|Delivery Type||Delivery length / details|
|Practical||44 Hours. Laboratory. 22 laboratory sessions|
|Assessment Type||Assessment length / details||Proportion|
|Semester Assessment||Course Work: MathCad exercises||20%|
|Semester Assessment||Course Work: Theory exercises||20%|
|Semester Assessment||Course Work: Young's Modulus experiment||30%|
|Semester Assessment||Course Work: Photometry experiment||30%|
|Supplementary Assessment||Supplementary assessment As determined by Departmental Examination Board||100%|
After taking this module student should be able to:
- explain the nature of random error in experimental data
- use the Gaussian distribution and appreciate why it applies in so many cases
- calculate the mean and standard deviation of data following a simple, unbiased Gaussian
- recognise the effect of inter-dependence of measurements and extreme values on data sets
- combine several different errors to derive a final error
- identify the most important source of error in an experiment and concentrate on reducing that error
- fit a straight line to experimental data and evaluate the standard error in the slope and intercept.
- write a simple MathCad program to model a physical system.
This module is a laboratory-based course where the handling of data in selected experiments is treated in parallel with a course on the theory of measurement, the nature of experimental errors, random and systematic. The course provides an introduction to the basic statistics encountered in Physics, including the Binomial, Poisson and Normal distributions, and simple least-squares regression. The estimate of standard error, the combination of errors and the optimum design of experiments to reduce the final error in the most efficient way are covered. Applications of these concepts will be made through practical work and computational work using MathCad.
Theory of measurement
Random and systematic errors
Accuracy and precision
Mean and standard deviation
Gaussian, Poisson and Binomial distribtions
The Least Squares Principle, graphing data and fitting a straight line to data
1. Photometry experiment.
Determine the temperature of an incandescent filament by optical measurements.
2. Young's Modulus experiment.
Determination of Young's Modulus, with special care taken to estimate the random uncertainty
in the final result. Identification of the parameter contributing most to the final error.
3. Compound pendulum experiment.
Determine the properties of a compound pendulum and the value of gravity at the Earth's surface.
Simple modelling using MathCad.
Writing lab reports.
Reading ListRecommended Text
Roger Barlow Statistics Wiley Primo search Reference Text
P.M. Morse Vibration and Sound Primo search R. Larsen Introduction to Mathcad 2000 Prentice Hall Primo search
This module is at CQFW Level 5