ST220 Introduction to Mathematical Statistics
Please note that all lectures for Statistics modules taught in the 2022-23 academic year will be delivered on campus, and that the information below relates only to the hybrid teaching methods utilised in 2021-22 as a response to Coronavirus. We will update the Additional Information (linked on the right side of this page) prior to the start of the 2022/23 academic year.
Throughout the 2021-22 academic year, we will be adapting the way we teach and assess your modules in line with government guidance on social distancing and other protective measures in response to Coronavirus. Teaching will vary between online and on-campus delivery through the year, and you should read the additional information linked on the right hand side of this page for details of how this will work for this module. The contact hours shown in the module information below are superseded by the additional information.You can find out more about the University’s overall response to Coronavirus at: https://warwick.ac.uk/coronavirus.
All dates for assessments for Statistics modules, including coursework and examinations, can be found in the Statistics Assessment Handbook at http://go.warwick.ac.uk/STassessmenthandbook
ST220-12 Introduction to Mathematical Statistics
Introductory description
This module runs in Term 1 and is optional for students in their second year and from outside the Statistics department. It is of particular relevance to students who may be interested in taking third year Statistics modules.
Students from outside Statistics and not in their second year should take 'ST226-12 Introduction to Mathematical Statistics' instead, which is identical to this module.
This module is not available to students who have their home department in Statistics, who take equivalent modules.
Prerequisites: ST111 Probability A and ST112 Probability B
Leads to: Many ST3 modules.
Module aims
This module is designed for students in the Mathematics, Computer Science and other non-Statistics departments. It will introduce the main ideas of statistical inference emphasising the use of likelihood for estimation and testing. These ideas are fundamental to the use of statistics in modern applications such as mathematical finance, telecommunications, bioinformatics as well as more traditional areas such as insurance, engineering and the social sciences.
Outline syllabus
This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.
- Standard families of Probability distributions: Binomial, Geometric, Poisson, Exponential, Gamma, Gaussian.
- The weak law of large numbers and central limit theorem.
- The Multivariate Gaussian distribution. Orthogonality and Independence for jointly Gaussian random variables.
Distributions derived from the Gaussian: Chi-squared, t and F. - The notion of a parametrized Statistical model, and examples.
- Likelihood including maximum likelihood estimates and use of likelihood ratios to compare hypotheses.
- The repeated sampling principle: bias and MSE, confidence intervals and p-values.
- Fisher's theorem on Gaussian sampling, and its extension to linear regression.
Learning outcomes
By the end of the module, students should be able to:
- Understand more advanced notions of probability needed in mathematical statistics including properties of multivariate Gaussian distributions, the law of large numbers, and the central limit theorem.
- Understand the main notions of statistical inference including a (parametrized) statistical model, an estimator and its sampling distribution, and hypothesis tests.
- Be able to calculate maximum likelihood estimators in a variety of examples. Be able to derive properties of sampling distributions of estimators in a variety of examples, and thereby construct confidence intervals.
- Be able to use likelihood ratios to construct hypothesis tests in a variety of examples including the classical t and F tests.
Indicative reading list
View reading list on Talis Aspire
Subject specific skills
TBC
Transferable skills
TBC
Study time
| Type | Required | Optional |
|---|---|---|
| Lectures | 30 sessions of 1 hour (25%) | 2 sessions of 1 hour |
| Tutorials | 5 sessions of 1 hour (4%) | |
| Private study | 73 hours (61%) | |
| Assessment | 12 hours (10%) | |
| Total | 120 hours |
Private study description
Weekly revision of lecture notes and materials, wider reading and practice exercises, working on problem sets and preparing for examination.
There will be fortnightly problem sets which will be marked and returned with feedback in tutorials.
Costs
No further costs have been identified for this module.
You do not need to pass all assessment components to pass the module.
Assessment group D1
| Weighting | Study time | Eligible for self-certification | |
|---|---|---|---|
| Multiple Choice Quiz 1 | 2% | 3 hours | Yes (waive) |
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A multiple choice quiz which will take place during the term that the module is delivered. |
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| Multiple Choice Quiz 2 | 3% | 3 hours | Yes (waive) |
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A multiple choice quiz which will take place during the term that the module is delivered. |
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| Multiple Choice Quiz 3 | 2% | 3 hours | Yes (waive) |
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A multiple choice quiz which will take place during the term that the module is delivered. |
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| Multiple Choice Quiz 4 | 3% | 3 hours | Yes (waive) |
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A multiple choice quiz which will take place during the term that the module is delivered. |
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| On-campus Examination | 90% | No | |
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The examination paper will contain four questions, of which the best marks of THREE questions will be used to calculate your grade. ~Platforms - Moodle
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Assessment group R1
| Weighting | Study time | Eligible for self-certification | |
|---|---|---|---|
| In-person Examination - Resit | 100% | No | |
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The examination paper will contain four questions, of which the best marks of THREE questions will be used to calculate your grade. ~Platforms - Moodle
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Feedback on assessment
Answers to the formative problems sets will be marked and returned to students in a tutorial or seminar taking place the following week when students will have the opportunity to discuss it.
Solutions and cohort level feedback will be provided for the examination.
Post-requisite modules
If you pass this module, you can take:
- ST409-15 Medical Statistics with Advanced Topics
- ST332-15 Medical Statistics
Anti-requisite modules
If you take this module, you cannot also take:
- ST218-12 Mathematical Statistics Part A
- ST219-12 Mathematical Statistics Part B
- ST226-12 Introduction to Mathematical Statistics
Courses
This module is Optional for:
- Year 3 of UMAA-G1NC Undergraduate Mathematics and Business Studies
- Year 3 of UMAA-GL11 Undergraduate Mathematics and Economics
This module is Option list A for:
- Year 2 of UMAA-G105 Undergraduate Master of Mathematics (with Intercalated Year)
- Year 2 of UMAA-G100 Undergraduate Mathematics (BSc)
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UMAA-G103 Undergraduate Mathematics (MMath)
- Year 2 of G100 Mathematics
- Year 2 of G103 Mathematics (MMath)
- Year 2 of UMAA-G106 Undergraduate Mathematics (MMath) with Study in Europe
- Year 2 of UMAA-G1NC Undergraduate Mathematics and Business Studies
- Year 2 of UMAA-G1N2 Undergraduate Mathematics and Business Studies (with Intercalated Year)
- Year 2 of UMAA-GL11 Undergraduate Mathematics and Economics
- Year 2 of UECA-GL12 Undergraduate Mathematics and Economics (with Intercalated Year)
- Year 2 of UMAA-G101 Undergraduate Mathematics with Intercalated Year
This module is Option list B for:
- Year 2 of UCSA-G4G1 Undergraduate Discrete Mathematics
- Year 2 of UCSA-G4G3 Undergraduate Discrete Mathematics