UID:
almafu_9959237700702883
Umfang:
1 online resource (xvi, 396 pages) :
,
digital, PDF file(s).
ISBN:
0-511-73962-1
,
1-107-20829-7
,
0-521-74656-6
,
1-282-53891-8
,
9786612538919
,
0-511-80755-4
,
0-511-68377-4
,
0-511-67856-8
,
0-511-67730-8
,
0-511-67981-5
Inhalt:
A reader-friendly introduction to geostatistics for students and researchers struggling with statistics. Using simple, clear explanations for introductory and advanced material, it demystifies complex concepts and makes formulas and statistical tests easy to apply. Beginning with a critical evaluation of experimental and sampling design, the book moves on to explain essential concepts of probability, statistical significance and type 1 and type 2 error. An accessible graphical explanation of analysis of variance (ANOVA) leads onto advanced ANOVA designs, correlation and regression, and non-parametric tests including chi-square. Finally, it introduces the essentials of multivariate techniques, multi-dimensional scaling and cluster analysis, analysis of sequences and concepts of spatial analysis. Illustrated with wide-ranging examples from topics across the Earth and environmental sciences, Geostatistics Explained can be used for undergraduate courses or for self-study and reference. Worked examples at the end of each chapter reinforce a clear understanding of the statistical tests and their applications.
Anmerkung:
Title from publisher's bibliographic system (viewed on 05 Oct 2015).
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Cover; Half-title; Title; Copyright; Contents; Preface; 1 Introduction; 1.1 Why do earth scientists need to understand experimental design and statistics?; 1.2 What is this book designed to do?; 2 "Doing science": hypotheses, experiments and disproof; 2.1 Introduction; 2.2 Basic scientific method; 2.3 Making a decision about a hypothesis; 2.4 Why can't a hypothesis or theory ever be proven?; 2.5 "Negative" outcomes; 2.6 Null and alternate hypotheses; 2.7 Conclusion; 2.8 Questions; 3 Collecting and displaying data; 3.1 Introduction; 3.2 Variables, sampling units and types of data
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3.3 Displaying data3.3.1 Histograms; 3.3.2 Frequency polygons or line graphs; 3.3.3 Cumulative graphs; 3.4 Displaying ordinal or nominal scale data; 3.5 Bivariate data; 3.6 Data expressed as proportions of a total; 3.7 Display of geographic direction or orientation; 3.8 Multivariate data; 3.9 Conclusion; 4 Introductory concepts of experimental design; 4.1 Introduction; 4.2 Sampling: mensurative experiments; 4.2.1 Confusing a correlation with causality; 4.2.2 The inadvertent inclusion of a third variable: sampling confounded in time
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4.2.3 The need for independent samples in mensurative experiments4.2.4 The need to repeat the sampling on several occasions and elsewhere; 4.3 Manipulative experiments; 4.3.1 Independent replicates; 4.3.2 Control treatments; 4.3.3 Pseudoreplication; 4.4 Sometimes you can only do an unreplicated experiment; 4.5 Realism; 4.6 A bit of common sense; 4.7 Designing a "good" experiment; 4.7.1 Good design versus the ability to do the experiment; 4.8 Conclusion; 4.9 Questions; 5 Doing science responsibly and ethically; 5.1 Introduction; 5.2 Dealing fairly with other people's work; 5.2.1 Plagiarism
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5.2.2 Acknowledging previous work5.2.3 Fair dealing; 5.2.4 Acknowledging the input of others; 5.3 Doing the sampling or the experiment; 5.3.1 Approval; 5.3.2 Ethics; 5.4 Evaluating and reporting results; 5.4.1 Pressure from peers or superiors; 5.4.2 Record keeping; 5.5 Quality control in science; 5.6 Questions; 6 Probability helps you make a decision about your results; 6.1 Introduction; 6.2 Statistical tests and significance levels; 6.3 What has this got to do with making a decision or statistical testing?; 6.4 Making the wrong decision; 6.5 Other probability levels
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6.6 How are probability values reported?6.7 All statistical tests do the same basic thing; 6.8 A very simple example: the chi-square test for goodness of fit; 6.9 What if you get a statistic with a probability of exactly 0.05?; 6.10 Conclusion; 6.11 Questions; 7 Working from samples: data, populations and statistics; 7.1 Using a sample to infer the characteristics of a population; 7.2 Statistical tests; 7.3 The normal distribution; 7.3.1 The mean of a normally distributed population; 7.3.2 The variance of a population; 7.3.3 The standard deviation of a population; 7.3.4 The Z statistic
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7.4 Samples and populations
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English
Weitere Ausg.:
ISBN 0-511-68179-8
Weitere Ausg.:
ISBN 0-521-76322-3
Sprache:
Englisch
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