MA317-7-AU-CO:
Modelling Experimental Data
2016/17
Mathematics, Statistics and Actuarial Science (School of)
Colchester Campus
Autumn
Postgraduate: Level 7
Current
15
06 February 2014
Requisites for this module
(none)
(none)
(none)
(none)
MA321
MSC G30412 Data Science,
DIP G30009 Statistics,
MSC G30012 Statistics
This module is concerned with the application of linear models to the analysis of data. The underlying assumptions are discussed and general results are obtained using matrices. The standard approach to the analysis of normally distributed data using ANOVA is introduced. Methods for the design and analysis of efficient experiments are introduced. The general methodology is extended to logistic regression and the analysis of multidimensional contingency tables.
Learning Outcomes
On completion of the module students should be able to:
- calculate confidence intervals for parameters and prediction intervals for future observations;
- understand how to represent a linear model in matrix form;
- check model assumptions and identify influential observations;
- identify simple designed experiments;
- construct factorial experiments in blocks;
- adapt linear models to fit growth curves;
- carry out logistic regression;
- analyze cross-tabulated data using log linear models;
- analyse linear models using R.
No information available.
No information available.
No additional information available.
The module has 38 contact hours in total. These consist of 25 lectures, 5 labs and 5 classes during the autumn term, together with 3 revision lectures in the summer term.
Assessment items, weightings and deadlines
| Coursework / exam |
Description |
Deadline |
Coursework weighting |
| Coursework |
Group Presentation |
|
0% |
| Coursework |
Group Project Report |
|
100% |
| Exam |
Main exam: 180 minutes during Summer (Main Period)
|
Additional coursework information
Information about coursework deadlines can be found in the "Coursework and Exams" section of the Current Students, Information for Students Maths web pages: Coursework and Test Information
Exam format definitions
- Remote, open book: Your exam will take place remotely via an online learning platform. You may refer to any physical or electronic materials during the exam.
- In-person, open book: Your exam will take place on campus under invigilation. You may refer to any physical materials such as paper study notes or a textbook during the exam. Electronic devices may not be used in the exam.
- In-person, open book (restricted): The exam will take place on campus under invigilation. You may refer only to specific physical materials such as a named textbook during the exam. Permitted materials will be specified by your department. Electronic devices may not be used in the exam.
- In-person, closed book: The exam will take place on campus under invigilation. You may not refer to any physical materials or electronic devices during the exam. There may be times when a paper dictionary,
for example, may be permitted in an otherwise closed book exam. Any exceptions will be specified by your department.
Your department will provide further guidance before your exams.
Overall assessment
Reassessment
Module supervisor and teaching staff
Dr Martin Griffiths, email griffm@essex.ac.uk, tel 01206 873027
Mrs Shauna Meyers - Graduate Administrator. email: smcnally (Non essex users should add @essex.ac.uk to create the full email address), Tel 01206 872704
Yes
Yes
No
Prof John Nigel Scott Matthews
The University of Newcastle-upon-Tyne
Professor of Medical Statistics
Available via Moodle
Of 36 hours, 31 (86.1%) hours available to students:
4 hours not recorded due to service coverage or fault;
1 hours not recorded due to opt-out by lecturer(s).
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