if $p>n$, then the column vectors must be linearly dependent

If $p>n$, then the column vectors must be linearly independent

If $p=n$, then the column vectors must be orthogonal

If $p < n$, then the column vectors must be linearly independent

$y(x)=\exp \left(-\frac{x}{2}\right)\left(\cos \left(\frac{\sqrt{3} x}{2}\right)+\sqrt{3} \sin \left(\frac{\sqrt{3} x}{2}\right)\right)$

$y(x)=\exp \left(-\frac{x}{2}\right)\left(\cos \left(\frac{\sqrt{3} x}{2}\right)+\frac{1}{\sqrt{3}} \sin \left(\frac{\sqrt{3} x}{2}\right)\right)$

$y(x)=\exp \left(-\frac{x}{2}\right)\left(\cos \left(\frac{\sqrt{3} x}{2}\right)-\frac{1}{\sqrt{3}} \sin \left(\frac{\sqrt{3} x}{2}\right)\right)$

$y(x)=\exp \left(-\frac{x}{2}\right)\left(\cos \left(\frac{\sqrt{3} x}{2}\right)-\sqrt{3} \sin \left(\frac{\sqrt{3} x}{2}\right)\right)$

The value of the determinant of $A$ is either +1 or -1 .

The eigenvalues of $A$ have modulus 1.

$\|A x\|=\|x\|$, for all $x \in R^n$, where $\|x\|$ denotes the Euclidean norm of $x$, and $(A x)^{\top}(A y) \neq x^{\top} y$, for all distinct $x, y \in R^n$.

$\|A x\|=\|x\|$, for all $x \in R^n$, where $\|x\|$ denotes the Euclidean norm of $x$, and $(A x)^T(A y)=x^T y$, for all distinct $x, y \in R^n$.