Finding outliers in proportions
Here I show a simple technique, using a funnel chart, to identify when a proportion is an outlier relative to the number of observations. I use a simulated data example in python to showcase the technique.
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- Finding outliers in proportions
- Denver's STAR Program and Disorder Crime Reductions
- Some extensions to the WDD statistic
- Why crime analysts should learn SQL
- Crime Analysts make too many BOLOs
- Junk science: Detecting deception in 911 homicide calls
- A market for empirical research
- How to use python to query your RMS
- Applications of AI in policing
- Aoristic Analysis of Uncertain Crime Times in Python
- Wake Libertarian Talk on LPRs
- Crime Analysis with Python Book Released
- Simple rule to identify if rare crimes have spiked
- Geocoding Crime Data Locally
- Building Custom Software
- Compstat and Counterfactuals
- Using surveys to measure attitudes towards police
- AI regulation in policing
- Dashboard Advice
- What are Early Intervention Systems
- How to Evaluate Pred Policing Software
- Custom Training Services
- Early Release of Data Science for Crime Analysis with Python Book
- NLP applications in crime analysis
- Tech recruiting PhDs
- PDs should share crime data
- Using data to establish reasonableness in premises liability cases
- A Primer on SNA for Crime Analysts
- Additional Services CRIME De-Coder offers
- Dashboards should be up-to-date
- Don't use percent change for crime data, use this stat instead
- $$$ Million Dollar HotSpots $$$
- What distinguishes CRIME De-Coder from other firms