Skip to main content

Analysing Crime Data

The Information School’s MSc Data Science programme aims to give students the chance to enhance their analysis skills by working on real data sets.  As part of a recent assignment, students have analysed data sets on crimes which have been reported to the UK police.

One assignment, conducted by Rebecca Thorpe, investigated burglaries in the South Yorkshire region and specifically examined where burglaries occur in the Sheffield area, also looking for associations with other variables.  Using boxplots, time series, line charts and Holt-Winters forecasting, this assignment found that the mean number of monthly burglaries in South Yorkshire was higher in 2012 than in 2011 or 2013.  Using Holt-Winters forecasting, the assignment predicted that burglaries would decrease in South Yorkshire over the next three years.  Focusing upon burglaries in Sheffield, it was found that instances were highly concentrated in the eastern areas of the city and there was some correlation between unemployment and the number of burglaries.

The following diagrams were included in the analysis which was conducted in this assignment.

Box-whisker plot showing total number of burglaries in South Yorkshire per month from 2011 to 2013:



 Burglaries per capita in Sheffield from 2011 to 2013:



A second assignment carried out by Joseph Ellard analysed instances of anti-social behaviour in Cambridgeshire between 2010 and 2014 and also analysed bicycle theft levels.  Analysis was carried out using R, Holt-Winters forecasting, linear regression and ggmap for plotting.  Key findings from this assignment were that crime levels peaked during the summer and that they had decreased between 2010 and 2014.  Analysis also found that warmer weather typically resulted in an increase in crime, while increased rainfall caused fewer instances of crime.  Bicycle thefts were also found to peak during summer months although they were highest during September and October.  Most bicycle thefts were found to occur around Cambridge and Peterborough.

The following diagrams were included in the analysis which was conducted in this assignment.

Anti-social behaviour correlations:


Bicycle thefts in Cambridgeshire:


These excerpts from student assignments highlight the skills and techniques that are taught on the MSc Data Science course which prepare our students for a career in the data science industry.   For more details about the course please visit our website.




Comments

Popular posts from this blog

Raspberry Pi Weather Project now live

A project to create a raspberry pi weather station is currently live in the Information School.  The Sheffield Pi weather station has been created by Romilly Close, undergraduate Aerospace Engineering student at the University of Sheffield.  The project was funded by the Sheffield Undergraduate Research Experience (SURE) scheme and is being supervised by Dr Jo Bates, Paula Goodale and Fred Sonnenwald from the Information School. Information about the Sheffield Pi station and how to create your own can be found on the project website .  You can also see live data from the Sheffield Pi station on Plot.ly , and further information can also be found on the Met Office Weather Observations Website .    This work compliments the School’s existing project entitled ‘The Secret Life of a Weather Datum’ which explores socio-cultural influences on weather data.  This project is funded under the AHRC’s Digital Transformations Big Data call.  It aims to pilot a new approach to im

Our Chemoinformatics Group wins Jason Farradane Award

The Information School's Chemoinformatics Research Group has been awarded the 2012 UKeiG Jason Farradane Award , in recognition of its outstanding 40 year contribution to the information field. The prize is awarded to the three current members of the group,  Professor Val Gillet , Dr John Holliday and Professor Peter Willett . The judges recognised the Group's status as one of the world's leading centres of chemoinformatics research, a major contributor to the field of information science, and an exemplar in raising the profile of the information profession. The School has a long association with the Farradane prize. Its second recipient was long time member of staff Professor Mike Lynch in 1980.

Professor Mike Thelwall gives inaugural lecture

Professor of Data Science Mike Thelwall recently gave his inaugural lecture at the University of Sheffield, entitled  How helpful are AI and bibliometrics for assessing the quality of academic research? The lecture, delivered in the University's Diamond building, was introduced by Head of the Information School Professor Briony Birdi. It covered Mike's research into whether Artificial Intelligence can inform - or replace - expert peer review in the journal article publication process and what this could look like, as well as to what extent bibliometrics and citation statistics can play a role in assessing the quality of a piece of research. Mike also discussed whether tools like ChatGPT can accurately detect research quality. The inaugural lecture was well attended by colleagues from around the University.