# Module Information

Module Identifier
PH24010
Module Title
DATA HANDLING AND STATISTICS
2012/2013
Co-ordinator
Semester
Semester 1
Pre-Requisite
Successful completion of Part 1
Other Staff

#### Course Delivery

Delivery Type Delivery length / details
Lecture
Practical 44 Hours. Laboratory. 22 workshop sessions

#### Assessment

Assessment Type Assessment length / details Proportion
Semester Assessment Course Work: SciLab exercises  20%
Semester Assessment Course Work: Theory exercises  40%
Semester Assessment Course Work: Experiment  40%
Supplementary Assessment Supplementary assessment  As determined by Departmental Examination Board  100%

### Learning Outcomes

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 SciLab program to model a physical system.

### Brief description

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 using SciLab.

### Content

Use of SciLab for statistical problems.

Theory of measurement

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.
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.

### Transferable skills

Applying basic statistical principles.
Problem solving and numerical calculation in statistics.
Simple modelling using Scilab.
Writing lab reports.