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.

Installation:

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 value

width = value.ValueUncertainty(11, 0.4)
length = value.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:

l = value.ValueUncertainty(92.95, 0.1)
T = value.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.

Source Distribution

measurement_stats-0.1.1.tar.gz (13.6 kB view hashes)

Uploaded Source

Built Distribution

measurement_stats-0.1.1-py2.py3-none-any.whl (18.9 kB view hashes)

Uploaded Python 2 Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page