Measurement statistics with uncertainties and error propagation

## Project description

# Measurement Statistics

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

## 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

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