Big-O Explained

Thank you for the explanation and the links for further reading.

how come this expression evals to false: "n 2 <= 1 * 4 for 1 > 0, we can see that this is now false" ?

also if chose for O(n^2) case c to be 1 then why do you write it as 3?
"3<=3*3^2, for 3>0 which is true, but the truthy applies also to 1st expression where you say it s falsy..

Really clear examples, this is great starting point on the whole theory of algorithm complexity, thanks for sharing this 👍

Great article, thank you for writing!

Thank you for breaking down Big O - such a popular topic in bootcamps! I can see it being used as a go to resource for a lot of new developers.