TxDOT- Building Analytical Capacity

Webinar Series

 

IADLEST, in conjunction with the Texas Department of Transportation (TxDOT), is offering, at no cost, a 5-part analytical webinar training series.

These training segments are designed to build essential skills for those tasked with analyzing data to direct a data-driven operational model. Attendees will have an opportunity to learn and interact with Senior Analytical Specialist, Christopher W. Bruce, who is a subject matter expert and instructor in the field of crime analysis.


The live webinars will start at 1:00 pm CST and will run for one hour over the course of 5 months. In addition to the recordings being available, free hands-on analytical assistance is also available.

Use Data to Save Lives - Build Analytical Capacity (Flyer)

Recordings of the completed webinar can be accessed by using the same Registration links below.

Overview of Building Analytical Capacity Webinar Series (Flyer)

Schedule:

Date 2023/2024 Topic Objectives Flyers Passcode

Registration / Archive

December 19th Obtaining and Cleaning Data for Data-Driven Operations Cleaning Data Flyer n/a View Recording
January 23rd Depicting Crime and Crash Hot Spots: A Survey of Methods Methods Flyer n/a

View Recording

 

February 13th Working with Coordinates Coordinates Flyer n/a

View Recording

 

March 19th Analyzing Crashes for Causal Factors Causal Factors Flyer 351789

Registration

 

April 16th Data-Driven Evaluation Evaluation Flyer 732249

Registration

 


Instructor Bio


Christopher W. Bruce, Assistant Professor, Husson University.
Senior Analytical Specialist and DDACTS Subject Matter Expert

Christopher W. Bruce is a trainer and consultant with expertise in police data systems, crime analysis, and data-driven strategies to reduce crime. He was a crime analyst for 18 years in Massachusetts, where he performed daily tactical, strategic, and administrative analysis for municipal police agencies. For the last 13 years, he has provided consulting and training through a variety of nonprofit associations and government agencies in the areas of data management, crime analysis, traffic analysis, hot spot policing, and problem-oriented policing. In 2019, after almost 20 years of adjunct teaching at various colleges, he became a full-time assistant professor of criminal justice at Husson University in Bangor, Maine.

Christopher served on the board of the International Association of Crime Analysts for nearly 20 years, including periods as vice president of administration (2000-2006), president (2007-2012), and vice president of membership (2016-2019). He was the first editor of the IACA's flagship publication, Exploring Crime Analysis. His other publications include Spatial Statistics in Crime Analysis: Using CrimeStat III (2013), Better Policing with Microsoft Office (2007), and Building a Model Crime Analysis Program (2017).


Course Objectives

Webinar 1:  Obtaining and Cleaning Data for Data-Driven Operations

Tuesday, 19 December 2023, 13:00 CST

This session tackles perhaps the most fundamental question for a crime or crash analyst: Where do I get my data in the first place? We take a look at common police computer-aided dispatch (CAD), records management systems (RMS), and crash databases and look at methods of linking and exporting data from them so it can be properly analyzed with common tools, like Microsoft Access, Microsoft Excel, and ArcGIS Pro. The class also looks at techniques for identifying problems with datasets and cleaning bad data.

Learning objectives

After taking this webinar, students should be able to:

  • Create a plan for regular access to their crash and crime data.
  • Determine if an ODBC connection will work with their systems.
  • Identify the most common data quality issues and analyze their data for those issues.
  • Identify the tools and processes they can use to clean data and automate that cleaning.
  • Access exported or linked datasets from Microsoft Excel, Microsoft Access, and ArcGIS Pro.
  • Download crash data from the CRIS system in a way that maintains its original relational form.

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Webinar 2: Depicting Crime and Crash Hot Spots: A Survey of Methods

Tuesday, 23 January 2024, 13:00 CST

Graduated symbol maps, choropleth maps, density maps, “heat” maps . . . modern GIS systems offer at least a dozen ways to aggregate points and depict hot spots. Which is the right choice? This session surveys the different hot spot methodologies and discusses how they work, what assumptions they make, and which are the right choice for various purposes.

Learning objectives

After taking this webinar, students should be able to:

  • Define and distinguish between different types of hot spot maps.
  • Articulate the strengths and weaknesses of different ways of depicting hot spots.
  • Identify the tools necessary to create different types of maps.
  • Prepare, filter, and query data to support different types of maps.
  • Avoid common problems with color and labeling when preparing maps.

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Webinar 3: Working with Coordinates 

Tuesday, 13 February, 13:00 CST

To create crime and crash hot spots, we must begin with individual points on a map. To get the individual points on the map, we must have coordinates associated with crime and crash records. Some analysts are lucky enough that their CAD and RMS databases assign coordinates automatically—but how accurate are they? Other analysts will have to determine coordinates based on addresses. Whatever your particular situation, this session is all about those coordinates: Where they come from, what they mean, how to interpret them, how to get them if you don’t already have them, how to improve them if you do. Students will learn about projection systems, measuring distances between coordinates, and creating their own libraries to translate addresses to coordinates.

Learning objectives

After taking this webinar, students should be able to:

  • Distinguish between geographic and projected coordinates, and identify both in an unfamiliar dataset.
  • Convert between different types of coordinate systems.
  • Troubleshoot common problems when points do not show up in the correct place on the map.
  • Create and manage a coordinate library to improve the accuracy and completeness of geocoding.

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Webinar 4: Analyzing Crashes for Causal Factors

Tuesday, 19 March 2024, 13:00 CST

Hot spots of crashes tend to be hot spots of traffic—there are more crashes where there are more drivers, and often for reasons that police cannot address. In contrast, maps that show crashes by causal factors—including speed, running red lights and stop signs, and drunk driving—can help identify locations in which crashes are caused by enforceable violations.

Even in regular hot spot analysis, however, consideration of crash causes can help officers determine what activities to enforce in those areas. This session will show how to use a variety of spreadsheet and database tricks to extract the causal factors from crash datasets and adjust maps and other analysis products accordingly. Specific attention is given to the causal factors as they appear in the Texas CRIS dataset.

Learning objectives

After taking this webinar, students should be able to:

  • Manipulate exported CRIS data to prepare causal factors for analysis using tools found in Microsoft Excel and Microsoft Access.
  • Identify causal factors that can be mitigated through proactive enforcement.
  • Articulate existing research findings on the effectiveness of police enforcement on different types of driving behaviors.
  • Create point maps and hot spot maps filtered for specific types of causal factors.
  • Include an analysis of causal factors in hot spot maps and target zone recommendations.

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Webinar 5: Data-Driven Evaluation

Wednesday, 17 April 2024, 13:00 CST

This session covers how to know if we’re successful with a data-driven implementation. Students learn how to identify and set measurable outcome objectives in the first place, and then review a variety of statistical models for analyzing the results of an operation, including methods of measuring change. The session emphasizes the importance of designating control areas and how to compare changes in target zones with those in control zones. Various statistical significance formulas are offered, with calculations performed in Excel.

Learning objectives

After taking this webinar, students should be able to:

  • Create an evaluation plan for a classic, target-zone based DDACTS project.
  • Articulate the basic principles of quantitative research design.
  • Select treatment and control zones.
  • Create “expected” values for treatment zones by both central tendency calculations and regression analysis.
  • Determine and calculate appropriate measures of statistical significance for an evaluation model.

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