Answer:
Her performance over the course of a season.
Explanation:
An athlete is signed for a season. These days each aspect of an athlete is noted through the effective use of the best technology. However, for detailed study, one or several plays, and certainly not the second half of a game is enough. It's required to collect the details for a complete season. And that is possible, as an athlete is hired for a season. And through such a detailed data set of a complete season, we can now train a machine as well, and it will let the athlete know where she is going wrong. And thus she can improve and remove those faults from her game, and become a better athlete. And even for a coach, one complete season is required, though when he has not seen her playing before that season. It's assumed that this is her first season. All the options mentioned are good, but the best is certainly the one with complete details, and that is a complete season. The rest is good but not the best.
Answer: Virus Hoax
Explanation:
A computer virus hoax is a message that warns someone of a false virus threat. It is a a chain email that encourages who ever has received the message to pass it to other people as a form of warning.
Answer:
The governor found a way to free Sostre without assessing whether or not he was guilty or innocent of drug crime in buffalo.
Explanation:
Answer:
There is nothing to answer from this statement.
Explanation:
Can you rephrase the statement into question?
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.
