The Center for Statistics and Applications in Forensic Evidence (CSAFE) has launched a series of new Learning Paths designed to enhance the understanding and application of statistical methods in forensic science.
Learning Paths are curated sets of resources organized around key themes in forensic statistics, allowing learners to interact with various materials at their own pace without the need to follow a sequential order. This approach enables learners to select and engage with content best suited to their educational needs.
CSAFE’s Learning Paths offer flexibility and allow learners to gain a deeper knowledge of the relationship between statistics and forensic analysis, regardless of their prior experience or existing knowledge.
Enrolling in a Learning Path will only enroll learners in the free learning opportunities. A separate enrollment may be needed for any courses with a required fee. All learners who complete a course within these Learning Paths will receive a Certificate of Completion.
Listed below are the three Learning Paths currently available for enrollment. CSAFE Learning will release additional Learning Paths in the future.
For more information and to enroll, visit the CSAFE Learning website.
Principles of Statistics
Enroll Here
This Learning Path introduces concepts such as statistics as a mathematical science and includes the following learning opportunities:
- What do we mean by ‘Statistics’?
5 minutes
This beginner-level Stats Starter helps define the term “statistics” and how it is used. - Stats in the Courtroom
30 minutes
This Foundational Learning opportunity is designed specifically for legal professionals. However, it applies to anyone navigating forensic evidence in court and walks through a variety of statistical concepts as applied in the courtroom. - Statistical Thinking for Forensic Practitioners
8 hours
This short course introduces fundamental concepts from probability and statistics, followed by a detailed investigation of how they apply to assess forensic evidence’s probative value. - Forensic Stats 101
30 hours
This self-paced course addresses the core concepts of probability and statistics and their application to today’s issues in forensic science. An enrollment fee is required for this course.
Probability
Enroll Here
This Learning Path defines fundamental probability concepts and introduces standard mathematical notation used in probability. It includes the following courses:
- Probability
5 minutes
This beginner-level Stats Starter focuses on probability and its application to forensic evidence. - Conditional Probability
5 minutes
This beginner-level Stats Starter focuses on conditional probability and its application to forensic evidence. - Discrete vs Continuous Probability
5 minutes
This beginner-level Stats Starter outlines the similarities and differences between discrete and continuous probabilities. - Bayes’ Rule
5 minutes
This beginner-level Stats Starter introduces Bayes’ Rule or Bayes’ Theorem and how it applies to forensic evidence. - Statistical Thinking for Forensic Practitioners
8 hours
This short course introduces fundamental concepts from probability and statistics, followed by a detailed investigation of how they apply to assess forensic evidence’s probative value. - Forensic Stats 101
30 hours
This self-paced course addresses the core concepts of probability and statistics and their application to today’s issues in forensic science. An enrollment fee is required for this course.
Machine Learning & Statistical Algorithms
Enroll Here
This Learning Path introduces machine learning concepts for forensic science. It includes the following learning opportunities:
- Regression
5 minutes
This beginner-level Stats Starter introduces regression analysis, explaining how to model the relationship between two variables and make predictions in forensic casework. - Classification
5 minutes
This beginner-level Stats Starter discusses the concept of classifying objects based on shared qualities or characteristics and how that applies to forensic evidence. - Algorithms in Forensic Science
30 minutes
This Foundational Learning opportunity presents key components of using algorithms in forensic science. - Machine Learning for Forensic Practitioners
6 hours
This short course provides an overview of machine learning and how it applies to forensic evidence. It introduces the basics of supervised learning algorithms in the context of forensic applications while emphasizing classification trees, random forests and neural networks. The course also addresses some limitations of machine learning algorithms and how to introduce methods for assessing their performance.
