|Delivery Type||Delivery length / details|
|Lecture||11 x 2 Hour Lectures|
|Assessment Type||Assessment length / details||Proportion|
|Semester Assessment||Programming exercise||25%|
|Semester Assessment||Experimental Data Analysis||25%|
|Semester Assessment||Weekly Coursework||25%|
|Semester Assessment||Theory Exercise||25%|
|Supplementary Assessment||As determined by the Departmental Examining Board||100%|
After taking this module students 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 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 and computational work.
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
Simple experiments to measure basic physical quantities, such as gravity, friction, Young's modulus, spring constant or sound speed.
Problem solving and numerical calculation in statistics.
Simple modelling by programming
Writing lab reports.
This module is at CQFW Level 5