Format:
Online Ressource (xix, 676 p.)
,
ill., maps.
Edition:
3rd ed
Edition:
Online-Ausg.
ISBN:
9780123850225
,
0123850223
,
9781283101295
,
1283101297
Series Statement:
International geophysics series v. 100
Content:
I Preliminaries -- Ch. 1 Introduction -- Ch. 2 Review of Probability -- II Univariate Statistics -- Ch. 3 Empirical Distributions and Exploratory Data Analysis -- Ch. 4 Parametric Probability Distributions -- Ch. 5 Frequentist Statistical Inference -- Ch. 6 Bayesian Inference -- Ch. 7 Statistical Forecasting -- Ch. 8 Forecast Verification -- Ch. 9 Time Series -- III Multivariate Statistics -- Ch. 10 Matrix Algebra and Random Matrices -- Ch. 11 The Multivariate Normal (MVN) Distribution -- Ch. 12 Principal Component (EOF) Analysis -- Ch. 13 Canonical Correlation Analysis (CCA) -- Ch. 14 Discrimination and Classification -- Ch. 15 Cluster Analysis -- Appendix A Example Data Sets -- Appendix B Probability Tables -- Appendix C Answers to Exercises -- References -- Index
Content:
Praise for the First Edition: "I recommend this book, without hesitation, as either a reference or course text ... Wilks' excellent book provides a thorough base in applied statistical methods for atmospheric sciences."--BAMS (Bulletin of the American Meteorological Society) Fundamentally, statistics is concerned with managing data and making inferences and forecasts in the face of uncertainty. It should not be surprising, therefore, that statistical methods have a key role to play in the atmospheric sciences. It is the uncertainty in atmospheric behavior that continues to move research forward and drive innovations in atmospheric modeling and prediction. This revised and expanded text explains the latest statistical methods that are being used to describe, analyze, test and forecast atmospheric data. It features numerous worked examples, illustrations, equations, and exercises with separate solutions. Statistical Methods in the Atmospheric Sciences, Second Edition will help advanced students and professionals understand and communicate what their data sets have to say, and make sense of the scientific literature in meteorology, climatology, and related disciplines. Accessible presentation and explanation of techniques for atmospheric data summarization, analysis, testing and forecasting Many worked examples End-of-chapter exercises, with answers provided
Note:
Includes bibliographical references and index. - Description based on print version record
,
pt. 1. Preliminaries -- pt. 2. Univariate statistics -- pt. 3. Multivariate statistics.
,
I Preliminaries -- Ch. 1 Introduction -- Ch. 2 Review of Probability -- II Univariate Statistics -- Ch. 3 Empirical Distributions and Exploratory Data Analysis -- Ch. 4 Parametric Probability Distributions -- Ch. 5 Frequentist Statistical Inference -- Ch. 6 Bayesian Inference -- Ch. 7 Statistical Forecasting -- Ch. 8 Forecast Verification -- Ch. 9 Time Series -- III Multivariate Statistics -- Ch. 10 Matrix Algebra and Random Matrices -- Ch. 11 The Multivariate Normal (MVN) Distribution -- Ch. 12 Principal Component (EOF) Analysis -- Ch. 13 Canonical Correlation Analysis (CCA) -- Ch. 14 Discrimination and Classification -- Ch. 15 Cluster Analysis -- Appendix A Example Data Sets -- Appendix B Probability Tables -- Appendix C Answers to Exercises -- References -- Index.
Additional Edition:
ISBN 0691081042
Language:
English
Subjects:
Physics
Keywords:
Atmosphäre
;
Statistik
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