01091nam0-2200385---450 99000848739040332120200430095647.088-513-0031-3000848739FED01000848739(Aleph)000848739FED0100084873920070319d2002----km-y0itay50------baitaITa-------001yy<<Il >>fotovoltaico in architettural'integrazione dei sistemi a energia solare negli edificiNiccolò AsteNapoliEsselibri2002XIII, 237 p.ill.24 cmArchitettura sostenibile4Energia solareImpianti solari697.78Aste,Niccolò447775ITUNINARICAUNIMARCBK990008487390403321B 704 CAN3720 URBDARPU08 AM 851456DINED12.12906/19DARSTDARSTDARPUDINEDFotovoltaico in architettura104080UNINA04083nam 22007095 450 991064778600332120250610122441.09783031142758(electronic bk.)978303114274110.1007/978-3-031-14275-8(MiAaPQ)EBC7191448(Au-PeEL)EBL7191448(CKB)26089876900041(DE-He213)978-3-031-14275-8(PPN)268204969(EXLCZ)992608987690004120230204d2022 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierTen Projects in Applied Statistics /by Peter McCullagh1st ed. 2022.Cham :Springer International Publishing :Imprint: Springer,2022.1 online resource (415 pages)Springer Series in Statistics,2197-568XPrint version: McCullagh, Peter Ten Projects in Applied Statistics Cham : Springer International Publishing AG,c2023 9783031142741 Includes bibliographical references and index.1. Rat Surgery -- 2. Chain Saws -- 3. Fruit Flies -- 4. Growth Curves -- 5. Louse Evolution -- 6. Time Series I -- 7. Time Series II -- 8. Out of Africa -- 9. Environmental Projects -- 10. Fulmar Fitness -- 11. Basic Concepts -- 12. Principles -- 13. Initial Values -- 14. Probability Distributions -- 15. Gaussian Distributions -- 16. Space-Time Processes -- 17. Likelihood -- 18. Residual Likelihood -- 19. Response Transformation -- 20. Presentations and Reports -- 21. Q & A. .The first half of the book is aimed at quantitative research workers in biology, medicine, ecology and genetics. The book as a whole is aimed at graduate students in statistics, biostatistics, and other quantitative disciplines. Ten detailed examples show how the author approaches real-world statistical problems in a principled way that allows for adequate compromise and flexibility. The need to accommodate correlations associated with space, time and other relationships is a recurring theme, so variance-components models feature prominently. Statistical pitfalls are illustrated via examples taken from the recent scientific literature. Chapter 11 sets the scene, not just for the second half of the book, but for the book as a whole. It begins by defining fundamental concepts such as baseline, observational unit, experimental unit, covariates and relationships, randomization, treatment assignment, and the role that these play in model formulation. Compatibility of the model with the randomization scheme is crucial. The effect of treatment is invariably modelled as a group action on probability distributions. Technical matters connected with space-time covariance functions, residual likelihood, likelihood ratios, and transformations are discussed in later chapters.Springer Series in Statistics,2197-568XStatisticsBiometrySampling (Statistics)Quantitative researchStatistical Theory and MethodsBiostatisticsMethodology of Data Collection and ProcessingData Analysis and Big DataEstadísticathubInvestigació quantitativathubLlibres electrònicsthubStatistics.Biometry.Sampling (Statistics)Quantitative research.Statistical Theory and Methods.Biostatistics.Methodology of Data Collection and Processing.Data Analysis and Big Data.EstadísticaInvestigació quantitativa519.5519McCullagh P. J(Peter John),479401MiAaPQMiAaPQMiAaPQ9910647786003321Ten projects in applied statistics3362300UNINA