Crime Forecasting Sergeant Tim Podlin Hanover Park Police Department

Why forecast crime? Catch Criminals Officer and Citizen Safety Allocation of Resources Long Term Work Reduction

Why does crime forecasting work? Past behavior is the best predictor of future behavior.

Crime Forecasting Guarantee If you never use crime forecasting, you will never forecast a crime.

Golden Rule of Crime Forecasting NEVER let numbers over rule common sense or sound professional judgment.

Who What When Where Why How “Statistical Elimination”

Gathering Data – Quality Timely Accurate Complete Reliable Valid

Gathering Data – Where Police Reports Dispatch Download (be careful with times)

Gathering Data – What Location Date(s) Time(s) Target Entry Tool/Weapon Suspect Other MO Reference Data

Matrix Format

Matrix Completed

Matrix Incident Relationship / Pattern vs. Series

Matrix Suspect Descriptions

Matrix Final

Date Analysis Mean The sum of all data divided by the number of data points. “Commonly called Average”

Date Analysis Standard Deviation A method of showing how far the data range above and below the mean. “Average Deviation from the Mean”

Date Analysis Confidence Interval Statistically accepted level of chance a data point will be above or below the mean. “Levels of Likely Deviation from the Mean”

Date Analysis Date Comparison

Date Analysis Days Between Hits (DBH)

Date Analysis Mean – Standard Deviation

Date Analysis Confidence Intervals

Date Analysis Confidence Intervals - Rounded

Date Analysis Forecasting Results

Time Analysis Format

Time Analysis Equal Opportunity Method

Time Analysis Equal Opportunity Method with Frequency Distribution

Time Analysis Weighted Method

Time Analysis Time Range Peaks 58% Chance hours 27% Chance hours 90% Chance hours

Complete Analysis Who: M/W, tall, thin, dark coat What: Residential Burglaries Where: Area of “Tree Streets” How: Prying side or rear doors and removing jewelry and USC from bedrooms.

Date and Time Predictions Dates 68% Chance Eves of 2/13-2/18 95% Chance Eves of 2/10-2/20 99% Chance before Eve of 2/24 Times 58% Chance hours 27% Chance hours 90% Chance hours

Day of Week Analysis Determine Days of Week Sun, Sun, Sat, Sat, Fri, Mon, Sun, Mon, Tue, Wed, Thu, Thu, Sun, Mon, Mon, Tue, Fri, and Sun.

Day of Week Analysis Determine Daily and Total Frequency Sun, Sun, Sat, Sat, Fri, Mon, Sun, Mon, Tue, Wed, Thu, Thu, Sun, Mon, Sun, Mon, Mon, Tue, Fri, and Sun.

Day of Week Analysis Determine Percentage per Day

Day of Week Analysis Optional – Graph Results

Spatial Analysis Visual (Common Sense) Grid STAC CrimeSTAT STandard deviation Around Mean center Point (STAMP)

Spatial Analysis (STAMP) Plot Incidents – Determine Longitude and Latitude

Spatial Analysis (STAMP) Calculate Mean Center Point

Spatial Analysis (STAMP) Plot Mean Point

Spatial Analysis (STAMP) Determine Distances from Mean Point

Spatial Analysis (STAMP) Calculate Mean Distance

Spatial Analysis (STAMP) Calculate Standard Deviation

Spatial Analysis (STAMP) Calculate Confidence Intervals

Spatial Analysis (STAMP) Plot Buffers Using Confidence Intervals

Spatial Analysis (STAMP) Shade Buffers for Thematic Map

Spatial Analysis (STAMP) Next Incident and Offender Location

Spatial Analysis (STAMP) CLEAR Arrest Data

Dissemination Intelligence Bulletins Monthly Report Crime Report (Public) Bi-Weekly Staff Meetings Intelligence Newsletters Roll Call Discussions

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Crime Forecasting Sergeant Tim Podlin Hanover Park Police Department