Transport Data Analysis and Techniques

Learning Outcomes

Subject Specific Practical Skills

Having successfully completed this module you will be able to:

• Use statistical software to analyse transportation related datasets

Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

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

Knowledge and Understanding

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

• The statistical characteristics of transportation related datasets
• Appropriate methods and techniques for statistical data analysis

Transferable and Generic Skills

Having successfully completed this module you will be able to:

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

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

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

Resources & Reading list

General Resources

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

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

Assessment strategy

Internal & External Repeat – Coursework

Formative

This is how we’ll give you feedback as you are learning. It is not a formal test or exam.

Summative

This is how we’ll formally assess what you have learned in this module.

Referral

This is how we’ll assess you if you don’t meet the criteria to pass this module.

Repeat Information

Repeat type: Internal & External