In today's era, data have become an integral part of our lives. From everyday activities to critical administrative tasks, vast amounts of sensitive and vital information are generated incessantly. Public safety agencies are no exception to this trend, managing a diverse range of data that includes police crime incident reports, traffic accidents, narcotic overdoses, 911 service calls, and various internal administrative procedures.

Organization-specific software provides a certain level of data management capabilities, but the real power lies in the knowledge and expertise of skilled, trained, and professional public safety analysts. With the right skillset, these analysts can decipher order from disorder, balance demand and workload, and enhance planning and research practices.

This course is designed to equip public safety practitioners with industry-standard best practices in crime analytics, data manipulation, and information visualization. Using Microsoft Office (Word, Excel, and Access) and various free open-source software, attendees will learn to create, publish, and understand statistical implications of data-driven products in the realm of public safety. Hands-on practical exercises and problem-solving scenarios are designed to ensure that learning is immersive and impactful.

This course is for anyone interested in crime analysis. It's not a traditional math class, but it does incorporate essential elements of descriptive statistics, providing a crucial understanding of mathematical principles required for successful data analysis.

Course ​​​​​​​Prerequisites: 

Be comfortable with the basic functions of a computer. 

Familiar with Microsoft Word, Excel, Access.

Understand basic mathematics and associated principles.

Students will need to have access to a laptop (personal or employer issued/assigned). The host agency is unable to provide students with a laptop for use within the course.

Duration: 40 Hours (8 Days)

Method: In Person

Restrictions: Restricted to active Public Safety Agency Employees only who are in a Full Duty status (or Light Duty due to medical). 

Required Disclosures: None

Fee: Course attendance is free

Course Objectives

After successfully completing the course, attendees will be able to know, discuss, use, and execute the following fundamentals:

• Fundamental understanding of types of data
  • Structured
  • Unstructured
  • Data Lake(s)
• How to use basic Microsoft Excel functions to sort/clean/group various forms of data
• How to create effective BOLO's
• Practical exercises designed to explore Tactical, Strategic, and Administrative analysis processes
• Exploration of data ethics within crime analysis
• Create, identify, and understand incident outliers
• Creating charts, graphs, and plots to display data
• Evaluation of the delta between data and information
• Overview of threats analysis, trend forecasting, productivity measures, and predictive policing
• Inferential versus descriptive statistics
• Communications ethics in the age of postmodernity

Required Text

Course Outline

Module 1

Crime analysis basics; the BAD, the AMAZING, the who, what, where, when, why, and how

Types of Analysis (Strategic, Tactical, Administrative), examples of various types and their use

Qualitative v. Quantitative data

National Incident Based Reporting System (NIBRS) - an introduction

BOLO management: the good, the bad, the useless

Module 2

Visualization basics. How to read charts, graphs, plots

How to spot flaws in data visualization

Identification of commonly used statistical visual aids

Picking the best visual aid to assist in data display (bar, graph, plot, Pareto, stem and leaf)

Creating basic charts using simple data

Limitations of visual aid types due to data

Module 3 - Data Basics Part 1

Operator precedence – PEMDAS

Box and Whisker and IQR – part 1 and 2

Level of measurement (using IQR)

Mean, Median, Mode

Module 4 - Data Basics Part 2

Inferential versus Descriptive statistics

Sample data versus and Population data

Proportion, percentage, percentage of change, and ratios

Identification of dependent and independent variables

Creating a Box and Whisker

Module 5 - Putting it all Together

Data Comparisons (rolling, trends, year to date)

Statistical Bias

Data collection schema within PGPD

Data ‘scoring’

Module 6 - PredPol

Trend forecasting, threat analysis

Hotspot crime analysis using mapping basics, evaluation of various published maps

Increase versus decrease within targeted area

Hot-Spot / Trend maps (an overview)

Module 7 - Problem Trees

Problem analysis, trend forecasting, “PAM”

What is a “Problem Tree”?

Statistical concepts within the Daily Trend Report.

The Simpson’s Paradox

Communication Ethics (age of postmodernity)

Final Project Development - Conducting crime analysis.