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The University of Southampton

CENV6124 Transport Data Analysis and Techniques

Module Overview

This module is designed to provide knowledge of the basic data analysis techniques necessary for understanding and analysing transportation related datasets. This includes identification of suitable analysis methods, applications/calculations of appropriate techniques and models (including with the use of statistical analysis software), interpretation of model and statistical test results and presentation of conclusions. The module covers a full range of data analysis topics from introductory level (Exploratory data analysis, Basic probability, Survey design), through more generally used techniques (Common statistical distributions, Hypothesis testing), to advanced analysis and statistical modelling techniques (Regression, Count data models, and discrete choice analysis), supported through the use of the Statistical Software packages SPSS and BIOGEME.

Aims and Objectives

Learning Outcomes

Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

  • Appropriate methods and techniques for statistical data analysis
  • The statistical characteristics of transportation related datasets
Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

  • Interpret, summarise and report transportation data using appropriate statistical descriptors
  • Identify and apply appropriate analysis methods for transportation data
  • Formulate appropriate statistical models and test statistical hypotheses
  • Evaluate transportation proposals/schemes with statistical rigour
Transferable and Generic Skills

Having successfully completed this module you will be able to:

  • Use creativity and innovation in problem solving
  • Learn and study/research independently
  • Report your work effectively
  • Manage and organise time
Subject Specific Practical Skills

Having successfully completed this module you will be able to:

  • Use statistical software to analyse transportation related datasets


1. Exploratory Data Analysis a. Measures of location and spread b. Visual data presentation 2. Probability and Distributions a. Basic probability theory b. Marginal, joint, and conditional probabilities b. Discrete probability distributions (e.g. Binomial, Poisson, etc.) c. Continuous probability distributions (e.g. Normal, etc.) 3. Survey Design a. Questionnaire design b. Sample size calculations 4. Hypothesis Testing a. Testing for population means, variances and proportions b. Comparing two populations 5. Regression a. Linear regression b. Introduction to estimation techniques (e.g., maximum likelihood estimation) c. Regression for count data 6. Discrete choice modelling a. Binary choice b. Choice with multiple alternatives 7. Statistical Analysis Software

Learning and Teaching

Teaching and learning methods

• Online recorded and live lectures introduce the theory and techniques • Practical classes include worked examples and class exercises to illustrate the techniques • Tutorial sheets (with solutions) enable students to apply the techniques to simple problems • Computer practical sessions introduce statistical software packages • Practical coursework enables students to follow the whole process through from initial question and data collection to formal analysis and report presentation • Tutorial sessions are available throughout the module for any students wanting additional support

Completion of assessment task30
Practical classes and workshops20
Preparation for scheduled sessions25
Project supervision5
Wider reading or practice21
Total study time150

Resources & Reading list

Laboratory space and equipment required. Survey Equipment: High visibility jackets, stopwatches required

Software requirements. 1. IBM SPSS 2. Biogeme (open-source)


Assessment Strategy

External Repeat – Exam Internal Repeat – Assessment includes group coursework and Semester 2 Exam


Tutorial sheets


MethodPercentage contribution
Continuous Assessment 100%


MethodPercentage contribution
Set Task 100%

Repeat Information

Repeat type: Internal & External


Costs associated with this module

Students are responsible for meeting the cost of essential textbooks, and of producing such essays, assignments, laboratory reports and dissertations as are required to fulfil the academic requirements for each programme of study.

In addition to this, students registered for this module typically also have to pay for:

Travel Costs for placements

Please refer to Appendix 4 of the Programme Specification for information regarding additional costs. In addition to the additional costs listed within the Programme Specification, the following additional costs may apply to this module: Students should cover their own very limited travel costs for collecting data.

Please also ensure you read the section on additional costs in the University’s Fees, Charges and Expenses Regulations in the University Calendar available at

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