How many samples from a drug seizure need to be analyzed?

Area of Science:

• Forensic Science
• Statistical Modeling
• Decision Analysis

Background:

• Aitken's advanced drug sampling decision-making approach offers a strong mathematical foundation but lacks widespread implementation.
• The complexity of existing methodologies hinders their adoption in routine forensic casework.

Purpose of the Study:

• To present a simplified Bayesian approach for drug sampling decisions, building upon Aitken's work.
• To enhance the accessibility and practical implementation of advanced statistical methods in forensic science.
• To encourage the routine application of this methodology by clearly explaining the underlying statistics.

Main Methods:

• Advocating a Bayesian framework inspired by Aitken's methodology.
• Developing a model with reduced mathematical sophistication for broader comprehension.
• Ensuring implementability using readily available software, specifically Microsoft Excel.
• Focusing on clear explanations of statistical concepts for casework practitioners.

Main Results:

• The proposed Bayesian approach is designed for ease of understanding and practical application in drug sampling.
• The methodology is adaptable for use with standard spreadsheet software, facilitating wider adoption.
• Minor modifications to Aitken's original model, concerning prior probability and discrete sample handling, are introduced.

Conclusions:

• The simplified Bayesian approach provides a practical and accessible tool for drug sampling decision-making.
• This methodology, while differing slightly from Aitken's, retains a sound mathematical basis.
• The study promotes the integration of robust statistical techniques into everyday forensic practice.