澳门六合彩开奖记录
ST4ED-Experimental Design
Module Provider: Mathematics and Statistics
Number of credits: 10 [5 ECTS credits]
Level:7
Terms in which taught: Spring term module
Pre-requisites: ST2LM Linear Models or ST2LMD Linear Models and Data Analysis
Non-modular pre-requisites:
Co-requisites:
Modules excluded: ST3ED Experimental Design
Current from: 2019/0
Email: m.d.dennett@reading.ac.uk
Type of module:
Summary module description:
Designed experiments are carried out in a wide range of applications to learn about the comparative effects of treatments and factors influencing a response. In this module the key principles which are essential for designing effective experiments from available resources will be covered. So too will be the factorial treatment structure and response surface methods, which are appropriate for studying more than one quantitative factor. Consideration will also be given to the analysis of data from experiments.
Aims:
To introduce students to key design principles, different experimental designs, and the practicalities associated with them; and to equip them with the skills to analyse data from different types of experiment.
Assessable learning outcomes:
On completion of the module students will have acquired:
- an appreciation of the statistical principles of good experimental design;
- some ability to plan an experiment;
- some ability to analyse data from a range of standard experimental designs;
- some ability to recognise the practical difficulties of real experiments.
- some ability to review other people's experimental designs.
This module will be assessed to a greater depth than the excluded module ST3ED
Additional outcomes:
Outline content:
Experiments, objectives and their practicalities.
Principles of good design: randomisation, replication, blocking.
Types of experiments: completely randomised designs, block designs, balanced incomplete block designs, single replicate designs.
Treatment structure: contrasts, factorial treatments, main effects, interactions.
Factorial experiments: full factorial designs, hidden replication, fractional factorial designs, confounding.
Quantitative treatments and designs for comparing more than one quantitative treatment factor, including response surfaces.
Brief description of teaching and learning methods:
Lectures supported by practical classes and tutorials.
听 | Autumn | Spring | Summer |
Lectures | 15 | ||
Tutorials | 1 | ||
Practicals classes and workshops | 4 | ||
Guided independent study: | 80 | ||
听 | 听 | 听 | 听 |
Total hours by term | 100 | ||
听 | 听 | 听 | 听 |
Total hours for module | 100 |
Method | Percentage |
Written exam | 80 |
Written assignment including essay | 20 |
Summative assessment- Examinations:
Two hours
Summative assessment- Coursework and in-class tests:
One assignment and one examination.
Formative assessment methods:
Problem sheets, practical classes, and a tutorial.
Penalties for late submission:
The Module Convener will apply the following penalties for work submitted late:
The University policy statement on penalties for late submission can be found at:
You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.
Assessment requirements for a pass:
A mark of 50% overall.
Reassessment arrangements:
One examination paper of 2 hours duration in August/September - the resit module mark will be the higher of the exam mark (100% exam) and the exam mark plus previous coursework marks (80% exam, 20% coursework).
Additional Costs (specified where applicable):
- Required text books:
- Specialist equipment or materials:
- Specialist clothing, footwear or headgear:
- Printing and binding:
- Computers and devices with a particular specification:
- Travel, accommodation and subsistence:
Last updated: 8 April 2019
THE INFORMATION CONTAINED IN THIS MODULE DESCRIPTION DOES NOT FORM ANY PART OF A STUDENT'S CONTRACT.