I have an algorithm, shown below, that I need to analyze. Because it's recursive in nature I set up a recurrence relation. 

```
//Input: Adjacency matrix A[1..n, 1..n]) of an undirected graph G  
//Output: 1 (true) if G is complete and 0 (false) otherwise  
GraphComplete(A[1..n, 1..n]) {
  if ( n = 1 )
    return 1 //one-vertex graph is complete by definition  
  else  
    if not GraphComplete(A[0..n − 1, 0..n − 1]) 
      return 0  
    else 
      for ( j ← 1 to n − 1 ) do  
        if ( A[n, j] = 0 ) 
          return 0  
      end
      return 1
}

```

Here is what I believe is a valid and correct recurrence relation: 

$\qquad \begin{align}
 T(1) &= 0 \\
 T(n) &= T(n-1) + n - 1 \quad \text{for } n \geq 2
\end{align}$

The "$n - 1$" is how many times the body of the for loop, specifically the "if A[n,j]=0" check, is executed.

The problem is, where do I go from here? How do I convert the above into something that actually shows what the resulting complexity is?