Transport data analysis

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TRAN5032M Transport Data Collection and Analysis Rail Stream Coursework specifications

Aim The learning outcomes of this coursework are to give you experience in and assess your ability to: • Evaluate the link between research needs and data requirements and collection • Discuss and recommend data collection techniques relevant to transport issues • Apply data acquisition skills • Apply data handling, statistical and analytical skills • Apply data presentation and reporting skills

The task In this coursework, you will make use of two datasets: 1) the questionnaire data collected during the fieldwork and 2) the Network Rail Cancellations and Significant Lateness (CaSL) multi-year data. For each dataset, you are required to:

1. Introduce the dataset

2. Perform statistical analyses

3. Reflect on the data quality and reliability

4. Discuss the results of the analyses and potential policy recommendations

In what follows, more detailed instructions about each task are provided.

1. How was the dataset collected? Is it representative of the relevant population? For the

survey data, you should draw on your own experience in the fieldwork. Complement your

experience as appropriate with information discussed in the lectures and in published

sources.

2. Apply the statistical techniques covered in the module to analyse each dataset and interpret

the data patterns shown. In the case of the survey, examine the questionnaire and choose

which variables to analyse and compare (motivate your choice). Produce the appropriate

graphs and statistics to effectively describe the data. Test whether there are significant

associations between variables, or significant differences between groups. For example, you

can use statistical tests to compare the responses reported by sub-samples of respondents

on the basis of their socio-demographic or other characteristics. The CaSL data is a large

dataset which contains several sheets, each focusing on a different aspect related to failures

and delays. In each sheet, you will find figures for different rail companies different time

periods. Choose one or more company/event and produce appropriate statistics. Consider

comparing different types of events (such as part and full cancellations), different operating

companies, and different years/time periods. There is no single ‘right or wrong’ answer:

make sure you motivate your selection of data, the assumptions you made and discuss the

results.

3. Identify strengths and limitations of the primary datasets collected and the datasets

provided with respect to a variety of factors (e.g. accuracy, cost, completeness, sampling

considerations, etc.). Consider what is useful and beneficial about each of the types of data.

Could the data be used with other data to create more value? What are the main problems

with the data?

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4. Discuss how the analysis performed at point 2. can inform policy design. This will vary

according to the data source analysed. For example, the primary data could be used by the

University or the City Council to design University-level or city-level travel policies, aimed at

staff/students or residents, while the secondary data could be used by the rail operating

companies to design measures to improve their service. Are there further analyses that you

would recommend?

Make sure your coursework constitutes a coherent report, both in the soundness and structure of the arguments, the appropriateness of the analyses and examples, as well as in the presentation of figures/diagrams and text.

Your submission You are required to write a coherent report of 2000 words (excluding tables, calculations, diagrams and appendices). The fieldwork material developed should be submitted with your coursework and placed in the appendix. Marks will be awarded for the correctness of your answer, the relevance of the answer, the use of relevant and recent literature, quality of discussion and critique, your synthesis, and (where appropriate) presentation. Marks will be awarded as follows: 1 Applying statistics (30%). Marks will be given for the correct selection, application and interpretation of statistical analyses on the data. 2 Reflecting on data quality (30%) Marks will be given for correct, in-depth and evidence-based discussion of both the strengths and limitations of different data (sources). 3 Recommending future work or improvements (30%) Marks will be given for an appropriate and innovative application of the interpretations and recommendations from the analyses (point 1 and 2) to design/recommendations of policy, infrastructure, fieldwork etc. 4 Presentation of coursework (10%) Marks will be given for the conciseness and coherence of the argument, the structure of the coursework, presentation of figures/diagrams and total presentation of the report. Timeline The report is due to be submitted by Wednesday 18th December at 2pm.

Submission Normal penalties for late submission and word count apply. If you think that you have a justification for submitting late you should seek our approval beforehand from the Student Education Office. The submission must be made electronically through the VLE. Credits This course work counts for 50% of your mark for this module