Lemma: Let $\mathbf{A}\in\mathbb{Z}_q^{n\times m}$ be a uniformly random matrix and $\Lambda^\perp(\mathbf{A})=\lbrace x\in\mathbb{Z}^{m} : \mathbf{A}^Tx\equiv\mathbf{0}\ (\text{mod }q)\rbrace$ be a lattice. Then $\text{det}(\Lambda^\perp(\mathbf{A})) = q^n$ with high probability.
I have found this proof: If $m$ is large enough then rows of $\mathbf{A}$ are linearly independant over $\mathbb{Z}_q$ with high probability. Therefore there are $q^{m-n}$ vector of $\mathbf{Z}_q^{m}$ belonging to $\Lambda^\perp(\mathbf{A})$ since the kernel of $\mathbf{A}$ has dimension $m-n$. From this follows that $\text{vol}(\Lambda^\perp(\mathbf{A})) = \text{det}(\Lambda^\perp(\mathbf{A}))=q^n$.
Question 1 Can anybody please elaborate more on the last implication?
Question 2 How to estimate the probability that a matrix $\mathbf{A}\in\mathbb{Z}_q^{n\times m}$ (where $m> n$) picked uniformly at random has linearly independant rows?
Edit Thanks to the comments Question 2 is no longer a problem.