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[null,"1.","Record Nr.",null,"UNINA9910484650903321"]
[null,null,"Autore",null,"Dodge Yadolah"]
[null,null,"Titolo",null,"The Concise Encyclopedia of Statistics [[electronic resource] /] / by Yadolah Dodge"]
[null,null,"Pubbl/distr/stampa",null,"New York, NY : , : Springer New York : , : Imprint : Springer, , 2008"]
[null,null,"ISBN",null,"0-387-32833-5"]
[null,null,"Edizione",null,"[1st ed. 2008.]"]
[null,null,"Descrizione fisica",null,"1 online resource (611 p.)"]
[null,null,"Collana",null,"Springer reference"]
[null,null,"Disciplina",null,"519.503"]
[null,null,"Soggetti",null,"Statistics "]
[{"$nulls":4},"Engineering"]
[{"$nulls":4},"Statistics, general"]
[{"$nulls":4},"Science, Humanities and Social Sciences, multidisciplinary"]
[{"$nulls":4},"Engineering, general"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","\"With 247 tables.\""]
[null,null,null,"Nota di bibliografia","Includes bibliographical references (pages [597]-616)."]
[null,null,"Nota di contenuto",null,"A -- Acceptance Region -- Accuracy -- Algorithm -- Alternative hypothesis -- Analysis of binary data -- Analysis of categorical data -- Analysis of residuals -- Analysis of variance -- Anderson Oskar -- Anderson Theodore W -- Anderson-Darling test -- Arithmetic mean -- Arithmetic triangle -- ARMA models -- Arrangement -- Attributable risk -- Autocorrelation and partial autocorrelation -- Avoidable risk."]
[null,null,null,"Sommario/riassunto","The Concise Encyclopedia of Statistics presents the essential information about statistical tests, concepts, and analytical methods in language that is accessible to practitioners and students of the vast community using statistics in medicine, engineering, physical science, life science, social science, and business/economics. The reference is alphabetically arranged to provide quick access to the fundamental tools of statistical methodology and biographies of famous statisticians. The more than 500 entries include definitions, history, mathematical details, limitations, examples, references, and further readings. All entries include cross-references as well as the key citations. The back matter includes a timeline of statistical inventions. This reference will be an enduring resource for locating convenient overviews about this essential field of study. Founder of the Master in Statistics program in 1989 for the University of Neuchâtel in Switzerland, Professor Yadolah Dodge earned his Master in Applied Statistics from the Utah State University in 1970 and his Ph.D. in "]
[{"$nulls":4},"Statistics with minor in Biometry from the Oregon State University in 1973. He has published numerous articles and authored, co-authored and edited several books including Mathematical Programming in Statistics (John Wiley 1981, Classic Edition 1993), Analysis of Experiments with Missing Data (John Wiley 1985), Alternative Methods of Regression (John Wiley 1993), Premier Pas en Statistique (Springer 1999), Adaptive Regression (2000), The Oxford Dictionary of Statistical Terms (2003), Statistique: Dictionnaire encyclopédique (Springer 2004), and Optimisation appliquée (Springer 2005). Professor Dodge is an elected member of the International Statistical Institute and a Fellow of the Royal Statistical Society."]
[null,"2.","Record Nr.",null,"UNINA9910595066903321"]
[null,null,"Autore",null,"Luo Suhuai"]
[null,null,"Titolo",null,"Computational Methods for Medical and Cyber Security"]
[null,null,"Pubbl/distr/stampa",null,"Basel, : MDPI Books, 2022"]
[null,null,"Descrizione fisica",null,"1 electronic resource (228 p.)"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Sommario/riassunto","Over the past decade, computational methods, including machine learning (ML) and deep learning (DL), have been exponentially growing in their development of solutions in various domains, especially medicine, cybersecurity, finance, and education. While these applications of machine learning algorithms have been proven beneficial in various fields, many shortcomings have also been highlighted, such as the lack of benchmark datasets, the inability to learn from small datasets, the cost of architecture, adversarial attacks, and imbalanced datasets. On the other hand, new and emerging algorithms, such as deep learning, one-shot learning, continuous learning, and generative adversarial networks, have successfully solved various tasks in these fields. Therefore, applying these new methods to life-critical missions is crucial, as is measuring these less-traditional algorithms' success when used in these fields."]
[null,"3.","Record Nr.",null,"UNINA9910637782303321"]
[null,null,"Autore",null,"Wu Jianhua"]
[null,null,"Titolo",null,"Groundwater Quality and Public Health"]
[null,null,"Pubbl/distr/stampa",null,"Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022"]
[null,null,"ISBN",null,"3-0365-5835-7"]
[null,null,"Descrizione fisica",null,"1 online resource (228 p.)"]
[null,null,"Soggetti",null,"Environmental economics"]
[{"$nulls":4},"Pollution control"]
[{"$nulls":4},"Research and information: general"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Sommario/riassunto","This book attempts to provide a platform for researchers, policy makers, and engineers to share their latest thoughts and findings on groundwater quality and public health, as well as novel methods dealing with groundwater pollution. The chapters published in this book include the latest research results by world-renowned researchers, whose findings can benefit researchers, engineers, policy makers, and government officials in future groundwater quality research and policy making."]