Hello Guys, How are you all? Hope You all Are Fine. Today We Are Going To learn about **How can I calculate the variance of a list in python** **in Python**. So Here I am Explain to you all the possible Methods here.

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## How can I calculate the variance of a list in python?

**How can I calculate the variance of a list in python?**Well, there are two ways for defining the variance. You have the variance

*n*that you use when you have a full set, and the variance*n-1*that you use when you have a sample.**calculate the variance of a list in python**Well, there are two ways for defining the variance. You have the variance

*n*that you use when you have a full set, and the variance*n-1*that you use when you have a sample.

## Method 1

Starting `Python 3.4`

, the standard library comes with the `variance`

function (*sample variance* or *variance n-1*) as part of the `statistics`

module:

from statistics import variance # data = [-14.82381293, -0.29423447, -13.56067979, -1.6288903, -0.31632439, 0.53459687, -1.34069996, -1.61042692, -4.03220519, -0.24332097] variance(data) # 32.024849178421285

The *p**opulation variance* (or *variance n*) can be obtained using the `pvariance`

function:

from statistics import pvariance # data = [-14.82381293, -0.29423447, -13.56067979, -1.6288903, -0.31632439, 0.53459687, -1.34069996, -1.61042692, -4.03220519, -0.24332097] pvariance(data) # 28.822364260579157

Also note that if you already know the mean of your list, the `variance`

and `pvariance`

functions take a second argument (respectively `xbar`

and `mu`

) in order to spare recomputing the mean of the sample (which is part of the variance computation).

## Method 2

Well, there are two ways for defining the variance. You have the variance *n* that you use when you have a full set, and the variance *n-1* that you use when you have a sample.

The difference between the 2 is whether the value `m = sum(xi) / n`

is the real average or whether it is just an approximation of what the average should be.

Example1 : you want to know the average height of the students in a class and its variance : ok, the value `m = sum(xi) / n`

is the real average, and the formulas given by Cleb are ok (variance *n*).

Example2 : you want to know the average hour at which a bus passes at the bus stop and its variance. You note the hour for a month, and get 30 values. Here the value `m = sum(xi) / n`

is only an approximation of the real average, and that approximation will be more accurate with more values. In that case the best approximation for the actual variance is the variance *n-1*

varRes = sum([(xi - m)**2 for xi in results]) / (len(results) -1)

Ok, it has nothing to do with Python, but it does have an impact on statistical analysis, and the question is tagged statistics and variance

Note: ordinarily, statistical libraries like numpy use the variance *n* for what they call `var`

or `variance`

, and the variance *n-1* for the function that gives the standard deviation.

**Summery**

It’s all About this issue. Hope all Methods helped you a lot. Comment below Your thoughts and your queries. Also, Comment below which Method worked for you? Thank You.

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