Answer 1

Big-O refers to the complexity of the algorithm in time.
O(n) means that the algorithm will take on the order of n operations to complete its purpose.
For instance, if you want to find an element in an unsorted array of n elements, your algorithm will need in the worst case n iterations (in case the element is the last one)

for (int i=0;i<array.size();i++){
if (array[i]==x){
print("I found it");
break;
}
} //n=array.size()