PLEASE ANSWER QUICKLY For each of the following functions, use big-O notation to give a tight bound on the runtime in terms of n, the number of elements in num_Ist. You can assume that the length of a list can be computed in constant time (that is, the len() operation is O(1) - the amount of time required to compute the length is the same no matter how big the list is).
PLEASE ANSWER QUICKLY For each of the following functions, use big-O notation to give a tight bound on the runtime in terms of n, the number of elements in num_Ist. You can assume that the length of a list can be computed in constant time (that is, the len() operation is O(1) - the amount of time required to compute the length is the same no matter how big the list is).
COMPREHENSIVE MICROSOFT OFFICE 365 EXCE
1st Edition
ISBN:9780357392676
Author:FREUND, Steven
Publisher:FREUND, Steven
Chapter6: Creating, Sorting, And Querying A Table
Section: Chapter Questions
Problem 10EYK
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PLEASE ANSWER QUICKLY
For each of the following functions, use big-O notation to give a tight bound on the runtime in
terms of n, the number of elements in num_Ist. You can assume that the length of a list can be
computed in constant time (that is, the len() operation is O(1) - the amount of time required
to compute the length is the same no matter how big the list is).
![def func2(num_1st):
for j in num_1st:
if j < 20:
print (j)
for k in range (len (num_1st)):
if k < 20:
print (num_1st [k])
O 0(1)
O O(lg(n))
O O(n)
O O(n *lg(n))
○ O(n²)
00(n³)
O 0 (2¹)](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F99733c5f-a94b-4ebf-8e3e-a9283624e793%2Fd88d5e1b-f08c-4973-88ad-c3bc92bbfa58%2Fk4udko_processed.jpeg&w=3840&q=75)
Transcribed Image Text:def func2(num_1st):
for j in num_1st:
if j < 20:
print (j)
for k in range (len (num_1st)):
if k < 20:
print (num_1st [k])
O 0(1)
O O(lg(n))
O O(n)
O O(n *lg(n))
○ O(n²)
00(n³)
O 0 (2¹)
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