# Modules

### CEG8423 : Transport Research Methods

• Offered for Year: 2019/20
• Module Leader(s): Dr Neil Thorpe
• Other Staff: Dr Graeme Hill
• Owning School: Engineering
• Teaching Location: Newcastle City Campus
##### Semesters
 Semester 2 Credit Value: 10 ECTS Credits: 5.0

#### Aims

The aims of this module are:
1. To provide an understanding of statistical, and/or other numerical methods, appropriate to
research in a range of science and engineering disciplines
2. To enable students to develop a working knowledge of relevant software.
3. To introduce the key skills needed by researchers in order to prepare for, and successfully undertake, a significant piece of research.
4. To expose students to current transport research projects and initiatives both within and outside the University, as examples of how to manage, conduct and present the findings from research.

#### Outline Of Syllabus

Introduction and basics of statistics; populations and samples; parameters, statistic and cases; histograms and frequency distributions; different measurement scales; arithmetic and harmonic means, medians and modes; percentiles, quartiles and ranges; the normal distribution; skewness and kurtosis; measures of dispersion (variance, standard deviation and mean deviation) and outliers; the Box Plot; sampling and distributions; elementary sampling theory; methods of sampling; samples and populations; standard errors; levels of confidence; degrees of freedom; distributions - Student t; chi Squared; testing for differences between groups; examples of Chi square test; hypothesis testing; structure of a test; probability threshold; test statistic and p values; Z scores and z test; one and two-tailed tests; Type 1 and Type II errors; one sample t-test; correlation; scatterplots; positive and negative relationships; covariance; standardisation; the R squared value; interpretation of R squared; regression; fitting a straight line; goodness of fit; method of least squares; errors and residuals; R squared values; using regression models for prediction; Elementary Probability Theory; data reduction techniques – factor analysis and cluster analysis; principles of time series analysis; setting research objectives and conducting a literature review; survey design; risk management; research ethics; basics of transport statistics in transport modelling.

#### Teaching Methods

##### Teaching Activities
Category Activity Number Length Student Hours Comment
Guided Independent StudyAssessment preparation and completion123:3023:30Includes background reading and reading lecture notes for a full understanding of material.
Scheduled Learning And Teaching ActivitiesLecture44:0016:00N/A
Guided Independent StudyAssessment preparation and completion190:309:30Revision for exam.
Guided Independent StudyAssessment preparation and completion12:002:00Online exam.
Scheduled Learning And Teaching ActivitiesLecture13:003:00N/A
Guided Independent StudyAssessment preparation and completion114:0014:00Project brief preparation and completion.
Scheduled Learning And Teaching ActivitiesPractical43:0012:00Computer-based exercises.
Scheduled Learning And Teaching ActivitiesSmall group teaching201:0020:00Research seminars.
Total100:00
##### Teaching Rationale And Relationship

Formal lectures are used to disseminate knowledge regarding statistical and other numerical techniques, and the technical knowledge required for preparing for and undertaking a significant piece of research at postgraduate level. Research seminars are designed to expose students to different aspects of current transport research as well as different approaches to research design, methodology and methods for communicating and presenting information to a critical audience. Students are encouraged to undertake practical-based computer exercises to reinforce numerical skills.

#### Assessment Methods

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

##### Exams
Description Length Semester When Set Percentage Comment
PC Examination1202A60Unseen PC based examination
##### Other Assessment
Description Semester When Set Percentage Comment
Research proposal2A40Detailed report of proposed research for the compulsory CEG8499 module (approx 2000 words inc. relevant tables, figures and charts).
##### Assessment Rationale And Relationship

This module is assessed by written examination and coursework. This format allows a student’s knowledge and understanding of numerical and research methods to be quantified. Analytical Methods for Transport Research is a core module providing the students with the fundamentals of statistical analysis procedures essential in ensuring academic rigour is preserved in the design and execution of surveys; quality in the data collection procedures and in the statistical analysis of the data collected in the MSc dissertations. An extra 30 minutes which is included in the 2 hour exam is necessary to enable the satisfactory assessment of students' knowledge of key statistical concepts and processes which are fundamental to the transport discipline. In order to create an exam that can explore in sufficient depth the understanding of quantitative methods, it is essential to set questions requiring numerical analysis. These require the use of calculators and statistical tables. However, in order to test a student's breadth and depth of statistical knowledge, rather than simply the use of the calculator, students are required to perform certain calculations manually. Extra time of 30 minutes which is included in the 2 hour exam is therefore necessary to allow for these manual calculations to take place.

The research project brief should contain descriptions of the key elements of a research project (including the rationale for the project; aims, objectives and methodologies; and a project management plan). This document, developed in consultation with the dissertation supervisor, will form the basis for tackling the Masters level dissertation undertaken elsewhere in the degree programme. The project brief helps the students to understand research methods and how they might be applied in their forthcoming dissertation.