Skip to main content

Measurement statistics with uncertainties and error propagation

Project description

A statistical package for measurement and population statistics that incorporate measurement uncertainties and error propagation.


pip install measurement_stats

Error Propagation

Say, for example, that we have measured a rectangle to be 11 +/- 0.4 centimeters wide and 8 +/- 0.3 centimeters long. We can then calculate the area with uncertainty as follows:

from measurement_stats import ValueUncertainty

width = ValueUncertainty(11, 0.4)
length = ValueUncertainty(8, 0.3)

area = length * width

print('AREA:', area.label)
# $ AREA: 88 +/- 5

For a more complicated example, consider the canonical physics 101 experiment of trying to calculate the acceleration due to gravity using a pendulum. If a student has setup a pendulum with a measured length of 92.95 centimeters and an uncertainty of 0.1 centimeters and measured a period of that pendulum to be 1.936 seconds with an uncertainty of 0.004 seconds, the acceleration due to gravity, with propagated uncertainty, can be determined as follows:

from measurement_stats import ValueUncertainty

l = ValueUncertainty(92.95, 0.1)
T = ValueUncertainty(1.936, 0.004)

g = 4.0 * (math.pi ** 2) * l / (T ** 2)

print('Acceleration Due To Gravity:', g.label)
# $ Acceleration Due To Gravity: 979 +/- 4

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Filename, size & hash SHA256 hash help File type Python version Upload date
measurement_stats-0.2.3-py2.py3-none-any.whl (23.9 kB) Copy SHA256 hash SHA256 Wheel py2.py3
measurement_stats-0.2.3.tar.gz (17.5 kB) Copy SHA256 hash SHA256 Source None

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN SignalFx SignalFx Supporter DigiCert DigiCert EV certificate StatusPage StatusPage Status page