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Statistical analysis in forensic science : evidential value of multivariate physicochemical data / / Grzegorz Zadora [and three others]
| Statistical analysis in forensic science : evidential value of multivariate physicochemical data / / Grzegorz Zadora [and three others] |
| Autore | Zadora Grzegorz |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Chichester, West Sussex : , : Wiley, , 2014 |
| Descrizione fisica | 1 online resource (338 p.) |
| Disciplina | 614/.12 |
| Altri autori (Persone) |
ZadoraGrzegorz
MartynaAgnieszka RamosDaniel AitkenColin |
| Soggetto topico |
Chemistry, Forensic
Forensic statistics Chemometrics |
| ISBN |
1-118-76318-1
1-118-76315-7 1-118-76317-3 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Statistical Analysis in Forensic Science; Contents; Preface; 1 Physicochemical data obtained in forensic science laboratories; 1.1 Introduction; 1.2 Glass; 1.2.1 SEM-EDX technique; 1.2.2 GRIM technique; 1.3 Flammable liquids: ATD-GC/MS technique; 1.4 Car paints: Py-GC/MS technique; 1.5 Fibres and inks: MSP-DAD technique; References; 2 Evaluation of evidence in the form of physicochemical data; 2.1 Introduction; 2.2 Comparison problem; 2.2.1 Two-stage approach; 2.2.2 Likelihood ratio approach; 2.2.3 Difference between an application of two-stage approach and likelihood ratio approach
2.3 Classification problem2.3.1 Chemometric approach; 2.3.2 Likelihood ratio approach; 2.4 Likelihood ratio and Bayes' theorem; References; 3 Continuous data; 3.1 Introduction; 3.2 Data transformations; 3.3 Descriptive statistics; 3.3.1 Measures of location; 3.3.2 Dispersion: Variance estimation; 3.3.3 Data distribution; 3.3.4 Correlation; 3.3.5 Continuous probability distributions; 3.4 Hypothesis testing; 3.4.1 Introduction; 3.4.2 Hypothesis test for a population mean for samples with known variance from a normal distribution 3.4.3 Hypothesis test for a population mean for small samples with unknown variance from a normal distribution3.4.4 Relation between tests and confidence intervals; 3.4.5 Hypothesis test based on small samples for a difference in the means of two independent populations with unknown variances from normal distributions; 3.4.6 Paired comparisons; 3.4.7 Hotelling's test; 3.4.8 Significance test for correlation coefficient; 3.5 Analysis of variance; 3.5.1 Principles of ANOVA; 3.5.2 Feature selection with application of ANOVA; 3.5.3 Testing of the equality of variances; 3.6 Cluster analysis 3.6.1 Similarity measurements3.6.2 Hierarchical cluster analysis; 3.7 Dimensionality reduction; 3.7.1 Principal component analysis; 3.7.2 Graphical models; References; 4 Likelihood ratio models for comparison problems; 4.1 Introduction; 4.2 Normal between-object distribution; 4.2.1 Multivariate data; 4.2.2 Univariate data; 4.3 Between-object distribution modelled by kernel density estimation; 4.3.1 Multivariate data; 4.3.2 Univariate data; 4.4 Examples; 4.4.1 Univariate research data - normal between-object distribution - R software 4.4.2 Univariate casework data - normal between-object distribution - Bayesian network4.4.3 Univariate research data - kernel density estimation - R software; 4.4.4 Univariate casework data - kernel density estimation - calcuLatoR software; 4.4.5 Multivariate research data - normal between-object distribution - R software; 4.4.6 Multivariate research data - kernel density estimation procedure - R software; 4.4.7 Multivariate casework data - kernel density estimation - R software; 4.5 R Software; 4.5.1 Routines for casework applications; 4.5.2 Routines for research applications; References 5 Likelihood ratio models for classification problems |
| Record Nr. | UNINA-9910139027903321 |
Zadora Grzegorz
|
||
| Chichester, West Sussex : , : Wiley, , 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Statistical analysis in forensic science : evidential value of multivariate physicochemical data / / Grzegorz Zadora [and three others]
| Statistical analysis in forensic science : evidential value of multivariate physicochemical data / / Grzegorz Zadora [and three others] |
| Autore | Zadora Grzegorz |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Chichester, West Sussex : , : Wiley, , 2014 |
| Descrizione fisica | 1 online resource (338 p.) |
| Disciplina | 614/.12 |
| Altri autori (Persone) |
ZadoraGrzegorz
MartynaAgnieszka RamosDaniel AitkenColin |
| Soggetto topico |
Chemistry, Forensic
Forensic statistics Chemometrics |
| ISBN |
1-118-76318-1
1-118-76315-7 1-118-76317-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Statistical Analysis in Forensic Science; Contents; Preface; 1 Physicochemical data obtained in forensic science laboratories; 1.1 Introduction; 1.2 Glass; 1.2.1 SEM-EDX technique; 1.2.2 GRIM technique; 1.3 Flammable liquids: ATD-GC/MS technique; 1.4 Car paints: Py-GC/MS technique; 1.5 Fibres and inks: MSP-DAD technique; References; 2 Evaluation of evidence in the form of physicochemical data; 2.1 Introduction; 2.2 Comparison problem; 2.2.1 Two-stage approach; 2.2.2 Likelihood ratio approach; 2.2.3 Difference between an application of two-stage approach and likelihood ratio approach
2.3 Classification problem2.3.1 Chemometric approach; 2.3.2 Likelihood ratio approach; 2.4 Likelihood ratio and Bayes' theorem; References; 3 Continuous data; 3.1 Introduction; 3.2 Data transformations; 3.3 Descriptive statistics; 3.3.1 Measures of location; 3.3.2 Dispersion: Variance estimation; 3.3.3 Data distribution; 3.3.4 Correlation; 3.3.5 Continuous probability distributions; 3.4 Hypothesis testing; 3.4.1 Introduction; 3.4.2 Hypothesis test for a population mean for samples with known variance from a normal distribution 3.4.3 Hypothesis test for a population mean for small samples with unknown variance from a normal distribution3.4.4 Relation between tests and confidence intervals; 3.4.5 Hypothesis test based on small samples for a difference in the means of two independent populations with unknown variances from normal distributions; 3.4.6 Paired comparisons; 3.4.7 Hotelling's test; 3.4.8 Significance test for correlation coefficient; 3.5 Analysis of variance; 3.5.1 Principles of ANOVA; 3.5.2 Feature selection with application of ANOVA; 3.5.3 Testing of the equality of variances; 3.6 Cluster analysis 3.6.1 Similarity measurements3.6.2 Hierarchical cluster analysis; 3.7 Dimensionality reduction; 3.7.1 Principal component analysis; 3.7.2 Graphical models; References; 4 Likelihood ratio models for comparison problems; 4.1 Introduction; 4.2 Normal between-object distribution; 4.2.1 Multivariate data; 4.2.2 Univariate data; 4.3 Between-object distribution modelled by kernel density estimation; 4.3.1 Multivariate data; 4.3.2 Univariate data; 4.4 Examples; 4.4.1 Univariate research data - normal between-object distribution - R software 4.4.2 Univariate casework data - normal between-object distribution - Bayesian network4.4.3 Univariate research data - kernel density estimation - R software; 4.4.4 Univariate casework data - kernel density estimation - calcuLatoR software; 4.4.5 Multivariate research data - normal between-object distribution - R software; 4.4.6 Multivariate research data - kernel density estimation procedure - R software; 4.4.7 Multivariate casework data - kernel density estimation - R software; 4.5 R Software; 4.5.1 Routines for casework applications; 4.5.2 Routines for research applications; References 5 Likelihood ratio models for classification problems |
| Record Nr. | UNINA-9910820309003321 |
|
Zadora Grzegorz
|
||
| Chichester, West Sussex : , : Wiley, , 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||