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.
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Key Concepts
Review core concepts you need to learn to master this subject
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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