Given two vectors $v = (v_1,\dots,v_n)$ and $w = (w_1\dots,w_n)$ in $\mathbb{R}^n$, lets define $v*w$ as the matrix in which the element of row $i$ and column $j$ is $v_iw_j$. Supose that $v$ and $w$ are linearly independent. Find the rank of the matrix $v*w - w*v.$

1. **Define the matrix \( A = v * w - w * v \):**
   Given two vectors \( v = (v_1, v_2, \ldots, v_n) \) and \( w = (w_1, w_2, \ldots, w_n) \) in \( \mathbb{R}^n \), the matrix \( v * w \) is defined such that the element in the \( i \)-th row and \( j \)-th column is \( v_i w_j \). Similarly, the matrix \( w * v \) is defined such that the element in the \( i \)-th row and \( j \)-th column is \( w_i v_j \). Therefore, the matrix \( A \) is given by:
   \[
   A = v * w - w * v
   \]
   The element in the \( i \)-th row and \( j \)-th column of \( A \) is:
   \[
   A_{ij} = v_i w_j - w_i v_j
   \]

2. **Construct the matrix \( A \) for \( n = 3 \):**
   For \( n = 3 \), the matrix \( A \) is:
   \[
   A = \begin{bmatrix}
   0 & v_1 w_2 - w_1 v_2 & v_1 w_3 - w_1 v_3 \\
   v_2 w_1 - w_2 v_1 & 0 & v_2 w_3 - w_2 v_3 \\
   v_3 w_1 - w_3 v_1 & v_3 w_2 - w_3 v_2 & 0
   \end{bmatrix}
   \]
   Note that the diagonal elements are all zero.

3. **Analyze the rank of \( A \):**
   To determine the rank of \( A \), we need to check the linear independence of its rows (or columns). We observe that each element \( A_{ij} \) is of the form \( v_i w_j - w_i v_j \).

4. **Check linear independence for \( n = 3 \):**
   Consider the first row of \( A \):
   \[
   \begin{bmatrix}
   0 & v_1 w_2 - w_1 v_2 & v_1 w_3 - w_1 v_3
   \end{bmatrix}
   \]
   We need to check if this row can be written as a linear combination of the other two rows. Suppose:
   \[
   c_1 \begin{bmatrix}
   v_2 w_1 - w_2 v_1 & 0 & v_2 w_3 - w_2 v_3
   \end{bmatrix} + c_2 \begin{bmatrix}
   v_3 w_1 - w_3 v_1 & v_3 w_2 - w_3 v_2 & 0
   \end{bmatrix} = \begin{bmatrix}
   0 & v_1 w_2 - w_1 v_2 & v_1 w_3 - w_1 v_3
   \end{bmatrix}
   \]
   This gives us the system of equations:
   \[
   c_1 (v_2 w_1 - w_2 v_1) + c_2 (v_3 w_1 - w_3 v_1) = 0
   \]
   \[
   c_1 (v_2 w_3 - w_2 v_3) = v_1 w_3 - w_1 v_3
   \]
   \[
   c_2 (v_3 w_2 - w_3 v_2) = v_1 w_2 - w_1 v_2
   \]

5. **Solve for \( c_1 \) and \( c_2 \):**
   From the second and third equations, we get:
   \[
   c_1 = \frac{v_1 w_3 - w_1 v_3}{v_2 w_3 - w_2 v_3}
   \]
   \[
   c_2 = \frac{v_1 w_2 - w_1 v_2}{v_3 w_2 - w_3 v_2}
   \]
   Substituting these into the first equation, we need to verify that:
   \[
   \left( \frac{v_1 w_3 - w_1 v_3}{v_2 w_3 - w_2 v_3} \right) (v_2 w_1 - w_2 v_1) + \left( \frac{v_1 w_2 - w_1 v_2}{v_3 w_2 - w_3 v_2} \right) (v_3 w_1 - w_3 v_1) = 0
   \]
   This equation holds due to the linear independence of \( v \) and \( w \).

6. **Generalize for any \( n \):**
   By similar reasoning, for any \( n \), the \( k \)-th row can be written as a linear combination of the second and third rows. Therefore, the rank of the matrix \( A \) is always 2.

The final answer is \(\boxed{2}\).