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MA20227: Statistics 2B

Follow this link for further information on academic years Academic Year: 2016/7
Further information on owning departmentsOwning Department/School: Department of Mathematical Sciences
Further information on credits Credits: 6      [equivalent to 12 CATS credits]
Further information on notional study hours Notional Study Hours: 120
Further information on unit levels Level: Intermediate (FHEQ level 5)
Further information on teaching periods Period:
Semester 2
Further information on unit assessment Assessment Summary: CW 25%, EX 75%
Further information on unit assessment Assessment Detail:
  • Coursework (CW 25%)
  • Examination (EX 75%)
Further information on supplementary assessment Supplementary Assessment:
MA20227 Mandatory extra work (where allowed by programme regulations)
Further information on requisites Requisites: Before taking this module you must take MA20226
Further information on descriptions Description: Aims:
Introduce the principles of building and analysing linear models, introduce the principles of statistical modelling.

Learning Outcomes:
After taking this unit, students should be able to:
* Carry out analyses using linear Gaussian models, including regression and ANOVA.
* Manipulate joint, marginal and conditional distributions.
* Represent normal linear models in vector and matrix form.

Skills:
Numeracy T/F A
Problem Solving T/F A
Computing Skills T/F A
Written and Spoken Communication F (in tutorials).

Content:
Regression: Estimation of model parameters, tests and confidence intervals, prediction intervals, polynomial and multiple regression. One-way analysis of variance (ANOVA): One-way classification model. Main effects and interaction, parameter estimation, F- and t-tests. Use of residuals to check model assumptions: probability plots, identification and treatment of outliers.
Multivariate distributions: expectation and variance-covariance matrix of a random vector; statement of properties of the bivariate and multivariate normal distribution. The general linear model: Vector and matrix notation. examples of the design matrix for regression and ANOVA, least squares estimation, internally and externally studentised residuals.
Further information on programme availabilityProgramme availability:

MA20227 is Compulsory on the following programmes:

Department of Mathematical Sciences
  • USMA-AFB01 : BSc(Hons) Mathematics and Statistics (Year 2)
  • USMA-AAB02 : BSc(Hons) Mathematics and Statistics with Study year abroad (Year 2)
  • USMA-AKB02 : BSc(Hons) Mathematics and Statistics with Year long work placement (Year 2)
  • USMA-AFB05 : BSc(Hons) Statistics (Year 2)
  • USMA-AAB06 : BSc(Hons) Statistics with Study year abroad (Year 2)
  • USMA-AKB06 : BSc(Hons) Statistics with Year long work placement (Year 2)

MA20227 is Optional on the following programmes:

Department of Economics Department of Mathematical Sciences

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