# Variance and Standard Deviation

In this module, you will learn how to quantify the spread of the dataset by calculating the variance and standard deviation.

Start## Key Concepts

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Calculating Variance in Python

Interpretation of Variance

Variance

Standard Deviation

Standard Deviation Units

Calculating Standard Deviation in Python

Calculating Variance in Python

Calculating Variance in Python

```
import numpy as np
values = np.array([1,3,4,2,6,3,4,5])
# calculate variance of values
variance = np.var(values)
```

In Python, we can calculate the variance of an array using the NumPy `var()`

function.

Variance

Lesson 1 of 2

- 2Now that you have learned the importance of describing the spread of a dataset, let’s figure out how to mathematically compute this number. How would you attempt to capture the spread of the data …
- 3We now have five different values that describe how far away each point is from the mean. That seems to be a good start in describing the spread of the data. But the whole point of calculating vari…
- 4We’re almost there! We have one small problem with our equation. Consider this very small dataset: [-5, 5] The mean of this dataset is 0, so when we find the difference between each point and the…
- 5Well done! You’ve calculated the variance of a data set. The full equation for the variance is as follows: \sigma^2 = \frac{\sum_{i=1}^{N}{(X_i -\mu)^2}}{N} Let’s dissect this equation a bit. * …

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