Buch, Englisch, 368 Seiten, Format (B × H): 170 mm x 244 mm, Gewicht: 608 g
Buch, Englisch, 368 Seiten, Format (B × H): 170 mm x 244 mm, Gewicht: 608 g
ISBN: 978-0-470-74253-2
Verlag: Wiley
This text is an accessible, student-friendly introduction to the wide range of mathematical and statistical tools needed by the forensic scientist in the analysis, interpretation and presentation of experimental measurements.
From a basis of high school mathematics, the book develops essential quantitative analysis techniques within the context of a broad range of forensic applications. This clearly structured text focuses on developing core mathematical skills together with an understanding of the calculations associated with the analysis of experimental work, including an emphasis on the use of graphs and the evaluation of uncertainties. Through a broad study of probability and statistics, the reader is led ultimately to the use of Bayesian approaches to the evaluation of evidence within the court. In every section, forensic applications such as ballistics trajectories, post-mortem cooling, aspects of forensic pharmacokinetics, the matching of glass evidence, the formation of bloodstains and the interpretation of DNA profiles are discussed and examples of calculations are worked through. In every chapter there are numerous self-assessment problems to aid student learning.
Its broad scope and forensically focused coverage make this book an essential text for students embarking on any degree course in forensic science or forensic analysis, as well as an invaluable reference for post-graduate students and forensic professionals.
Key features:
- Offers a unique mix of mathematics and statistics topics, specifically tailored to a forensic science undergraduate degree.
- All topics illustrated with examples from the forensic science discipline.
- Written in an accessible, student-friendly way to engage interest and enhance learning and confidence.
- Assumes only a basic high-school level prior mathematical knowledge.
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
- Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizinische Fachgebiete Forensik, Rechtsmedizin, Gerichtsmedizin
Weitere Infos & Material
Preface.
1 Getting the basics right.
Introduction: Why forensic science is a quantitative science.
1.1 Numbers, their representation and meaning.
Self-assessment exercises and problems.
1.2 Units of measurement and their conversion.
Self-assessment problems.
1.3 Uncertainties in measurement and how to deal with them.
Self-assessment problems.
1.4 Basic chemical calculations.
Self-assessment exercises and problems.
Chapter summary.
2 Functions, formulae and equations.
Introduction: Understanding and using functions, formulae and equations.
2.1 Algebraic manipulation of equations.
Self-assessment exercises.
2.2 Applications involving the manipulation of formulae.
Self-assessment exercises and problems.
2.3 Polynomial functions.
Self-assessment exercises and problems.
2.4 The solution of linear simultaneous equations.
Self-assessment exercises and problems.
2.5 Quadratic functions.
Self-assessment problems.
2.6 Powers and indices.
Self-assessment problems.
Chapter summary.
3 The exponential and logarithmic functions and their applications.
Introduction: Two special functions in forensic science.
3.1 Origin and definition of the exponential function.
Self-assessment exercises.
3.2 Origin and definition of the logarithmic function.
Self-assessment exercises and problems.
Self-assessment exercises.
3.3 Application: the pH scale.
Self-assessment exercises.
3.4 The "decaying" exponential.
Self-assessment problems.
3.5 Application: post-mortem body cooling.
Self-assessment problems.
3.6 Application: forensic pharmacokinetics.
Self-assessment problems.
Chapter summary.
4 Trigonometric methods in forensic science.
Introduction: Why trigonometry is needed in forensic science.
4.1 Pythagoras’s theorem.
Self-assessment exercises and problems.
4.2 The trigonometric functions.
Self-assessment exercises and problems.
4.3 Trigonometric rules.
Self-assessment exercises.
4.4 Application: heights and distances.
Self-assessment problems.
4.5 Application: ricochet analysis.
Self-assessment problems.
4.6 Application: aspects of ballistics.
Self-assessment problems.
4.7 Suicide, accident or murder?
Self-assessment problems.
4.8 Application: bloodstain shape.
Self-assessment problems.
4.9 Bloodstain pattern analysis.
Self-assessment problems.
Chapter summary.
5 Graphs - their construction and interpretation.
Introduction: Why graphs are important in forensic science.
5.1 Representing data using graphs.
5.2 Linearizing equations.
Self-assessment exercises.
5.3 Linear regression.
Self-assessment exercises.
5.4 Application: shotgun pellet patterns in firearms incidents.
Self-assessment problem.
5.5 Application: bloodstain formation.
Self-assessment problem.
5.6 Application: the persistence of hair, fibres and flints on clothing.
Self-assessment problem.
5.7 Application: determining the time since death by fly egg hatching.
5.8 Application: determining age from bone or tooth material
Self-assessment problem.
5.9 Application: kinetics of chemical reactions.
Self-assessment problems.
5.10 Graphs for calibration.
Self-assessment problems.
5.11 Excel and the construction of graphs.
Chapter summary.
6 The statistical analysis of data.
Introduction: Statistics and forensic science.
6.1 Describing a set of data.
Self-assessment problems.
6.2 Frequency statistics.
Self-assessment problems.
6.3 Probability density functions.
Self-assessment problems.
6.4 Excel and ba
