Introductory description
This module runs in Term 2 and is available for students on a course where it is a listed option and as an Unusual Option to students who have completed the prerequisite modules.
Prerequisites:
Statistics Students: ST218 Mathematical Statistics A AND ST219 Mathematical Statistics B
NonStatistics Students: ST220 Introduction to Mathematical Statistics
Module web page
Module aims
This course is concerned with the theory and practice of shortterm forecasting, using both data and subjective information. The course focuses on Dynamic Linear Models (DLM). DLM's are a class of Bayesian Forecasting Models which generalise linear regression models and static statistical linear models. Some extensions to nonlinear dynamic models are also considered.
Forecasting is a vital prerequisite to decision making. This course offers a very powerful fundamental probabilistic approach to forecasting, controlling and learning about uncertain commercial, financial, economic, production, environmental and medical dynamic systems. The theory will be illustrated by real examples from industry, marketing, finance, government, agriculture etc.
A familiarity with the material in this module will be very useful to all students planning a career involving a component of industrial, business or government statistics.
Outline syllabus
This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.
 State space modelling
 Bayesian updating of beliefs
 Specifying Dynamic Linear Models
 Updating Dynamic Linear Models, forecasting
 Building Dynamic Linear Models, accommodating external information
 ARIMA models, stationarity
Learning outcomes
By the end of the module, students should be able to:
 Acquire an appreciation of forecasting recurrences and be able to calculate these for special cases.
 Know how to select an appropriate model in simple scenarios.
 Have an acquaintance with the most useful models in the class of DLMs for statistical forecasting in a business environment.
 Know how to intervene in these processes in the light of external information.
 Have an appreciation of diagnostic methods and estimation techniques for this model class.
Indicative reading list
View reading list on Talis Aspire
Subject specific skills
TBC
Transferable skills
TBC
Study time
Type 
Required 
Optional 
Lectures 
30 sessions of 1 hour (20%)

2 sessions of 1 hour

Private study 
120 hours (80%)


Total 
150 hours 

Private study description
Weekly revision of lecture notes and materials, wider reading, practice exercises and preparing for examination.
Costs
No further costs have been identified for this module.
You must pass all assessment components to pass the module.
Students can register for this module without taking any assessment.
Assessment group B3

Weighting 
Study time 
Inperson Examination

100%


The examination paper will contain four questions, of which the best marks of THREE questions will be used to calculate your grade.
 Answerbook Pink (12 page)
 Students may use a calculator

Assessment group R2

Weighting 
Study time 
Inperson Examination  Resit

100%


The examination paper will contain four questions, of which the best marks of THREE questions will be used to calculate your grade.
 Answerbook Pink (12 page)
 Students may use a calculator
 Cambridge Statistical Tables (blue)

Feedback on assessment
Solutions and cohort level feedback will be provided for the examination.
Past exam papers for ST337
Antirequisite modules
If you take this module, you cannot also take:

ST40515 Bayesian Forecasting and Intervention with Advanced Topics
Courses
This module is Optional for:

UCSAG4G1 Undergraduate Discrete Mathematics

Year 3 of
G4G1 Discrete Mathematics

Year 3 of
G4G1 Discrete Mathematics

Year 3 of
UCSAG4G3 Undergraduate Discrete Mathematics

Year 4 of
UCSAG4G4 Undergraduate Discrete Mathematics (with Intercalated Year)

Year 4 of
UCSAG4G2 Undergraduate Discrete Mathematics with Intercalated Year

USTAG300 Undergraduate Master of Mathematics,Operational Research,Statistics and Economics

Year 3 of
G300 Mathematics, Operational Research, Statistics and Economics

Year 4 of
G300 Mathematics, Operational Research, Statistics and Economics
This module is Option list A for:

Year 4 of
USTAG300 Undergraduate Master of Mathematics,Operational Research,Statistics and Economics

Year 5 of
USTAG301 Undergraduate Master of Mathematics,Operational Research,Statistics and Economics (with Intercalated

USTAG1G3 Undergraduate Mathematics and Statistics (BSc MMathStat)

Year 3 of
G1G3 Mathematics and Statistics (BSc MMathStat)

Year 4 of
G1G3 Mathematics and Statistics (BSc MMathStat)

USTAG1G4 Undergraduate Mathematics and Statistics (BSc MMathStat) (with Intercalated Year)

Year 4 of
G1G4 Mathematics and Statistics (BSc MMathStat) (with Intercalated Year)

Year 5 of
G1G4 Mathematics and Statistics (BSc MMathStat) (with Intercalated Year)

USTAGG14 Undergraduate Mathematics and Statistics (BSc)

Year 3 of
GG14 Mathematics and Statistics

Year 3 of
GG14 Mathematics and Statistics

Year 4 of
USTAGG17 Undergraduate Mathematics and Statistics (with Intercalated Year)

USTAY602 Undergraduate Mathematics,Operational Research,Statistics and Economics

Year 3 of
Y602 Mathematics,Operational Research,Stats,Economics

Year 3 of
Y602 Mathematics,Operational Research,Stats,Economics

Year 4 of
USTAY603 Undergraduate Mathematics,Operational Research,Statistics,Economics (with Intercalated Year)
This module is Option list B for:

USTAG302 Undergraduate Data Science

Year 3 of
G302 Data Science

Year 3 of
G302 Data Science

Year 3 of
USTAG304 Undergraduate Data Science (MSci)

Year 4 of
USTAG303 Undergraduate Data Science (with Intercalated Year)

UMAAG105 Undergraduate Master of Mathematics (with Intercalated Year)

Year 4 of
G105 Mathematics (MMath) with Intercalated Year

Year 5 of
G105 Mathematics (MMath) with Intercalated Year

Year 3 of
USTAG300 Undergraduate Master of Mathematics,Operational Research,Statistics and Economics

USTAG301 Undergraduate Master of Mathematics,Operational Research,Statistics and Economics (with Intercalated

Year 3 of
G30E Master of Maths, Op.Res, Stats & Economics (Actuarial and Financial Mathematics Stream) Int

Year 4 of
G30E Master of Maths, Op.Res, Stats & Economics (Actuarial and Financial Mathematics Stream) Int

UMAAG100 Undergraduate Mathematics (BSc)

Year 3 of
G100 Mathematics

Year 3 of
G100 Mathematics

Year 3 of
G100 Mathematics

UMAAG103 Undergraduate Mathematics (MMath)

Year 3 of
G100 Mathematics

Year 3 of
G103 Mathematics (MMath)

Year 3 of
G103 Mathematics (MMath)

Year 4 of
G103 Mathematics (MMath)

Year 4 of
G103 Mathematics (MMath)

UMAAG106 Undergraduate Mathematics (MMath) with Study in Europe

Year 3 of
G106 Mathematics (MMath) with Study in Europe

Year 4 of
G106 Mathematics (MMath) with Study in Europe

Year 4 of
UMAAG101 Undergraduate Mathematics with Intercalated Year
This module is Option list F for:

Year 3 of
USTAG300 Undergraduate Master of Mathematics,Operational Research,Statistics and Economics

USTAG301 Undergraduate Master of Mathematics,Operational Research,Statistics and Economics (with Intercalated

Year 3 of
G30H Master of Maths, Op.Res, Stats & Economics (Statistics with Mathematics Stream)

Year 4 of
G30H Master of Maths, Op.Res, Stats & Economics (Statistics with Mathematics Stream)