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Students
Tuition Fee
GBP 2,936
Per course
Start Date
2026-01-19
Medium of studying
On campus
Duration
11 weeks
Program Facts
Program Details
Degree
Courses
Major
Data Analysis | Mathematics | Statistics
Area of study
Mathematics and Statistics
Education type
On campus
Course Language
English
Tuition Fee
Average International Tuition Fee
GBP 2,936
Intakes
Program start dateApplication deadline
2026-01-19-
About Program

Program Overview


Time Series Analysis (7CCM344BM)

Course Overview

This module introduces the analysis of time series, i.e. a series of observations observed at discrete points in time. The module considers both theoretical and applied aspects of time series. Modern techniques such as the Kalman filter will be explained. In addition, links to computational statistics will be made. For example, the Gibbs sampler will be analysed as a Markov model. Issues of predictability and analysis of goodness-of-fit will be highlighted.


Course Details

  • Duration: 11 weeks
  • Credit level: 7
  • Credit value: 15
  • Fees:
    • Full Price: £1,125.00
    • International: £2,936.00

Entry Requirements

To enrol on this module, you must meet the following module-specific requirements:


  • A 2:1 honours degree (or above) in Mathematics, Statistics or other mathematics-based subject, including modules covering probability theory, statistical inference and linear regression models
  • A 2:2 honours degree in Mathematics, Statistics or other mathematics-based subject, including modules covering probability theory, statistical inference and linear regression models, supported by a CV and employer reference letter demonstrating a minimum of three years relevant professional experience.

Plus the additional standard entry requirements:


  • A CV and personal statement outlining reasons for study
  • English language at Band D (IELTS 6.5 overall with a minimum of 6.0 in reading/writing and 6.0 in listening/speaking).

Assessment

You will be assessed via coursework and examination, as follows:


  • Coursework = 20%
  • Examination = 80%

Learning Outcomes

At the end of this module you will be able to:


  • Describe the structure and the purpose of time series models and assess the suitability of different models in reference to the theory of time series analysis
  • Analyse and appraise the properties of particular models, e.g. ARMA(1,1) models
  • Demonstrate expertise in the application of statistical software to analyse time series data and critically assess the fit
  • Carry out a statistical analysis of time series data and interpret the results.

Course Features

Lectures will cover both the theoretical aspects and the practical applications using statistical software. You will be given problem sheets with both analytical exercises and numerical problems to be solved using the statistical software. You will be able to measure your progress using these exercises and have the opportunity to receive feedback in the tutorials. Full solutions will be provided subsequent to the tutorial (including any code).


The coursework will comprise of an individual data analysis project to be carried out using the tools covered in the module lectures and tutorials. Problems sets will prepare you in using the necessary statistical software and in the presentation of the results.


Who Will I Be Taught By

Professor Michael Pitt


Professor in Statistics


Offered By

Faculty of Natural, Mathematical & Engineering Sciences Department of Mathematics


Key Information

  • Course code: 7CCM344BM
  • Delivery mode: In person
  • Application deadline: 01 December 2025
  • Places: Course closed
  • Dates: 19 January 2026 - 01 May 2026
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