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Module Title LI Statistics
SchoolMathematics
Department Mathematics
Module Code 06 25671
Module Lead Dr Chris Good
Level Intermediate Level
Credits 20
Semester Full Term
Pre-requisites LC Vectors, Geometry & Linear Algebra - (06 25664) LC Real Analysis & the Calculus (BNatSci) - (06 25764) LC Real Analysis & the Calculus - (06 25660) LC Probability & Statistics - (06 25663)
Co-requisites
Restrictions None
Exclusions
Description Statistics is the study of uncertainty, which arises in all aspects of life. How long will I live for? What is the probability that Birmingham City will win the FA Cup this season? Will it rain today? What is the probability that I will win the lottery this week? Statistical theory and methods are fundamental to our understanding of such uncertainty, and are an increasingly sought after skill. For example, Google uses statistics to improve their search algorithms; medical research uses statistics to design and analyse clinical trials evaluating whether a new cancer treatment is effective; and actuarial and economic teams use statistics to make accurate predictions about future risks and outcomes. This module presents a parallel development of statistical theory and methods, building on the introductory material in Probability & Statistics. Topics covered include classical linear models, with an introduction to the analysis of variance; basic methods for handling discrete data; further work in the theory of probability distributions; and some aspects of the theory of estimation and hypothesis testing. In the computing sessions, a statistical package is used to illustrate the application of statistical methods to the analysis of some typical data sets.
Learning Outcomes By the end of the module students should be able to:
  • demonstrate a basic understanding of the principles of statistical inference;
  • be able to handle simple problems in the distributional calculus;
  • be able to identify standard situations to which statistical models apply;
  • be able to build statistical models and use them for the analysis of data;
  • demonstrate fluency with a standard statistical package.
Assessment 25671-07 : Raw Module Mark : Coursework (100%)
Assessment Methods & Exceptions Assessment: 1.5 hour examination (80%), work done during semester (20%)

Reassessment: best of 1.5 hour resit examination (100%) or 1.5 hour resit examination (80%) and work done during the semester (20%)

Depending on their programme, students will take either one or two of Algebra & Combinatorics 2, Statistics and Differential Equations. Students taking two of these modules will sit a single three hour paper.
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