INTRODUCTION TO FORENSIC STATISTICS

Università degli Studi
"G. d'Annunzio"

Chieti - Pescara

Single discipline educational activity

Course Sheet

Course code:

000207L

Academic Year of enrolment:

2021

Year of supply:

2022/2023

Type of Course:

Characterising

Degree:

Course of 1st Cycle Degree in SOCIOLOGY AND CRIMINOLOGY

Disciplinary Sector:

Statistics

Language:

Italian

Location:

CHIETI

Credits:

Programme Year:

Professor and Collaborators:

FONTANELLA Lara

Cycle:

First semester

Hours of classroom activity:

Individual study hours:

204

Prerequisites:

Basic knowledge of calculus

Objectives

This course introduces students to descriptive and inferential statistical techniques in a forensics context. The focus is the description and analysis of data with an emphasis on statistical methods used in forensic applications. Students are introduced to the statistical capabilities of Excel and the statistical package R.
LEARNING OUTCOMES
1. Understand the nature and consequences of natural variability in forensic data; express a problem in statistical terms.
2. Summarise data graphically and numerically, either manually or using Excel and the statistical language R.
3. Explain basic concepts in probability as they apply to random events and uncertain evidence in a forensic framework.
4. Test hypotheses in the frequentist and Bayesian approaches.
5. Understand how test hypothesis theory is applied in the forensic context.
Making judgements
- To learn the logical and statistical concepts that are indispensable for working independently in the research, selection and processing of data relevant in the forensic context.
Communication skills
- Learn the terminology and statistical techniques to communicate or correctly discuss the results of the analysis of company data relevant in the forensic context.

Contents

The following topics are considered as important parts of the teaching program for the fulfilment of the objectives: descriptive statistics, probability and probability distributions; statistical inference; association between variables; forensic evidence evaluation

Extended Syllabus

Introduction: A short history of statistics in the law
1. Descriptive statistics: Data types, location and dispersion
- Types of data
- Populations and samples
- Distributions and their representation
- Location
- Dispersion
- Hierarchies of variation
2. Probability and probability distributions
- Definitions of probability
- Conditional probability and Bayes Theorem
- Random variables
- Probability distribution (Binomial, Poisson, Normal)
- Empirical probabilities
- Modelled empirical probabilities
- Truly empirical probabilities
3. Statistical Inference
- Paradigms for inference
- Estimation theory
- Point Estimation
- Interval Estimation
- Statistical hypothesis testing
4. Measures of association
- Measures of nominal and ordinal association
- Correlation
- Regression
5. Evidence evaluation
- Forensic Evidences types
- The value of evidence
- Significance testing and evidence evaluation
- Relevance and the formulation of propositions
6. Evaluation of evidence in practice and example
- Which database to use
- Type and geographic factors
- DNA and database selection
- Verbal equivalence of the likelihood ratio
- Some common criticisms of statistical approaches
- Blood group frequencies
- Trouser fibres
- Shoe types
- Airweapon projectiles
- Height description from eyewitness
- DNA
7. Errors in interpretation
Statistically based errors of interpretation (Transposed conditional;
Defender’s fallacy; Numerical conversion error)
Methodological errors of interpretation
Different level error
Defendant’s database fallacy
Independence assumption

Recommended Bibliography

Coursebook:
Simone Di Zio, Antonio Pacinelli, STATISTICA SOCIALE, Mondadori Università, 2015
Further materials (e.g. slides) can be downloaded from https://fad.unich.it/.
Suggested Textbooks
David Lucy, Introduction to Statistics for Forensic Scientist, Wiley, 2005
James Michael Curran, Introduction to Data Analysis with R for Forensic Scientists, CRC Press 2010

Methods of Provision

Conventional

Teaching Methods

Frontal lectures as well as practical exercises with the use of Excel and the software R. Attendance to teaching activities, even if not compulsory, is strongly recommended

Evaluation methods

Verification of learning:

The exam is divided into a 90-minute written test (open questions, to verify the knowledge of the theoretical part of the topics covered in class; question example can be downloaded form the FAD website) and in a 90-minute test on the use of Excel to analyse a given dataset and to solve statistical execercises. In the examination, the two tests have the same importance and both must be overcome for the finalization of the examination. The final grade will be given by the average of the partial scores (in thirtieths) received by the student in the two tests

Contacts/More Information

E-mail: lara.fontanella@unich.it
Students will be received after the lectures
Appointments can be fixed by e-mail

Università degli Studi
"G. d'Annunzio"

Chieti - Pescara

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