Transport Data Collection and Analysis
jhh19970724
coursework.docxLearining Outcome
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
task objectives
The objectives are to:
Present summary statistics and analysis for each dataset (and to interpret the statistics),
Describe the advantages and disadvantages of using primary and new generation data sources, and Discuss the policy contribution of each type of data
Two datasets are used:
• Fieldwork Questionnaire data (‘Primary data’)
• Track and Trace example dataset (‘New and emerging data form’). This is a synthetic dataset generated according to a typical format for this type of data.
First Task/1
• Applying statistics: Present summary statistics and analysis for each dataset and interpret the data patterns shown
• choose any two variables from each of the datasets to analyse.
• Calculate and report appropriate statistics for central tendency and spread in the variables you have chosen from the questionnaire dataset and the Track and Trace data set provided.
• Produce an appropriate diagram (for example a histogram, pie chart, bar chart or other) to represent the data for each variable in each dataset.
First Task/2
• Hint: Use information in your statistics lectures to guide you on which statistics and types of diagram to use. There isn’t a single ‘right or wrong’ answer, but some choices are more appropriate to the data than others.
• Using the methods from your statistics lectures, 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.
First Task/3
Dealing with missing data e.g. people who dropped out, missing answers to questions, transcribing errors (to Excel spreadsheet – do some checks?)
• This is realistic and happens with other data
• There are statistical techniques to deal with missing data (but you aren’t expected to apply these in the coursework)
• Different options on how to treat missing data for the coursework – eg could exclude a respondent, treat missing data as separate category.
second task
• Reflecting on data quality: Describe the advantages and disadvantages of each data type i.e the Questionnaire and the Track and Trace data, with respect to a variety of factors (e.g. accuracy, cost, sampling considerations etc)
• what is useful and beneficial about each data type. Could the data be used with other data to create more value? Which other data might be needed to realise the full potential of the data type? What are the main problems with the data? Are there ‘better’ data types that would give similar information?
• Use your own experience from the fieldwork + published work eg journal papers, reports etc.
Third task/1
•Recommending future work: Describe what is shown in the diagrams and analysis you have provided in (2).
•Interpret what you have found in an urban transport policy context. How could each of the two data sets be used in informing decision makers who work with local or regional transport policy?
•Your answer will depend on which variables you have chosen to analyse
Third task/2
Examples of local transport policy that might be appropriate include:
encouraging people to use public transport more, reducing congestion/delays, reducing accidents etc.
You should use references to support your discussion, which may include: journal articles, transport policy documents, formal on-line resources (e.g. government policy statements).
Whilst the data has been collected in the UK, you may refer to transport policy from another country if you wish.
Format
• Submit your coursework as a typed WRITTEN REPORT (that is, with a front cover, contents page, structured sections and a list of references)
• Use proper sentences, don’t rely on bullet points and avoid excessive repetition
• Why this format - Transferable skills: professional communication
• Accuracy matters
• Label diagrams, number equations etc
• Specify units of measurement
Summary
Applying statistics (30%).
Reflecting on data quality (30%)
Recommending future work or improvements (30%)
Presentation of coursework (10%)
Things to check
• Completeness and correctness: have you addressed all requirements?
• Argument quality: pay attention to the discussion parts of the task, have you answered the question?
• Use of evidence in your arguments: have you used references and other evidence?
• Make your answers proportionate to the marks allocated
Reference
• Referencing
– You are expected to draw on 10-20 references to add to your knowledge
– Suitable references can be journal articles, government reports, advice notes. Wikipedia is NOT (usually) a suitable reference
– You should have a References section at the end of your report, using the Leeds Harvard referencing style. Remember the ‘in text’ citations.
– A list of references is not a bibliography
• Word count
– Maximum word count is 2000 (not including figures, tables and references)
– You should not bypass the word count by making extra text into a figure or table. Figures and tables have to be explained in the text!
