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Statistics for Forensic Toxicology

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Principles of Forensic Toxicology
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Abstract

Forensic toxicologists routinely deal with the analysis of numerical data. Statistical methods have a wide variety of applications, from initial method development and data interpretation to method validation and measurement uncertainty. In this chapter, basic concepts including data distributions, types of error, and hypothesis testing are explored. Using illustrative examples from forensic toxicology, the use of statistical tests is discussed, including the Student’s t-test and some of its variants, F-tests, and analysis of variance (ANOVA). The treatment of outliers, regression analysis, and tools for the evaluation of calibration models are also discussed.

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Further Reading

  • ANSI/ASB 036: Standard Practices for Method Validation in Forensic Toxicology

    Google Scholar 

  • Bell, S (2006) Statistics, Sampling, and Data Quality in Forensic Chemistry. Pearson Prentice Hall, Saddle River, NJ

    Google Scholar 

  • Curran MJ (2011) Introduction to data analysis with R for forensic scientists. CRC Press, Taylor & Francis Group, Boca Raton, FL

    Google Scholar 

  • ENFSI. Guideline for evaluative reporting in forensic science. Strengthening the Evaluation of Forensic Results across Europe (STEOFRAE). European Network of Forensic Sciences Institutes (2015)

    Google Scholar 

  • Lucy D (2005) Introduction to statistics for forensic scientists. John Wiley & Sons, Chichester, UK

    Google Scholar 

  • Miller JN, Miller JC, Miller RD (2018) Statistics and chemometrics for analytical chemistry, 7th edn. Pearson Education Ltd, Harlow, UK

    Google Scholar 

  • Robertson B, Vignaux GA, CEH B (2016) Interpreting evidence: Evaluating forensic science in the courtroom. John Wiley & Sons, Chichester

    Book  Google Scholar 

  • Skoog DA, West DM, Holler FJ (1994) Analytical chemistry – An introduction, 6th edn. Saunders College Publishing, Harcourt Brace College Publishers, Philadelphia, PA

    Google Scholar 

  • Taroni F, Bozza S, Biedermann A, Garbolino P, Aitken C (2010) Data analysis in forensic science – A Bayesian decision perspective. John Wiley & Sons, Chichester

    Book  Google Scholar 

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Correspondence to Patrick Buzzini .

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Appendices

Appendix 1: Table of the critical values for the Student’s t-distribution

 

α – upper tail probability p

d.f.

0.10

0.05

0.025

0.01

0.005

0.001

0.0005

1

3.078

6.314

12.076

31.821

63.657

318.310

636.620

2

1.886

2.920

4.303

6.965

9.925

22.326

31.598

3

1.638

2.353

3.182

4.541

5.841

10.213

12.924

4

1.533

2.132

2.776

3.747

4.604

7.173

8.610

5

1.476

2.015

2.571

3.365

4.032

5.893

6.869

6

1.440

1.943

2.447

3.143

3.707

5.208

5.959

7

1.415

1.895

2.365

2.998

3.499

4.785

5.408

8

1.397

1.860

2.306

2.896

3.355

4.501

5.041

9

1.383

1.833

2.262

2.821

3.250

4.297

4.781

10

1.372

1.812

2.228

2.764

3.169

4.144

4.587

11

1.363

1.796

2.201

2.718

3.106

4.025

4.437

12

1.356

1.782

2.179

2.681

3.055

3.930

4.318

13

1.350

1.771

2.160

2.650

3.012

3.852

4.221

14

1.345

1.761

2.145

2.624

2.977

3.787

4.140

15

1.341

1.753

2.131

2.602

2.947

3.733

4.073

16

1.337

1.746

2.120

2.583

2.921

3.686

4.015

17

1.333

1.740

2.110

2.567

2.898

3.646

3.965

18

1.330

1.734

2.101

2.552

2.878

3.610

3.922

19

1.328

1.729

2.093

2.539

2.861

3.579

3.883

20

1.325

1.725

2.086

2.528

2.845

3.552

3.850

21

1.323

1.721

2.080

2.518

2.831

3.527

3.819

22

1.321

1.717

2.074

2.508

2.819

3.505

3.792

23

1.319

1.714

2.069

2.500

2.807

3.485

3.767

24

1.318

1.711

2.064

2.492

2.797

3.467

3.745

25

1.316

1.708

2.060

2.485

2.787

3.450

3.725

26

1.315

1.706

2.056

2.479

2.779

3.435

3.707

27

1.314

1.703

2.052

2.473

2.771

3.421

3.690

28

1.313

1.701

2.048

2.467

2.763

3.408

3.674

29

1.311

1.699

2.045

2.462

2.756

3.396

3.659

30

1.310

1.697

2.042

2.457

2.750

3.385

3.646

40

1.303

1.684

2.021

2.423

2.704

3.307

3.551

60

1.296

1.671

2.000

2.390

2.660

3.232

3.460

120

1.289

1.658

1.980

2.358

2.617

3.160

3.373

1000

1.282

1.646

1.962

2.330

2.581

3.098

3.300

z

1.282

1.645

1.960

2.326

2.576

3.091

3.291

 

80%

90%

95%

98%

99%

99.8%

99.9%

 

Confidence level C

Appendix 2: Table of selected critical values for the F distribution for sample sets of 10 objects or 9 degrees of freedom and a significance level at α = 0.05. Refer to rows α = 0.05 for a one-tailed test and rows α = 0.025 for a two-tailed test

   

d.f. in the numerator

  

α

1

2

3

4

5

6

7

8

9

d.f. in the denominator

1

0.05

161.45

199.50

215.71

224.58

230.16

233.99

236.77

238.88

240.54

 

0.025

647.79

799.50

864.16

899.58

921.85

937.11

948.22

956.66

963.28

2

0.05

18.51

19.00

19.16

19.25

19.30

19.33

19.35

19.37

19.38

 

0.025

38.51

39.00

39.17

39.25

39.30

39.33

39.36

39.37

39.39

3

0.05

10.13

9.55

9.28

9.12

9.01

8.94

8.89

8.85

8.81

 

0.025

17.44

16.04

15.44

15.10

14.88

14.73

14.62

14.54

14.47

4

0.05

7.71

6.94

6.59

6.39

6.26

6.16

6.09

6.04

6.00

 

0.025

12.22

10.65

9.98

9.60

9.36

9.20

9.07

8.98

8.90

5

0.05

6.61

5.79

5.41

5.19

5.05

4.95

4.88

4.82

4.77

 

0.025

10.01

8.43

7.76

7.39

7.15

6.98

6.85

6.76

6.68

6

0.05

5.99

5.14

4.76

4.53

4.39

4.28

4.21

4.15

4.10

 

0.025

8.81

7.26

6.60

6.23

5.99

5.82

5.70

5.60

5.52

7

0.05

5.59

4.74

4.35

4.12

3.97

3.87

3.79

3.73

3.68

 

0.025

8.07

6.54

5.89

5.52

5.29

5.12

4.99

4.90

4.82

8

0.05

5.32

4.46

4.07

3.84

3.69

3.58

3.50

3.44

3.39

 

0.025

7.57

6.06

5.42

5.05

4.82

4.65

4.53

4.43

4.36

9

0.05

5.12

4.26

3.86

3.63

3.48

3.37

3.29

3.23

3.18

 

0.025

7.21

5.71

5.08

4.72

4.48

4.32

4.20

4.10

4.03

Appendix 3: Table of critical values of the Q test statistic (P = 0.05)

Q test statistic

 

Significance level α

 

n

0.10

0.05

0.01

\( Q=\frac{x_2-{x}_1}{x_n-{x}_1} \)

3

0.886

0.941

0.988

4

0.679

0.765

0.889

5

0.557

0.642

0.780

6

0.482

0.560

0.698

7

0.434

0.507

0.637

\( Q=\frac{x_2-{x}_1}{x_{n-1}-{x}_1} \)

8

0.479

0.554

0.683

9

0.441

0.512

0.635

10

0.409

0.477

0.597

\( Q=\frac{x_3-{x}_1}{x_{n-1}-{x}_1} \)

11

0.517

0.576

0.679

12

0.490

0.546

0.642

13

0.467

0.521

0.615

\( Q=\frac{x_3-{x}_1}{x_{n-2}-{x}_1} \)

14

0.492

0.546

0.641

15

0.472

0.525

0.616

16

0.454

0.507

0.595

17

0.438

0.490

0.577

18

0.424

0.475

0.561

19

0.412

0.462

0.547

20

0.401

0.450

0.535

21

0.391

0.440

0.524

22

0.382

0.430

0.514

23

0.374

0.421

0.505

24

0.367

0.413

0.497

25

0.360

0.406

0.489

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Buzzini, P., Kerrigan, S. (2020). Statistics for Forensic Toxicology. In: Levine, B.S., KERRIGAN, S. (eds) Principles of Forensic Toxicology. Springer, Cham. https://doi.org/10.1007/978-3-030-42917-1_18

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