Teaching Responsibility
LJMU Schools involved in Delivery:
Computer Science and Mathematics
Learning Methods
Lecture
Practical
Tutorial
Module Offerings
5103STATS-JAN-CTY
Aims
To extend the student’s knowledge of, and experience in, the use of probability models.
To deepen the student’s understanding of important topics in inference.
To introduce the students to the use of simulation models.
To enable the student to familiarise themselves with risk techniques through which they can assist decision makers in making informed decisions in the face of uncertainty.
Learning Outcomes
1.
Compare estimators on the basis of their important properties.
2.
Calculate sample-sizes on the basis of power considerations.
3.
Apply simulation - based techniques in more complex situations.
4.
Identify sources of uncertainty.
5.
Apply concepts of robustness, flexibility and sensitivity analysis to a number of application areas using statistical software.
Module Content
Outline Syllabus:Review of some aspects of the theory of probability, Bayes’ Theorem.
Discrete probability distributions: binomial, Poisson, hypergeometric, geometric.
Continuous probability distributions: normal, exponential, lognormal, X2, T and F.
Introductory power and sample size calculations.
The bootstrap.
Inference for linear combinations of normally distributed random variables.
An introduction to the use of ranking methods.
Goodness of fit tests, contingency tables.
Uncertainty in specification of problems, data sources, model, forecasts, objectives.
Robustness, flexibility, sensitivity. Decision making tools. Paper analysis. Decision Trees. Bayesian Analysis. Project Management.
Module Overview:
This module will extend your knowledge of the use of probability models to introduce the use of simulation models in order to enable you to familiarise yourself with risk techniques through which can assist decision makers in making informed decisions in the face of uncertainty.
This module will extend your knowledge of the use of probability models to introduce the use of simulation models in order to enable you to familiarise yourself with risk techniques through which can assist decision makers in making informed decisions in the face of uncertainty.
Additional Information:In this module the basic tools of Risk – Analysis, Management and Assessment, are introduced. In particular, we discuss
a number of probability distributions along with certain aspects of statistical inference.
Finally, we study simulation techniques and their development on a computer.