Introduction & Explanation

Produce an illustrated report that uses analysis and techniques examined during lectures and practicals to examine the distribution, variation and relationships between at least two variables from the following London data:
UK Census
Air Quality
Roads and Parks
Airbnb
Another dataset for London as agreed with your lecturers
The following specific requirements apply (over and above the official Coursework Submission Requirements):
Students are expected to present and interpret a mix of descriptive statistics, maps, tables (and other visualisations) to provide an evidential base to describe spatial patterns and relationships. Literature should be used to support analysis of the patterns and relationships observed, including a discussion of the possible underlying drivers or causes. Analysis could be at neighbourhood, borough, or city scales.
You are free to develop a topic that speaks to your research and study interests, but some possible topics include: the impact of Airbnb on housing; the relationship between air pollution and deprivation; and the impact of green space and roads on air pollution. The code used to create the supplied data set is available for those who wish to extend it with new data. Feel free to discuss your ideas with the module co-ordinator, especially if you wish to use data not supplied to you.
Your submission should include a balanced assessment of the strengths and limitations of the data (e.g. what is recorded, what is not recorded, what is potentially misleading, etc.), as well as a justification of the methods used in your analysis. The focus of this assessment is a demonstration of judgement and understanding, not mindlessly applying every technique acquired during the term.
The report should be structured using the following sub-headers:
Introduction: to set the context for your analysis, including brief overview of relevant literature;
Data and Methods: briefly describe the origin of the data and the rationale for any
transformation/manipulation of the data;
Results: present an analysis (not simply a summary) of your data using charts, maps and tables (ensure
these are embedded in text);
Discussion: reflect on the possible drivers or causes of the Results, including commenting on the weight of
evidence provided (e.g. the strengths and weaknesses of analyses and data used);
Summary: briefly wrap-up your report with the key conclusions you want the reader to take-away.
Figures and summary tables should be used and be well-presented. Use of wider literature to support discussion and analysis is important. Any code used for analysis should be presented in an Appendix (not in the main body of the report).

https://github.com/kingsgeocomp/geocomputation/blob/master/data/LSOA%20Data.csv.gz – data to be used

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