- So we took a look into sorting algorithms and run-time complexity. Bubble sort and Merge sort . Then we checked how quickly the two sorts run. And whether the ran linearly or quadractically. We learned that linear is faster then quadratic. Also run time means how many steps are taken rather them how many seconds it takes to run.
- First we count the number of steps without constant factors. only the highest-order term matters . We then learned about algorithm analysis and asymptotic notation. We were introduced to this concept with an example of bubble sorting and merge sorting. We checked which of the two aforementioned methods of sorting was the most effective by analyzing their respective algorithms .Algorithms are important because they determine the running time of a function . We also learned about how we do not really care about the number of steps withing an algorithm, but about how the number of steps increases as the size of the input increases
- Then we started talking about Big Oh .We start off by picking a positive real number, c, and a natural number, b, that will work. Then we assume that n is a generic natural number in order to introduce ∀. We assume the antecedent, n ≥ B. We saw the definition of big Oh. So basically we must pick a c past the breakpoint B such that f(n) was less than or equal a constant times g(n) or n-squared.
