"Which complexity represents a majority of algorithms?"
My answer would be that there is no running time that represents the majority of algorithms. Some common algorithms (for example, BFS and DFS) run in linear time; some run in loglinear time (for example, sorting); dynamic programming algorithms run in superlinear polynomial time (for example, the standard algorithm for edit distance runs in quadratic time); algorithms involving matrix multiplication run (practically) in cubic time, and theoretically faster; SAT solvers have worst case exponential running time; and some algorithms involved in verification have even faster growing worst case running time, or are not guaranteed to terminate at all.