Uncertainty
Uncertainty in Physical Measurements
(C) David M. Harrison 2013-2016
based on Guide to the Expression of Uncertainty in Measurement (GUM)
An introduction intended for students, and another section introducing the Modules to Instructors.
Statistics of rolling a pair of dice, including an Activity of repeating the roll of dice 36 times. The module introduces:
- Histograms
- Probability distributions
- Triangular probability distributions
- The mean or average
- The deviation
- The variance
The modules also include links to videos using the computing environment (Python or Excel) for analysis of the data.
Uncertainty associated with digital instruments, including an Activity of measuring the diameter of a coin with a digital caliper. The module introduces:
- Rectangular or uniform probability distributions
- The standard deviation
- The uncertainty associated with a measurement
- Accuracy
- Quadrature
It also discusses significant figures in an experimental context.
Uncertainty associated with analog instruments, including an Activity of measuring the diameter of a coin with a ruler. The module also discusses systematic errors.
Uncertainty associated with repeated measurements that do not give the same values. It includes an Activity of measuring the time it takes a piece of paper to fall to the floor, and another Activity of measuring the ratio of the circumference to the radius of a number of metal hoops. The module introduces:
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Scattered or dispersed measurements
- Bell-shaped curves, also called Gaussian distributions or normal distributions
- Gaussian probability distributions.
- The uncertainty in the estimated standard deviation
- Propagation of uncertainties
- The uncertainty in the mean
A 10 minute PowerPoint review of bell-shaped curves that is useful after the students have read the Module but before they begin work on it. Primarily intended for instructors.
This Module is mostly concerned with fitting data to models, both by hand and by using least-squares techniques. It emphasises the visual display of data. The module introduces:
- Independent and dependent variables of a dataset
- Residuals of a fit
- Sum of the squares of the residuals
- Method of least squares
- Degrees of freedom of a fit
- Chi-squared
- Effective variance method
Miscellaneous topics that don't fit nicely into the previous Modules. The Sections are:
- Confidence Intervals
- Uncertainty in a Count
- Systematic Effects and Calibration
- Outliers and Robust Estimators
- Accepted Values
The Module includes an Activity of calibrating a force sensor, and another Activity using robust measures of data to determine the period of a pendulum.