Statistical methods for climate scientists / Timothy DelSole, Michael K. Tippett.
"A comprehensive introduction to the most commonly used statistical methods relevant in atmospheric, oceanic and climate sciences. Each method is described step-by-step using plain language, and illustrated with concrete examples, with relevant statistical and scientific concepts explained as n...
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| Online Access: |
Full Text (via Cambridge) |
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| Main Authors: | , |
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Cambridge, United Kingdom ; New York, NY :
Cambridge University Press,
2022.
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| Subjects: |
MARC
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| 100 | 1 | |a DelSole, Timothy M., |e author. | |
| 245 | 1 | 0 | |a Statistical methods for climate scientists / |c Timothy DelSole, Michael K. Tippett. |
| 264 | 1 | |a Cambridge, United Kingdom ; |a New York, NY : |b Cambridge University Press, |c 2022. | |
| 264 | 4 | |c ©2022 | |
| 300 | |a 1 online resource (xvii, 523 pages) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 385 | |a Climatologists |2 lcdgt | ||
| 504 | |a Includes bibliographical references and index. | ||
| 520 | |a "A comprehensive introduction to the most commonly used statistical methods relevant in atmospheric, oceanic and climate sciences. Each method is described step-by-step using plain language, and illustrated with concrete examples, with relevant statistical and scientific concepts explained as needed. Particular attention is paid to nuances and pitfalls, with sufficient detail to enable the reader to write relevant code. Topics covered include hypothesis testing, time series analysis, linear regression, data assimilation, extreme value analysis, Principal Component Analysis, Canonical Correlation Analysis, Predictable Component Analysis, and Covariance Discriminant Analysis. The specific statistical challenges that arise in climate applications are also discussed, including model selection problems associated with Canonical Correlation Analysis, Predictable Component Analysis, and Covariance Discriminant Analysis. Requiring no previous background in statistics, this is a highly accessible textbook and reference for students and early-career researchers in the climate sciences"-- |c Provided by publisher. | ||
| 588 | |a Description based on online resource; title from digital title page (viewed on April 20, 2022). | ||
| 650 | 0 | |a Climatology |x Statistical methods. | |
| 650 | 0 | |a Atmospheric science |x Statistical methods. | |
| 650 | 0 | |a Marine sciences |x Statistical methods. | |
| 650 | 7 | |a Climatology |x Statistical methods. |2 fast |0 (OCoLC)fst00864308 | |
| 700 | 1 | |a Tippett, Michael K., |e author. | |
| 776 | 0 | 8 | |i Print version: |a DelSole, Timothy M. |t Statistical methods for climate scientists. |d New York : Cambridge University Press, 2021 |z 9781108472418 |w (DLC) 2021024712 |
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