One way we can tell we have an observational error is to perform a measurement many times. Since in theory we should be getting the same result each time, if we get different results each time we can attribute that difference to observational error. This means the result of an experiment is usually not a single number but a distribution of numbers.
A distribution of numbers is hard to digest. Often we use summary statistics to describe the distribution in a few numbers. However, this can be misleading if one’s picture of the distribution from the summary statistics is rather different than the true distribution.
Readings:
OpenStax: Descriptive Statistics
Code:
numpy:statistics – all of these summary statistics can be calculated using numpy functions.
