Geostatistics explained: an introductory guide for earth scientists/ Steve McKillup

By: McKillup, SteveMaterial type: TextTextPublication details: Cambridge: Cambridge University Press, 2010Description: xvi, 396 pISBN: 9780521746564Subject(s): Geology--Statistical methods -- Earth sciences--Statistical methods DDC classification: 550.15195
Contents:
1. Introduction; 2. 'Doing science': hypotheses, experiments and disproof; 3. Collecting and displaying data; 4. Introductory concepts of experimental design; 5. Doing science responsibly and ethically; 6. Probability helps you make a decision about your results; 7. Working from samples: data, populations and statistics; 8. Normal distributions: tests for comparing the means of one and two samples; 9. Type 1 and type 2 error, power and sample size; 10. Single factor analysis of variance; 11. Multiple comparisons after ANOVA; 12. Two-factor analysis of variance; 13. Important assumptions of analysis of variance: transformations and a test for equality of variances; 14. Two-factor analysis of variance without replication, and nested analysis of variance; 15. Relationships between variables: linear correlation and linear regression; 16. Linear regression; 17. Non-parametric statistics; 18. Non-parametric tests for nominal scale data; 19. Non-parametric tests for ratio, interval or ordinal scale data; 20. Introductory concepts of multivariate analysis; 21. Introductory concepts of sequence analysis; 22. Introductory concepts of spatial analysis; 23. Choosing a test
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Holdings
Item type Current library Call number Status Date due Barcode Item holds
General Books General Books Central Library, Sikkim University
General Book Section
550.15195 MCK/G (Browse shelf(Opens below)) Available P27304
Total holds: 0

1. Introduction; 2. 'Doing science': hypotheses, experiments and disproof; 3. Collecting and displaying data; 4. Introductory concepts of experimental design; 5. Doing science responsibly and ethically; 6. Probability helps you make a decision about your results; 7. Working from samples: data, populations and statistics; 8. Normal distributions: tests for comparing the means of one and two samples; 9. Type 1 and type 2 error, power and sample size; 10. Single factor analysis of variance; 11. Multiple comparisons after ANOVA; 12. Two-factor analysis of variance; 13. Important assumptions of analysis of variance: transformations and a test for equality of variances; 14. Two-factor analysis of variance without replication, and nested analysis of variance; 15. Relationships between variables: linear correlation and linear regression; 16. Linear regression; 17. Non-parametric statistics; 18. Non-parametric tests for nominal scale data; 19. Non-parametric tests for ratio, interval or ordinal scale data; 20. Introductory concepts of multivariate analysis; 21. Introductory concepts of sequence analysis; 22. Introductory concepts of spatial analysis; 23. Choosing a test

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