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## How do you know if a transformation matrix is one-to-one?

(1) T is one-to-one if and **only if the columns of A are linearly independent**, which happens precisely when A has a pivot position in every column. (2) T is onto if and only if the span of the columns of A is Rm, which happens precisely when A has a pivot position in every row.

## Can a linear transformation be onto but not one-to-one?

In matrix terms, this means that a transformation with matrix A is onto if Ax=b has a solution for any b in the range. If a transformation is onto but not one-to-one, you can think of the domain as having too many vectors to fit into the range.

## How do you tell if it is a linear transformation?

It is simple enough to identify whether or not a given function f(x) is a linear transformation. Just **look at each term of each component of f(x)**. If each of these terms is a number times one of the components of x, then f is a linear transformation.

## What is a one-to-one and onto function?

Definition. A function f : A → B is one-to-one if for each b ∈ B there is at most one a ∈ A with f(a) = b. It is onto **if for each b ∈ B there is at least one a ∈ A with f(a) = b**. It is a one-to-one correspondence or bijection if it is both one-to-one and onto.

## What is linear transformation matrix?

Let be the coordinates of a vector Then. Define a matrix by Then the coordinates of the vector with respect to the ordered basis is. The matrix is called the matrix of the linear transformation with respect to the ordered bases and and is denoted by. We thus have the following theorem.

## How do you know if a transformation is onto?

Definition(Onto transformations)

A transformation T : **R n → R m is onto** if, for every vector b in R m , the equation T ( x )= b has at least one solution x in R n .

## Can a matrix be onto and not one-to-one?

Note a few things: generally, “onto” and “one-to-one” are independent of one another. **You can** have a matrix be onto but not one-to-one; or be one-to-one but not onto; or be both; or be neither.