Big O is not the worst case. Big O tells you the upper bound growth rate function. That's it. Worst case tells you a specific example of input which would make the algorithm run for the longest time. Big O can be used to describe the upper bound in worst case, average case, best case. Both are orthogonal.
This may be accurate, but for all practical purposes of conceptual understanding; upper-bound ≈ worst case.
It's simpler to describe Big-O vs Big-Theta vs Big-Omega and also stay away from little-o. Again, this is for simplistic terms and anything outside a data scientist and seasoned engineer should probably stick to the simplified understanding as colloquial terms.
Big O is already the worst case. otherwise, we have Omega and Theta
Big O is not the worst case. Big O tells you the upper bound growth rate function. That's it. Worst case tells you a specific example of input which would make the algorithm run for the longest time. Big O can be used to describe the upper bound in worst case, average case, best case. Both are orthogonal.
This may be accurate, but for all practical purposes of conceptual understanding; upper-bound ≈ worst case.
It's simpler to describe Big-O vs Big-Theta vs Big-Omega and also stay away from little-o. Again, this is for simplistic terms and anything outside a data scientist and seasoned engineer should probably stick to the simplified understanding as colloquial terms.
This is targeting entry level devs, which I think does service in how it describes the topic:
educative.io/blog/a-big-o-primer-f...