Answer:
- import math
-
- def standard_deviation(aList):
- sum = 0
- for x in aList:
- sum += x
-
- mean = sum / float(len(aList))
-
- sumDe = 0
-
- for x in aList:
- sumDe += (x - mean) * (x - mean)
-
- variance = sumDe / float(len(aList))
- SD = math.sqrt(variance)
-
- return SD
-
- print(standard_deviation([3,6, 7, 9, 12, 17]))
Explanation:
The solution code is written in Python 3.
Firstly, we need to import math module (Line 1).
Next, create a function standard_deviation that takes one input parameter, which is a list (Line 3). In the function, calculate the mean for the value in the input list (Line 4-8). Next, use the mean to calculate the variance (Line 10-15). Next, use sqrt method from math module to get the square root of variance and this will result in standard deviation (Line 16). At last, return the standard deviation (Line 18).
We can test the function using a sample list (Line 20) and we shall get 4.509249752822894
If we pass an empty list, a ZeroDivisionError exception will be raised.
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Answer:
D- Trojan Horse
Explanation:
Trojan horse is a malware that has hidden code and look legitimate in order to damage or transfer harmful action on the computer.
Example hackers can disguise as Trojan horse by spying on the victims computer in order to gain access to sensitive data on the computer over the network.
Answer:
The answer is option A.
Explanation:
Negative numbers can be found by binary search, this makes option B incorrect.
Unsorted and randomized lists are also not things that support a binary search, options C and D are incorrect.
Binary search uses a technique where the middle element of the list is located and used to determine whether the search should be done within the lower indexed part of the list or the higher. So for a list to be binary search-able, it should be sorted and not randomized.
The answer is A.
I hope this helps.
