Program Overview
Analysing Transport Data
Overview
This module is designed to equip transport planners and managers with the basic concepts used in statistics and social research methods, and their application in the transport context, illustrated by suitable examples. You will explore, manage, and analyse real-life transport datasets, using MS Excel and specialist software, and learn how to interpret and present your results.
Course Summary
The course consists of a series of online lectures that will be delivered via our BlackBoard virtual learning environment. Our interactive online courses provide real-time lessons with an expert tutor where key course themes will be introduced and discussed.
Learning Outcomes
By the end of the course, students will typically be able to:
- understand different sources of secondary data, their strengths and limitations compared to each other and to collecting primary data
- analyse and present different types of quantitative data, including in Excel and in SPSS
- be able to write reports based on this data analysis, critically commenting on their data analysis
Our Tutor
The course is led by Professor Rachel Aldred, Director of the Active Travel Academy, who has published more than fifty peer-reviewed journal articles using methods including statistical analysis of survey data.
Entry Requirements
You will normally have a first degree in a relevant subject, though this is not essential.
A basic understanding of Excel will be expected. No prior knowledge of SPSS or statistics is assumed. However, we strongly advise you to have some knowledge of GCSE-level maths concepts that will help you with basic data analysis, particularly percentages, fractions, and averages.
Course Structure
On this course, delegates will:
- learn about the secondary data available in transport and the advantages and limitations of this
- review different chart types and when each might be appropriate
- advanced chart making in Excel - pivot tables, combining different data sources
- understand basic SPSS functionality, e.g. using weights, using SPSS to explore and understand a dataset, frequencies and common problems requiring data management
- use cross-tabulation and statistical testing to further explore relationships between variables
- use chi-square tests with categorical data
- learn about analysing continuous or ordinal data (t-tests and Mann-Whitney tests)
- gain knowledge about using regression modelling
- learn about opening datasets from non-SPSS formats
- labelling data, creating missing values, etc. and also cover merging datasets; moving between SPSS and Excel to analyse and present data
- discover ways of making analysis more meaningful by making use of other datasets (here population, travel datasets)
There are two assessed pieces of work; coursework and an in-class test (which is timed and can be sat remotely).
Accreditation
This course is part of University of Westminster's MSc in Transport Planning and Management. Those who successfully complete it can use the credits towards a full MSc, a Postgraduate Diploma or a Postgraduate Certificate.
While the course is credit bearing, please note that successful completion of the module does not allow direct entry onto the associated Masters programme. To be eligible for entry onto the degree, you will still need to meet the necessary requirements and submit an application via Admissions.
Program Outline
Degree Overview:
This module is designed to equip transport planners and managers with the basic concepts used in statistics and social research methods, and their application in the transport context, illustrated by suitable examples.
Objectives:
By the end of the course, students will typically be able to:
- Understand different sources of secondary data, their strengths and limitations compared to each other and to collecting primary data
- Analyse and present different types of quantitative data, including in Excel and in SPSS
- Be able to write reports based on this data analysis, critically commenting on their data analysis
Outline:
Course Structure:
On this course, delegates will:
- Review different chart types and when each might be appropriate
- Advanced chart making in Excel - pivot tables, combining different data sources
- Understand basic SPSS functionality, e.g.
- Use chi-square tests with categorical data
- Gain knowledge about using regression modelling
- Labelling data, creating missing values, etc. and also cover merging datasets; moving between SPSS and Excel to analyse and present data
- Discover ways of making analysis more meaningful by making use of other datasets (here population, travel datasets)
Modules:
The course consists of a series of online lectures that will be delivered via our BlackBoard virtual learning environment. Our interactive online courses provide real-time lessons with an expert tutor where key course themes will be introduced and discussed.
Assessment:
There are two assessed pieces of work; coursework and an in-class test (which is timed and can be sat remotely).
Teaching:
Tutor:
The course is led by Professor Rachel Aldred, Director of the Active Travel Academy, who has published more than fifty peer-reviewed journal articles using methods including statistical analysis of survey data.
Teaching Methods:
The course consists of a series of online lectures that will be delivered via our BlackBoard virtual learning environment. Our interactive online courses provide real-time lessons with an expert tutor where key course themes will be introduced and discussed.
Careers:
Accreditation:
This course is part of University of Westminster's MSc in Transport Planning and Management. Those who successfully complete it can use the credits towards a full MSc, a Postgraduate Diploma or a Postgraduate Certificate.
Other:
Entry Requirements:
You will normally have a first degree in a relevant subject, though this is not essential. A basic understanding of Excel will be expected. No prior knowledge of SPSS or statistics is assumed. However, we strongly advise you to have some knowledge of GCSE-level maths concepts that will help you with basic data analysis, particularly percentages, fractions, and averages.
University of Westminster
Overview:
University of Westminster is a public university located in London, England. It offers a wide range of undergraduate and postgraduate programs across various disciplines. The university is known for its focus on practical learning and its strong connections to the industry.
Services Offered:
Student Life and Campus Experience:
The university has four campuses across London, providing students with a vibrant and diverse campus experience. Students have access to various facilities, including a cinema, gallery spaces, and sports facilities. The university also offers a range of student support services, including career guidance, academic support, and mental health services.
Key Reasons to Study There:
Location:
The university's location in London provides students with access to a wealth of cultural and professional opportunities.Practical Learning:
The university emphasizes practical learning, with many programs incorporating work placements and industry projects.Industry Connections:
The university has strong connections to industry, providing students with opportunities for networking and career development.Diverse Student Body:
The university has a diverse student body, creating a welcoming and inclusive environment.Academic Programs:
The university offers a wide range of academic programs, including:
Undergraduate courses:
A broad range of undergraduate courses in various disciplines, including business, design, creative industries, and liberal arts.Postgraduate courses:
A variety of postgraduate study options, including master's degrees, research degrees, and short courses.Other:
The university has a strong commitment to research and innovation, with a focus on areas such as sustainability, social justice, and digital technologies. It also has a dedicated alumni network, providing support and opportunities for graduates.
Entry Requirements:
You will normally have a first degree in a relevant subject, though this is not essential. A basic understanding of Excel will be expected. No prior knowledge of SPSS or statistics is assumed. However, we strongly advise you to have some knowledge of GCSE-level maths concepts that will help you with basic data analysis, particularly percentages, fractions, and averages.
