Introduction to Statistics for Forensic Scientists

摘要: Preface. List of Figures. 1. A short history the statistics in law. 1.1 History. 1.2 Some recent uses forensic science. 1.3 What is probability?. 2. Data types, location and dispersion. 2.1 Types data. 2.2 Populations samples. 2.3 Distributions. 2.4 Location. 2.5 Dispersion. 2.6 Hierarchies variation. 3. Probability. 3.1 Aleatory probability. One throw a six-sided die. single with more than one outcome interest. Two-sided dice. 3.2 Binomial 3.3 Poisson 3.4 Empirical Modelled empirical probabilities. Truly 4. The normal distribution. 4.1 4.2 Standard deviation standard error mean. 4.3 Percentage points 4.4 t-distribution 4.5 t-testing between two independent 4.6 Testing paired observations. 4.7 Confidence, significance p-values. 5. Measures nominal ordinal association. 5.1 Association discrete variables. 5.2 X2 test for 2 x table. 5.3 Yules Q. 5.4 tests greater tables. 5.5 02 Cramers V2. 5.6 limitations testing. 5.7 Interpretation conclusions. 6. Correlation. 6.1 Significance correlation coefficients. 6.2 Correlation coefficients non-linear 6.3 coefficient determination. 6.4 Partial correlation. 6.5 controlling or covariates. 7. Regression calibration. 7.1 Linear models. 7.2 Calculation linear regression model. 7.3 'goodness fit'. 7.4 b. 7.5 Residuals. 7.6 Calibration. calibration confidence interval point. 7.7 Points to remember. 8. Evidence evaluation. 8.1 Verbal statements evidential value. 8.2 types. 8.3 value evidence. 8.4 testing evidence 9. Conditional probability Bayes' theorem. 9.1 9.2 9.3 10. Relevance formulation propositions. 10.1 Relevance. 10.2 Hierarchy 10.3 Likelihood ratios relevance. 10.4 logic 10.5 10.6 kind propositions can we not evaluate?. 11. Evaluation practice. 11.1 Which database use. Type geographic factors. DNA selection. 11.2 equivalence likelihood ratio. 11.3 common criticisms statistical approaches. 12. evaluation examples. 12.1 Blood group frequencies. 12.2 Trouser fibres. 12.3 Shoe 12.4 Airweapon projectiles. 12.5 Height description from eyewitness. 13. Errors interpretation. 13.1 Statistically based errors Transposed conditional. Defender's fallacy. Another match error. Numerical conversion 13.2 Methodological Different level Defendant's independence assumption. 14. I. 14.1 Loci alleles. 14.2 Simple case genotypic 14.3 Hardy-weinberg equilibrium. 14.4 allelic 14.5 Accounting sub-populations. 15. II. 15.1 Paternity - mother father unrelated. 15.2 Database searches 15.3 Discussion. 16. Sampling sample size estimation. 16.1 Estimation 16.2 Sample sizes t-tests. Two t-test. 16.3 How many drugs sample. 16.4 Concluding comments. 17. Epilogue. 17.1 Graphical models bayesian networks. Bayesian 17.2 Kernel density 17.3 Multivariate continuous matching. Appendix A: Worked solutions questions. B: C: t-distributions. D: X2-distributions. E: beta-beta distributions. F: f-distributions. G: Calculating partial correlations using excel software. H: Further algebra "third law". References. Index.