To cover the parts of statistical distribution theory and statistical inference essential to a full understanding of econometrics and applied statistics. It develops ideas presented in ECON1007 and ECON1011 and applies mathematical techniques from ECON1008.
One of the pre-requisites for MATH2012, MATH3085, ECON2007 and STAT3010
Aims and Objectives
Subject Specific Intellectual and Research Skills
Having successfully completed this module you will be able to:
- apply logical analysis to statistical models
- abstract the essential features of probabilistic models and specify statistical procedures to assess their properties through estimation.
- identify violations of the theoretical assumptions required for statistical inference and describe their consequences and possible remedies.
Knowledge and Understanding
Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:
- properties of statistical models relevant for the analysis of small and large datasets and their distributional properties;
- key concepts and methods from statistical theory relevant for economic data analysis.
The module covers the following topics:
* Distribution Theory: Multivariate distributions: marginal and conditional distributions, multivariate normal. Relations between normal, chi-square, F, t and Cauchy distributions. Asymptotic theory: probability limits and the central limit theorem.
* Inference: Estimation: Cramer-Rao inequality and Rao-Blackwell theorem. Maximum likelihood. Hypothesis testing: Neyman-Pearson Lemma and Likelihood Ratio Tests.
The module uses mathematical techniques (mainly integration, differentiation and limits) to establish relationships between distributions, and the principles of classical statistical inference. A variety of distributions (Binomial, Poissson, negative Binomial, exponential, normal, gamma) can be used to exemplify and illustrate both the distribution theory and the inference.
Learning and Teaching
Teaching and learning methods
Lectures and masterclasses
|Total study time||150|
Resources & Reading list
Mathematical Statistics with Applicationsi.
Assessment in this module is through coursework in form of two problem sets (each worth 5% of the final mark) and an end of module examination (90%). The formative assessment consists of up to 10 exercises to give the students practice in applying techniques while familiarising them with the results. The examination assesses their familiarity with the techniques and results, and the facility with which the candidates can employ and present these. Assessment is the same for internal repeat. Assessment for external repeat and referral is through 100% end of module examination.
This is how we’ll formally assess what you have learned in this module.
This is how we’ll assess you if you don’t meet the criteria to pass this module.
An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.
Repeat type: Internal & External