Module Identifier | PH24010 | ||

Module Title | DATA HANDLING AND STATISTICS | ||

Academic Year | 2001/2002 | ||

Co-ordinator | Professor Geraint Vaughan | ||

Semester | Semester 1 | ||

Other staff | Dr James Whiteway | ||

Pre-Requisite | Core Physics Modules at Level 1 | ||

Course delivery | Lecture | 8 lectures (first half of semester) | |

Seminars / Tutorials | 3 workshops | ||

Laboratory | 36 Hours 12 laboratory sessions (3 hours each) | ||

Assessment | Course work | MathCad exercises | 10% |

Course work | Theory exercises | 10% | |

Course work | Young's Modulus experiment | 30% | |

Course work | Photometry experiment | 30% | |

Exam | 1 Hours End of Semester Examinations | 20% |

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, together with a demonstration of selection effects in compiling a data-base. Further instruction on the MathCad programming package will be given.

After taking this module student should be able to:

- understand the nature of random error in experimental data
- use the Gaussian distribution and apprectiate 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
- appreciate how selection effects introduce a bias into a data sample
- 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.

Use of STOMP CAL package.

Simple modelling using MathCad.

Use of Mathcad for statistical problems.

Theory of measurement (STOMP Measurement and Uncertainty package)

Random and systematic errors

Accuracy and precision

Mean and standard deviation

Gaussian, Poisson and Binomial distribtions

Combining uncertainties

The Least Squares Principle, graphing data and fitting a straight line to data.

Experiments

1. Photometry experiment. Exercise in taking and transforming 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.

Roger Barlow.

R. Larsen.

P.M. Morse.