Statistics for Evidence-Based Policing
This course is aimed at police analysts and those conducting research in Evidence-Based Policing. The course begins with basic descriptive statistics so is suitable for those with little prior knowledge of statistics.
Three days, Monday 16th to Wednesday 18th December 2024
Challenge:
Understanding and using statistics is an important part of the triple Ts (targeting, testing, and tracking) of evidence-based policing. Statistics are important to deciding how to target resources, and for testing the effects of evidence-based policing strategies.
This course trains attendees on how to use and apply statistics essential for evidence-based policing.
Who should attend:
This course is aimed at police analysts and those conducting research in evidence-based policing. The course begins with basic descriptive statistics so is suitable for those with little prior knowledge of statistics.
Objectives:
To learn how to use and apply statistics for evidence-based policing. To learn how to apply the Cambridge Crime Harm Index and understand key principles in statistics such as understanding statistical significance and effect sizes.
Course structure:
Attendees can expect the course to include a variety of teaching modalities including lectures, workshops, and group projects. These will be designed to equip attendees with not only the knowledge but also the practical skills for conducting essential statistics for evidence-based policing.
Pre course: Before the start of the course, we will arrange a webinar to assist people with issues downloading the R package and R studio.
Day 1: For day one all work will take place in Microsoft excel, and the attendees will be introduced to basic principles of essential statistics. This will also include lectures on the practical application and use of statistics in evidence-based policing, workshops on teaching practical skills and statistical techniques and an introduction to the group project. This days’ program will include understanding and use of basic descriptive statistics, data cleaning and limitations, research questions and hypothesis testing. Attendees will also be introduced to using the Cambridge Crime Harm Index (CCHI) to identify felonious few people and power few places.
At the end of day one we will also run a face-to-face session for people who have never used R before. This will be to support them importing a file, opening the dataset, running some basic tests, drawing some basic plots, exporting them and saving a file.
Day 2: For day two attendees will be introduced to using a statistical program – R for more complex analysis. The first session of the day will introduce attendees to probability and statistical significance, before moving on to getting set up in R and learning how to use and interpret statistical tests such as T tests, odd ratios, relative risk, and correlation. The final part of the day will be used to work on the group projects.
Day 3: For day three attendees will start the day learning how to analyse the results of a randomised controlled trial (RCT). This will include understanding and calculating effect sizes, as well as learning survival analysis. After the session on RCT analysis students will also be introduced to multivariate statistics learning some basic regression models. The day will finish with the groups presenting their projects to their peers and the teaching staff.
Post course follow up: After the conclusion of the course, we will run two webinars to support people in their ingoing use of R and help problem solve issues that may have come up.
Faculty:
The Cambridge Centre for Evidence-based policing team teaching this intensive three-day course includes the following instructors:
Dr Eleanor Neyroud PhD, University of Cambridge
Detective Chief Superintendent (retd) Simon Rose MBA, MSt , PhD candidate University of Cambridge
Cost: This three-day course, per person, offers two pricing options:
Residential including two night accommodation bed and breakfast basis in a Cambrige College room adjacent to the teaching facility (£850 + VAT)
Non residential (£620.VAT)
Requirements:
For this course students are required to bring a laptop with access to the internet, and Microsoft excel, and R installed. A basic knowledge of Microsoft excel including basic addition and division formula and pivot tables is useful for day one of the course. Day two and three will require the use of R, a guide on how to install R ahead of attending the course will be sent out to all attendees in advance of the course so that this it will be ready to go on day 2. An online session ahead of attending the course will also be held to troubleshoot any R installation issues.