Linear Algebra I MT22, Rank-Nullity Theorem
Rank-nullity theorem
When proving the rank-nullity theorem
Let $V, W$ be finite dimensional vector spaces and $T: V \to W$ a linear transformation. Then $\text{rank}(T) + \text{nullity}(T) = \dim V$ .
You start by considering a basis $B _ K = \{v _ 1, \ldots, v _ m\}$ of $\ker T$. What do you extend this basis into?
Let $V, W$ be finite dimensional vector spaces and $T: V \to W$ a linear transformation. Then $\text{rank}(T) + \text{nullity}(T) = \dim V$ .
A basis $B _ V = \{v _ 1, \ldots, v _ m, v _ {m+1}, \ldots v _ n\}$ of $V$.
When proving the rank-nullity theorem
Let $V, W$ be finite dimensional vector spaces and $T: V \to W$ a linear transformation. Then $\text{rank}(T) + \text{nullity}(T) = \dim V$ .
You consider three bases:
- $B _ K = \{v _ 1, \ldots, v _ m\}$ of $\ker T$,
- $B _ V = \{v _ 1, \ldots, v _ m, v _ {m+1}, \ldots v _ n\}$ of $V$, and
- $B _ I = \{ ??? \}$
What do you need to show is a valid basis of $\text{Im } T$ for the result to follow?
Let $V, W$ be finite dimensional vector spaces and $T: V \to W$ a linear transformation. Then $\text{rank}(T) + \text{nullity}(T) = \dim V$ .
How is the proof for the dimension formula
Let $U, W$ be subspaces of a finite dimensional vector space $V$. Then $\dim(U+W) + \dim(U \cap W) = \dim(U) + \dim(W)$.
and the proof of the rank-nullity theorem
Let $V, W$ be finite dimensional vector spaces and $T: V \to W$ a linear transformation. Then $\text{rank}(T) + \text{nullity}(T) = \dim V$ .
similar?
Let $U, W$ be subspaces of a finite dimensional vector space $V$. Then $\dim(U+W) + \dim(U \cap W) = \dim(U) + \dim(W)$.
Let $V, W$ be finite dimensional vector spaces and $T: V \to W$ a linear transformation. Then $\text{rank}(T) + \text{nullity}(T) = \dim V$ .
You do it by showing a set of a known size is a basis.