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This book includes a wide selection of papers presented at the 50th Scientific Meeting of the Italian Statistical Society (SIS2021), held virtually on 21-125 June 2021. It covers a wide variety of subjects ranging from methodological and theoretical contributions to applied works and case studies, giving an excellent overview of the interests of the Italian statisticians and their international collaborations. Intended for researchers interested in theoretical and empirical issues, this volume provides interesting starting points for further research.

Quantitative research. --- Mathematical statistics—Data processing. --- Statistics. --- Data Analysis and Big Data. --- Statistics and Computing. --- Statistical Theory and Methods. --- Applied Statistics. --- Estadística --- Estadística matemàtica --- Processament de dades --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Mathematics --- Econometrics --- Data analysis (Quantitative research) --- Exploratory data analysis (Quantitative research) --- Quantitative analysis (Research) --- Quantitative methods (Research) --- Research --- Processament de dades electròniques --- Processament automàtic de dades --- Processament electrònic de dades --- Processament integrat de dades --- Sistematització de dades (Ordinadors) --- Tractament de dades --- Tractament electrònic de dades --- Tractament integrat de dades --- Automatització --- Informàtica --- Complexitat computacional --- Curació de dades --- Depuració (Informàtica) --- Estructures de dades (Informàtica) --- Gestió de bases de dades --- Informàtica mòbil --- Informàtica recreativa --- Intel·ligència artificial --- Sistemes en línia --- Temps real (Informàtica) --- Tractament del llenguatge natural (Informàtica) --- Processament òptic de dades --- Protecció de dades --- Transmissió de dades --- Tolerància als errors (Informàtica) --- Estadística descriptiva --- Inferència estadística --- Matemàtica estadística --- Mètodes estadístics --- Anàlisi d'error (Matemàtica) --- Anàlisi de regressió --- Anàlisi de sèries temporals --- Anàlisi de variància --- Anàlisi multivariable --- Anàlisi seqüencial --- Astronomia estadística --- Correlació (Estadística) --- Dependència (Estadística) --- Estadística no paramètrica --- Estadística robusta --- Física estadística --- Mètode dels moments (Estadística) --- Models lineals (Estadística) --- Models no lineals (Estadística) --- Teoria de l'estimació --- Teoria de la predicció --- Tests d'hipòtesi (Estadística) --- Biometria --- Mostreig (Estadística) --- Anàlisi estadística --- Control estadístic --- Informació estadística --- Economia --- Matemàtica --- Allisament (Estadística) --- Censos --- Presa de decisions (Estadística) --- Estadística comercial --- Estadística demogràfica --- Estadística econòmica --- Estadística educativa --- Estadística financera --- Estadística industrial --- Estadística mèdica --- Mitjana (Estadística) --- Serveis estadístics --- Sondejos d'opinió --- Econometria --- Investigació quantitativa --- Statistics

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This book describes official statistics as a tool to hold up a mirror to society – but also as an instrument for those who can manipulate this mirror. It addresses the precarious interaction of politics, official statistics, and ethical principles. Three sets of themes can be derived from this relationship, which are the focus of this book: Political systems and guiding principles, official statistics as a science of the state, and ethical issues arising from them. Ultimately, the determining factor is the political system that exists in each case. The book contains eleven chapters. The first three focus on the key concepts of the book: power and morality, official statistics and policy making, and ethical principles for statistical work. Three further chapters focus on episodes that illustrate, as "drastic" examples, the misuse of official statistics over the past hundred years, covering the situation in the Soviet Union, the Third Reich and Greece. The remaining five chapters take up current topics that pose particular challenges to official statistics. These are the phenomena paraphrased by digitalisation, globalisation, happiness research, overpopulation, migration, the Covid-19 pandemic and climate change. The book is primarily aimed at statisticians working in national and international statistical institutions, but also at readers interested in statistics, national accounts, economic and statistics history, and ethical issues.

Statistical services. --- Data collection services --- Information services --- Statistics --- Estadística --- Serveis estadístics --- Política

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Regression analysis. --- Multivariate analysis. --- Multivariate distributions --- Multivariate statistical analysis --- Statistical analysis, Multivariate --- Analysis of variance --- Mathematical statistics --- Matrices --- Analysis, Regression --- Linear regression --- Regression modeling --- Multivariate analysis --- Structural equation modeling --- Anàlisi multivariable --- Anàlisi de regressió --- Model de regressió --- Regressió lineal --- Estadística --- Estadística matemàtica --- Correlació múltiple (Estadística) --- Correlació (Estadística) --- Models d'equacions estructurals --- Anàlisi multivariant --- Matrius (Matemàtica) --- Anàlisi de conglomerats --- Anàlisi de correspondències (Estadística) --- Anàlisi discriminant --- Modelització multiescala --- Anàlisi conjunt (Màrqueting)

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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.

Statistical science --- Biomathematics. Biometry. Biostatistics --- biomathematica --- biostatistiek --- statistiek --- biometrie --- statistisch onderzoek --- Mathematical statistics. --- Mathematical statistics --- Estadística --- Investigació quantitativa --- Asymptotic theory.

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This book provides a self-contained introduction of mixed-effects models and small area estimation techniques. In particular, it focuses on both introducing classical theory and reviewing the latest methods. First, basic issues of mixed-effects models, such as parameter estimation, random effects prediction, variable selection, and asymptotic theory, are introduced. Standard mixed-effects models used in small area estimation, known as the Fay-Herriot model and the nested error regression model, are then introduced. Both frequentist and Bayesian approaches are given to compute predictors of small area parameters of interest. For measuring uncertainty of the predictors, several methods to calculate mean squared errors and confidence intervals are discussed. Various advanced approaches using mixed-effects models are introduced, from frequentist to Bayesian approaches. This book is helpful for researchers and graduate students in fields requiring data analysis skills as well as in mathematical statistics.

Multilevel models (Statistics) --- Hierarchical linear models (Statistics) --- Mixed effects models (Statistics) --- Random coefficient models (Statistics) --- Variance component models (Statistics) --- Mathematical models --- Regression analysis --- Models multinivell (Estadística)