Analysis of data For this part of your assignment you will be given a dataset of realistic data measuring the time points of ED processes . Your task will be to have a look at the data (with your...

Analysis of data
For this part of your assignment you will be given a dataset of realistic data measuring the time points of ED processes . Your task will be to have a look at the data (with your understanding of ED processes from your previous reading) and:
•    Extract a data dictionary from the NSW document (will be provided) and add description of any data you construct.
•    Select which data you will be using for your analysis (and justify your choice)
•    Construct data (e.g. duration between “triage” and “seen by clinician”) – justify why you need this data, and describe in detail (in data dictionary) how you are going to construct the data point (formulas, …)
•    Explore the data (e.g. basic statistics, graphs…)
•    Comment on data quality
•    Make your choices on analytic methods (basic stats, process mining [Disco] etc.) and justify your choices (you are asked to use process mining – think about why it is useful – other methods are up to you).
•    Formatting/re-formatting data – what changes need to be done for methods you apply (different input is expected for statistical packages, and different for Disco).

•    Write an analysis plan – to discuss in the class

•    Perform the analysis as you propose it taking into account any comments you may have got.
This part of your assignment will form your project planning, execution and results section. You will re-use the Introduction/Background section from your previous assignment – you can coup/past it, but I suggest you try to improve it.
Group:
•    Data dictionary – this includes a consistent description of data – both copied/adjusted from the NSW data dictionary and description of data the group members constructed
•    Summary of dataset exploration
•    Analysis plan with justification and assigning work to individuals
•    Results of analysis – summary of results/findings produced by individual group members


Individual:
•    Data construction (each member of the group has to do at least one data construction task)
•    Result of exploring the data – each group member will submit result of their exploration of the dataset (what was done, why it was done, what was the result, what do you think about the result)

•    Data quality analysis (what are the problems, can they be fixed? How data quality will influence the validity/trustworthiness of results)
•    Analysis – as assigned by the group in the analysis plan
•    Result of analysis (what you found, what the data tells you – i.e. trends, patterns etc.; NB: this is about facts, not interpretations or opinions)