Postgraduate

# Modules

### MAS8382 : Time Series Data

• Offered for Year: 2020/21
• Module Leader(s): Dr Sarah Heaps
• Owning School: Mathematics, Statistics and Physics
• Teaching Location: Newcastle City Campus
##### Semesters
 Semester 1 Credit Value: 10 ECTS Credits: 5.0

#### Aims

To gain an understanding of the principles of time series analysis and to develop skills useful for the modelling, analysis and forecasting of time series.

Module Summary

A time series is a set of data ordered with respect to time, such as the sales of a product recorded each month or air temperature at a specific place measured at noon each day. In other branches of statistics, data are often regarded as independent draws from a population. In time series analysis we typically do not regard consecutive observations to be independent, and build special models to represent this dependence. Time series can also exhibit features such as trends and seasonal, or periodic, effects. In this module we look at modelling and inference for time series and how to produce forecasts for future observations.

#### Outline Of Syllabus

Introduction to time series, including trend effects and seasonality. Linear Gaussian processes, stationarity, autocovariance and autocorrelation. Autoregressive (AR), moving average (MA) and mixed (ARMA) models for stationary processes. Likelihood in a simple case such as AR(1). ARIMA processes, differencing, seasonal ARIMA as models for non-stationary processes. The role of sample autocorrelation, partial autocorrelation and correlograms in model choice. Inference for model parameters. Forecasting. Dynamic linear models and the Kalman filter. Use of R for time series analysis.

#### Teaching Methods

Please note that module leaders are reviewing the module teaching and assessment methods for Semester 2 modules, in light of the Covid-19 restrictions. There may also be a few further changes to Semester 1 modules. Final information will be available by the end of August 2020 in for Semester 1 modules and the end of October 2020 for Semester 2 modules.

##### Teaching Activities
Category Activity Number Length Student Hours Comment
Structured Guided LearningLecture materials32:307:30Structured non-synchronous practical
Structured Guided LearningLecture materials91:3013:30Non-synchronous online pre-recorded lectures and set reading
Guided Independent StudyAssessment preparation and completion214:0028:00Formative and summative reports
Scheduled Learning And Teaching ActivitiesPractical31:304:30Present in person, structured synchronous practical
Guided Independent StudyProject work128:3028:30Main project
Scheduled Learning And Teaching ActivitiesDrop-in/surgery31:304:30Virtual office hour, synchronous on line
Guided Independent StudyIndependent study91:3013:30Lecture follow up/background reading
Total100:00
##### Teaching Rationale And Relationship

Pre-recorded lectures and set reading are used for the delivery of theory and explanation of methods, illustrated with examples. Practicals are used both for solution of problems and work requiring extensive computation and to give insight into the ideas/methods studied. There is one present-in-person practical session per week to ensure rapid feedback on understanding, and further non-synchronous practical sessions to provide additional practice and experience. Scheduled on-line contact time provides opportunity to ask questions and receive immediate feedback. Students unable to attend PiP will be able to complete the practical work at home and will be able to receive immediate feedback through the scheduled on-line contact time.
Alternatives will be offered to students unable to be present-in-person due to the prevailing C-19 circumstances.
Studentâ€™s should consult their individual timetable for up-to-date delivery information.

#### Assessment Methods

Please note that module leaders are reviewing the module teaching and assessment methods for Semester 2 modules, in light of the Covid-19 restrictions. There may also be a few further changes to Semester 1 modules. Final information will be available by the end of August 2020 in for Semester 1 modules and the end of October 2020 for Semester 2 modules.

The format of resits will be determined by the Board of Examiners

##### Other Assessment
Description Semester When Set Percentage Comment
Practical/lab report1M40Individual report
Report1M60Main module project
##### Zero Weighted Pass/Fail Assessments
Description When Set Comment
Oral PresentationMA 3 min video articulating the main findings of one aspect of the report
##### Formative Assessments
Description Semester When Set Comment
Practical/lab report1MA compulsory report allowing students to develop problem solving techniques, to practise the methods learnt and to assess progress.
##### Assessment Rationale And Relationship

A compulsory formative practical report allows the students to develop their problem solving techniques, to practise the methods learnt in the module, to assess their progress and to receive feedback, before the summative assessments.

The oral presentation encourages students to focus on interpretation of statistical results, builds their skills in the presentation of statistical concepts, and provides opportunity for feedback.

In a foundational subject like the Mathematical Sciences, there is research evidence to suggest that continual consolidation of learning is essential and the fewer pieces of assessment there are, the more difficult it is to facilitate this. On this module, it is particularly important that the material on the earlier summative assessment is fully consolidated, before the later assessment is attempted.