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Introduction. Review of Probability. Empirical Distributions and Exploratory Data Analysis. Theoretical Probability Distributions. Hypothesis Testing. Statistical Weather Forecasting. Forecast Verification. Time Series. Methodsfor Multivariate Data. Chapter Exercises. Appendices: Example Data Sets. Selected Probability Tables. Answers to Exercises. References. Subject Index.
This book introduces and explains the statistical methods used to describe, analyze, test, and forecast atmospheric data. It will be useful to students, scientists, and other professionals who seek to make sense of the scientific literature in meteorology, climatology, or other geophysical disciplines, or to understand and communicate what their atmospheric data sets have to say. The book includes chapters on exploratory data analysis, probability distributions, hypothesis testing, statistical weather forecasting, forecast verification, time(series analysis, and multivariate data analysis. Worked examples, exercises, and illustrations facilitate understanding of the material; an extensive and up-to-date list of references allows the reader to pursue selected topics in greater depth.
@bul:* Presents and explains techniques used in atmospheric data summarization, analysis, testing, and forecasting
* Includes extensive and up-to-date references
* Features numerous worked examples and exercises
* Contains over 130 illustrations
Senior and graduate students in courses in meteorological statistics, statistical chemistry, and meteorological methods. Researchers in atmospheric science, meteorology, and oceanography.
- No. of pages:
- © Academic Press 1995
- 23rd January 1995
- Academic Press
- eBook ISBN:
@qu:The book is a must-buy if you use statistics in your classes or research. It can serve as a text or a reference work.
@source:-JAMES J. OBRIEN, The Florida State University
@qu:I recommend this book, without hesitation, as either a reference or course text. I found the books range of topics, depth of treatment, and pedagogical style with relatively few exceptions appropriate for upper-division undergraduates and beginning graduate students...Wilks excellent book provides a thorough base in applied statistical methods for atmospheric scientists. I hope its availability will encourage university atmospheric programs to provide all of their degree candidates with a treatment of this important subject that is as broad and in-depth as that provided by Wilks at Cornell.
@source:--Robert E. Livezey, National Centers fo Environmental Prediction, in BULLETIN OF THE AMS
@qu:It combines a clear introduction of both fundamentals and advanced applications with many examples of how they can be used. It could be used as an effective teaching tool at both the undergraduate and graduate level. A book of this type was needed.
@source:-DENNIS L. HARTMANN, University of Washington
@qu:Wilks has produced such a 'suitable replacement and I recommend his book, without hesitation, as either a reference or course text....Wilks excellent book provides a thorough base in applied statistical methods for atmospheric scientists. I hope its availability will encourage university atmospheric science programs to provide all of their degree candidates with a treatment of this important subject that is as broad and in-depth as that provided by Wilks at Cornell.
@source:Robert E. Livezey, Climate Prediction Center of the National Oceanic and Atmospheric Administrations National Centers for Environmental Prediction, Camp Springs, Maryland, in BULLETIN OF AMERICAN METEOROLOGY SOCIETY
@qu:The presentation is very readable and the material accurately presented.
Daniel S. Wilks has been a member of the Atmospheric Sciences faculty at Cornell University since 1987, and is the author of Statistical Methods in the Atmospheric Sciences (2011, Academic Press), which is in its third edition and has been continuously in print since 1995. Research areas include statistical forecasting, forecast postprocessing, and forecast evaluation.
Department of Earth and Atmospheric Sciences, Cornell University, USA
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