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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, AnoVa, Time series), supported through the use of the Statistical Software package SPSS.

Aims and Objectives

Module Aims

To select and apply the appropriate statistical methods tools to analyse transport related datasets.

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 Discrete probability distributions (e.g. Binomial, Poisson, etc.) c. Continuous probability distributions (e.g. Exponential, Normal, etc.) 3. Survey Design a. Questionnaire design b. Sample size calculations 4. Hypothesis Testing a. Testing for population means, variances and proportions b. Single and two sample tests c. Testing categorical data d. Non-parametric tests 5. Regression a. Simple linear regression b. Multiple linear regression c. Analysis of Variance 6. Time series a. Exponential smoothing methods b. Autoregressive/moving average methods 7. Statistical Analysis Software

Special Features

Online recorded lectures enable students to cover theory at their own pace. Timetabled sessions used primarily for practical examples and computer workshops. Practical coursework is designed so that students can take different roles within the groups as necessary.

Learning and Teaching

Teaching and learning methods

• Online recorded 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 a statistical analysis software package • 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

Wider reading or practice21
Practical classes and workshops20
Completion of assessment task30
Project supervision6
Preparation for scheduled sessions25
Total study time150

Resources & Reading list

Software requirements. IBM SPSS

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


Assessment Strategy

External Repeat – Assessment includes equivalent (individual) coursework and Semester 2 Exam Internal Repeat – Assessment includes group coursework and Semester 2 Exam


Tutorial sheets


MethodPercentage contribution
Examination  (120 minutes) 70%
Group Survey and Analysis Coursework 30%


MethodPercentage contribution
Examination  (120 minutes) 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

Some groups may choose survey plans that require group members to cover their own very limited travel costs. (travel)

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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