MA321-7-SP-CO:
Applied Statistics
2017/18
Mathematics, Statistics and Actuarial Science (School of)
Colchester Campus
Spring
Postgraduate: Level 7
Current
Monday 15 January 2018
Friday 23 March 2018
15
05 March 2014
Requisites for this module
(none)
(none)
(none)
(none)
(none)
MSC G30412 Data Science,
MSC G30424 Data Science,
DIP G30009 Statistics,
MSC G30012 Statistics
Aims
This module covers four application areas of statistics: multivariate methods, censored data: survival and reliability, demography and epidemiology and sampling (PG module 5 of the syllabus of the Royal Statistical Society).
On completion of the course students should be able to (learning outcomes):
- Understand and to apply multivariate methods;
- Assess the results of discriminant analysis, principal components, cluster analysis and multivariate analysis of variance;
- Model and to analyse censored data;
- Understand and to apply demographical and epidemiological methods;
- Understand and to apply sampling methods.
Syllabus:
Multivariate methods
Vectors of expected values. Covariance and correlation matrices. Discriminant analysis, choice between two populations, calculation of discriminant function, and probability of misclassification, test and training samples, leave-one-out and k-fold cross-validation, idea of extension to several populations. Principal components; definition, interpretation of calculated components, use in regression. Cluster analysis, similarity measures, single-link and other hierarchical methods, k-means. Informal approaches to checking for multivariate Normality. Tests and confidence regions for multivariate means.
Censored data: survival and reliability
Problems involving censored data, for example in clinical and engineering contexts.
Reliability and life testing. Hazard and survivor functions. Kaplan-Meier estimate of survivor function. Weibull and hazard plots. Proportional hazards and Cox regression. Checking for non-proportionality of hazards.
Demography and epidemiology
Population pyramids. Life tables. Standardised rates (e.g. mortality). Incidence and prevalence. Design and analysis of cohort (prospective) studies. Design and analysis of case-control (retrospective) studies. Confounding and interaction.
Matched case control design and analyses, using McNemar's test. Causation.
Relative risk. Odds ratio. Estimation and confidence intervals for 2x2 tables.
Mantel-Haenszel procedure. Sensitivity, specificity, ROC curves, positive predictive value, negative predictive value.
Sampling
Census and sample survey design. Target and study populations, uses and limitations of non-probability sampling methods, sampling frames, sampling fraction.
Simple random sampling. Estimators of totals, means and proportions; bias. Estimated standard errors, confidence intervals and precision. Sampling fraction and finite population correction. Ratio and regression estimators. Stratified random sampling. Estimators of totals, means and proportions; bias. Estimated standard errors, confidence intervals and precision. Cost functions. Proportional and optimal allocations. Limitations of stratified sampling. One-stage cluster sampling. Estimators for totals, means and proportions with equal cluster sizes and with different cluster sizes. Estimated standard errors, confidence intervals and precision. Link with systematic sampling. Description of two-stage sampling and of multi-stage sampling. Limitations.
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 spring term, together with 3 revision lectures in the summer term. A project is undertaken in groups. Coursework consists of problem sheets, a project report and presentation.
This module does not appear to have a published bibliography.
Assessment items, weightings and deadlines
| Coursework / exam |
Description |
Deadline |
Coursework weighting |
| Coursework |
Initial Task |
|
25% |
| Coursework |
Group Presentation and Group Project |
|
75% |
| 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.
Dr Martin Griffiths, email griffm@essex.ac.uk
Miss Shauna McNally, Graduate Administrator, Tel. 01206 872704, email smcnally (Non essex users should add @essex.ac.uk to create the full email address)
Yes
No
No
Prof Fionn Murtagh
University of Huddersfield
Professor of Data Science
Available via Moodle
Of 38 hours, 33 (86.8%) hours available to students:
5 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s).
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