In this section, you are asked to analyse the worst-case computational time complexity of Python functions....

 

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In this section, you are asked to analyse the worst-case computational time complexity of Python functions. Always identify the order of growth in the tightest and simplest possible form using big-O notation, e.g., write O(n) instead of O(2n+n/2). Question 14 (Complexity 1) State the overall worst-case time complexity of the below function and provide a short explanation of your answer. The function accepts an integer n as input. (2 marks) def mystery (n): num = 1 count = 0 while num In this section, you are asked to analyse the worst-case computational time complexity of Python functions. Always identify the order of growth in the tightest and simplest possible form using big-O notation, e.g., write O(n) instead of O(2n+n/2). Question 14 (Complexity 1) State the overall worst-case time complexity of the below function and provide a short explanation of your answer. The function accepts an integer n as input. (2 marks) def mystery (n): num = 1 count = 0 while num