Difference between revisions of "Group 11 Overview"
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<h1>Motivation</h1> | <h1>Motivation</h1> | ||
| − | + | Based on UN’s Survey of Crime Trends published in 2006, comparisons were made for OECD countries by CIVITAS Institute for the Study of Civil Society. Comparisons are based on six of the most serious crimes: intentional homicide, rape, robbery, assault causing serious bodily harm, burglary and vehicle theft. | |
| − | + | England and Wales have one of the highest crime rates among OECD countries for rape, robbery, assault and burglary. We therefore aim to investigate the spatial variation of crime across different districts in England and Wales, and the relationship between crime and socio-economic characteristics for each district. | |
<h1>Dataset</h1> | <h1>Dataset</h1> | ||
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</ul> | </ul> | ||
| − | <h1>Visualisation/ | + | <h1>Visualisation/Analysis</h1> |
<ul> | <ul> | ||
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<li>Parallel plot</li> | <li>Parallel plot</li> | ||
<li>Time series analysis</li> | <li>Time series analysis</li> | ||
| + | <li>Regression</li> | ||
</ul> | </ul> | ||
| − | <h1>Statistical and | + | <h1>Statistical and Visualisation Tools</h1> |
<ul> | <ul> | ||
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<li>R Shiny</li> | <li>R Shiny</li> | ||
<li>Bootstrap (Update from version 3 in shiny to version 4)</li> | <li>Bootstrap (Update from version 3 in shiny to version 4)</li> | ||
| − | <li>D3</li> | + | <li>D3 (If alternatives in R is not available or not as rich/interactive)</li> |
<li>Angular Js (For single page application routing and databinding)</li> | <li>Angular Js (For single page application routing and databinding)</li> | ||
</ul> | </ul> | ||
Latest revision as of 00:41, 4 December 2017
Motivation
Based on UN’s Survey of Crime Trends published in 2006, comparisons were made for OECD countries by CIVITAS Institute for the Study of Civil Society. Comparisons are based on six of the most serious crimes: intentional homicide, rape, robbery, assault causing serious bodily harm, burglary and vehicle theft.
England and Wales have one of the highest crime rates among OECD countries for rape, robbery, assault and burglary. We therefore aim to investigate the spatial variation of crime across different districts in England and Wales, and the relationship between crime and socio-economic characteristics for each district.
Dataset
Datasets from data.police.uk will be analysed and visualised.
The main datasets of interest are:
- Stop and search dataset
- Crime Data
- Outcome Data
- Shape of police force boundaries
- Shape of neighbourhood boundaries
Secondary dataset includes people, population and community data from Office for National Statistics.
- Health and socialcare
- Housing
- Income and wealth
- Shape of police force boundaries
- Population
Visualisation/Analysis
- Choropleth map (Temporal and Spatial)
- Clustering
- Parallel plot
- Time series analysis
- Regression
Statistical and Visualisation Tools
- R
- R Shiny
- Bootstrap (Update from version 3 in shiny to version 4)
- D3 (If alternatives in R is not available or not as rich/interactive)
- Angular Js (For single page application routing and databinding)
