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Module

MAR8174 : Shipping Market Analysis

  • Offered for Year: 2022/23
  • Module Leader(s): Dr Paul Stott
  • Owning School: Engineering
  • Teaching Location: Newcastle City Campus
Semesters
Semester 2 Credit Value: 10
ECTS Credits: 5.0

Aims

1.       To give students an understanding of marine data, sources and uses.
2.       To enable students to objectively judge data quality and to apply discrimination in the use of data.
3.       To enable students to use the correct type of software for different types of analysis.
4.       To enable students to use professional data to undertake analysis relating to the shipping markets.
5.       To enable students to structure and present data in a professional way.
6.       To introduce students to forecasting techniques in the marine field.
7.       To introduce students to the shipping market environment in the City of London.

Outline Of Syllabus

1.       Data, information and information quality.
2.       Databases and their uses (and the limitations of spreadsheets in data analysis).
3.       Data classification.
4.       Accuracy in inputting and checking strategies for analysis.
5.       Specific shipping classification problems, in particular relating to ship types, owner nationality and shipping geography.
6.       Analyzing chartering and fixture data.
7.       Creating shipping indices.
8.       Data presentation and trend analysis.
9.       The power of presentation.
10.       Forecasting techniques.
11.       Correlation and its limitations in data analysis.
12.       Linear regression and specific uses in the shipping sector.

Teaching Methods

Teaching Activities
Category Activity Number Length Student Hours Comment
Scheduled Learning And Teaching ActivitiesLecture82:0016:00Formal lecture series
Guided Independent StudyAssessment preparation and completion120:0020:00Assessment Preparation
Guided Independent StudyDirected research and reading120:0020:00Critical reading and assessment of data reports to be provided to the students.
Scheduled Learning And Teaching ActivitiesSmall group teaching22:004:00Tutorial and discussion of directed reading.
Scheduled Learning And Teaching ActivitiesWorkshops32:006:00Computer labs for practical data analysis exercises
Scheduled Learning And Teaching ActivitiesFieldwork118:0018:00Trip to City of London (3 days). If not possible, then online presentations by companies.
Guided Independent StudyReflective learning activity116:0016:00Review and study lecture materials and notes and study of reading list.
Total100:00
Teaching Rationale And Relationship

Teaching will be based around a series of formal lectures, which will outline what the students need to know about the subject. These will be interspersed with practical sessions in computer lab where students will practice application of the techniques taught in lectures. This will include retrieval and analysis of data under supervision.

Independent study will be based around review of industry reports and the output of professional analysts, which the students will be provided with. The aim is to gain inspiration and ideas from those practicing in the sector and to use this in their own work.

Central to the module is a field trip to the City of London to meet and discuss with analysts, data providers and shipping organizations, to see the use of data in shipping at first hand. The visit will be both informative and motivational.

Should the public health situation require it, the present-in-person teaching activities will be replaced by non- synchronous online sessions. Computer labs will be replaced by preparatory work and synchronous online sessions.

Assessment Methods

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

Other Assessment
Description Semester When Set Percentage Comment
Report2A100Report on a shipping industry sector assigned to the student
Formative Assessments
Description Semester When Set Comment
Computer assessment1MFormative questions will form the basis of the computer sessions.
Assessment Rationale And Relationship

The report provides students with an opportunity to demonstrate communication and analytical skills. It will be assessed to take into account the breadth of sources used, the quality of sources used, processes and software used, quality of illustrations and other data summaries and procedural elements, such as methods to check results and avoid data errors.

Reading Lists

Timetable