Thanks in advance,

SHORT ANSWER SECTION - Provide in depth answers in your own words.

1. (5 Points) Describe data structures in your own words.

2. (5 Points) What is n, in Big O notation? O(n), O(n ^2), etc.

3. (10 Points) Describe best case, average case, and worst case in terms of Big O Notation. When implementing algorithms or data structures which two Big O cases are most important to consider and why?

3. (10 Points) Compare and Contrast Sequential Access to Random Access and give examples of algorithms or data structures that align with both concepts.

4. (10 Points) Explain the trade offs or decisions required when writing/creating computer programs and how the decisions relate to Data Structures, algorithms, and Big O notation.

5. (10 Points) Describe divide and conquer algorithms in your won words. Why are divide and conquer algorithms useful?

Big O SECTION List appropriate Worst Case Big O Notation under the different algorithms or data structure operations.

Choose from right column and place under left column.

Right column can be used more than once or not all.

Leftcolumn Right column

A. Quicksort Recursive Algorithm on an Array of 100,000 elements ========== O(1)

B. Binary Search on sorted array of 100,000 elements =====================O(n)

C. Iterating over an array =========================================O(n^2)

D. Deleting last element in an array of 10 elements===================== O(log n)

E. Accessing first element in Array of 1,000,000 elements ===============O(n log n)