## Quantitative Methods

### Module aims

• To introduce students to key concepts underpinning quantitative techniques used in transport analysis.
• To show how fundamental concepts of probability can be used to represent travel behaviour and how statistical techniques can be used to summarise and analyse travel related data.

### Learning outcomes

On successfully completing this course unit, students will be able to:

• Understand concepts and techniques for the acquisition, processing, description and presentation of quantitative information, including elementary descriptive and inferential statistics.
• Have a foundation in essential quantitative methods that will be required in other core course units and for study project research and report writing.

### Module syllabus

Sources and examples of transport data; survey methods; presentation and interpretation of data; systematic and non-systematic variations in data, models for systematic variation; approaches to decision making and design; optimisation; probability and random processes; sampling; standard probability distributions; estimation of population parameters; hypothesis testing; categorical models; continuous models; model specification and fitting; model calibration and validation; students will be introduced to relevant software packages.

 No. Topic Staff 01 Presentation and interpretation of data DJG 02 Presentation and interpretation of data DJG Tutorial Data editing and descriptive statistics DJG 03 Sources and examples of transport data, survey methods HT 04 Sources and examples of transport data, survey methods HT Tutorial Workshop on survey methods HT 05 Probability and random processes BGH 06 Probability and random processes BGH Tutorial Exercise on probability BGH 07 Standard probability distributions BGH 08 Standard probability distributions BGH Tutorial Workshop on distributions BGH 09 Sampling and estimation BGH 10 Sampling and estimation BGH Tutorial Theoretical and empirical distributions BGH 11 Hypothesis testing: philosophy, simple examples BGH 12 Hypothesis testing: philosophy, simple examples BGH Tutorial Hypothesis testing workshop BGH 13 Decision making and optimisation BGH 14 Decision making and optimisation BGH Tutorial Optimisation workshop BGH 15 Introduction to linear regression DJG 16 Introduction to linear regression DJG Tutorial Introduction to regression with Excel and SPSS DJG 17 Further regression analysis DJG 18 Further regression analysis DJG Tutorial Further regression analysis workshop DJG

### Teaching methods

There will be 18 hours of lectures delivered over 9 weeks in two hour blocks. Tutorials are scheduled after each two-hour lecture to review and practice problems and to set coursework. If you have questions about specific problems, please be prepared to ask them at the tutorial.

### Assessments

 Assignment Title Date Set Coursework Weighting Set by Probability Coursework Lectures 11-12 50% BGH Regression Coursework Lectures 17-18 50% DJG

### Core

• #### A basic course in statistics

Clarke, G. M. (Geoffrey Mallin).

5th ed., Chichester : Wiley

• #### Probability and statistical inference

Hogg, Robert V.

9th ed., Upper Saddle River, N.J : Pearson Education