What does it mean to not have a pivot in every row

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SUMMARY

The discussion centers on the implications of a matrix A lacking a pivot in every row, specifically in relation to a theorem involving linear equations and linear combinations. It is established that if A does not have a pivot in every row, then the equation Ax lacks a solution for some vectors b in Rm, thus disproving statement (1). Furthermore, the absence of a pivot indicates that the columns of A do not span Rm, directly impacting statements (2) and (3). The determinant of A being zero confirms that A is not invertible, reinforcing the relationship between pivots and linear independence.

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I am trying to fully understand this theorem

Theorem: Let A be an m x n matrix. The following are all true or all false.
1. For each b in Rm, the equation Ax has a solution
2. Each b in Rm is a linear combination of the columns of A.
3. The columns of A span Rm
4. A has a pivot position in every row.

So when A does not have a pivot in every row, it disproves (1) because each b will not have a solution.

How would you disprove (2) with (4)?
 
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If A does not have a pivot in every row, then its determinant is 0 and A is not invertible.

When you say "disprove (2) with (4)" do you mean disprove (2) assuming (4) is NOT true?

If A does not have a pivot in every row, then A maps Rn[/itex] into a propersubspace of Rm so there exist b in Rm not in that subspace.
 

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