in R^m.
If A is size mxn then the range of the transformation T(x)=Ax is a subset of R^n?
Gonna go on a solutions release spam on some recent tweets
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