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Single discipline educational activity
Course Sheet Academic Year of enrolment:
Hours of classroom activity:
Prerequisites:
Basic knowledge of calculus.
Objectives
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
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
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