From Introduction to Algorithms by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein
For any two functions $f(n)$ and $g(n)$, we have $f(n) = \Theta(g(n))$ if and only if $f(n) = O(g(n))$ and $f(n) = \Omega(g(n))$
The worst case run time complexity of insertion sort is $O(n^2)$. However in case of sorted array the running time of the algorithm is $\Omega(n)$.
Don't these two things contradict with Theorem 3.1 when we say that run time complexity of Insertion sort in worst case is $\Theta(n^2)$.
Not sure if I am trying two mix different concepts; please help me in either case.