(a). Explain Big O notation; and give its relevance in Algorithm analysis. (b). Two algorithms A, B sort the same problem. When you go through each algorithm and break them down into their primitive operations, each can be represented as follows: A = 2n + 100n² + 26n + 50 B = 7n4 + 22n² + nlogn + 200 For very large values of n, which of the algorithms A or B will run in the shortest time to solve the problem and why? (c). (i). Distinguish between Best-case running time and Worst-case running time of an algorithm. (ii). Give practical examples to illustrate your answer for (i) above.

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