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Machine Learning - Standard Deviation
What is Standard Deviation?
Standard deviation is a number that describes how spread out the values are.
A low standard deviation means that most of the numbers are close to the mean (average) value.
A high standard deviation means that the values are spread out over a wider range.
Example: This time we have registered the speed of 7 bikes are
In a computer sense, a data set is any data collection. It can be anything from a program to a complete website.
Example of an array:
speed = [32,111,138,28,59,77,97]
The standard deviation is:
0.9
Meaning that most of the values are within the range of 0.9 from the mean value, which is 86.4./p>
The NumPy module has a method to calculate the standard deviation:
Example
import numpy
speed = [86,87,88,86,87,85,86]
x = numpy.std(speed)
print(x)
speed = [86,87,88,86,87,85,86]
x = numpy.std(speed)
print(x)
Variance
Variance is another number that indicates how spread out the values are.
Example
import numpy
speed = [32,111,138,28,59,77,97]
x = numpy.var(speed)
print(x)
speed = [32,111,138,28,59,77,97]
x = numpy.var(speed)
print(x)
Standard Deviation
Example
import numpy
speed = [32,111,138,28,59,77,97]
x = numpy.std(speed)
print(x)