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Estadística matemàtica --- R (Llenguatge de programació) --- Permutacions --- Àlgebra --- Anàlisi combinatòria --- Grups de permutacions --- GNU-S (Llenguatge de programació) --- Llenguatges de programació --- Estadística descriptiva --- Inferència estadística --- Matemàtica estadística --- Mètodes estadístics --- Estadística --- 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) --- Mathematical statistics. --- Mathematics --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Statistical methods --- R (Computer program language). --- GNU-S (Computer program language) --- Domain-specific programming languages --- R (Computer program language)

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Most commonly-used parametric and permutation statistical tests, such as the matched-pairs t test and analysis of variance, are based on non-metric squared distance functions that have very poor robustness characteristics. This second edition places increased emphasis on the use of alternative permutation statistical tests based on metric Euclidean distance functions that have excellent robustness characteristics. These alternative permutation techniques provide many powerful multivariate tests including multivariate multiple regression analyses. In addition to permutation techniques described in the first edition, this second edition also contains various new permutation statistical methods and studies that include resampling multiple contingency table analyses, analysis concerns involving log-linear models with small samples, an exact discrete analog of Fisher’s continuous method for combining P-values that arise from small data sets, multiple dichotomous response analyses, problems regarding Fisher’s Z transformation for correlation analyses, and multivariate similarity comparisons between corresponding multiple categories of two samples. Paul W. Mielke, Jr. is Professor of Statistics at Colorado State University, and a fellow of the American Statistical Association. Kenneth J. Berry is Professor of Sociology at Colorado State University.

Statistical hypothesis testing. --- Resampling (Statistics) --- Resampling methods (Statistics) --- Nonparametric statistics --- Hypothesis testing (Statistics) --- Significance testing (Statistics) --- Statistical significance testing --- Testing statistical hypotheses --- Distribution (Probability theory) --- Hypothesis --- Mathematical statistics --- Distribution (Probability theory. --- Mathematical statistics. --- Biometrics. --- Data mining. --- Psychometrics. --- Probability Theory and Stochastic Processes. --- Statistical Theory and Methods. --- Data Mining and Knowledge Discovery. --- Public Health. --- Measurement, Mental --- Measurement, Psychological --- Psychological measurement --- Psychological scaling --- Psychological statistics --- Psychology --- Psychometry (Psychophysics) --- Scaling, Psychological --- Psychological tests --- Scaling (Social sciences) --- Mathematics --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Distribution functions --- Frequency distribution --- Characteristic functions --- Measurement --- Scaling --- Methodology --- Statistical methods --- Probabilities. --- Statistics . --- Biometrics (Biology). --- Public health. --- Biological statistics --- Biology --- Biometrics (Biology) --- Biostatistics --- Biomathematics --- Statistical analysis --- Statistical data --- Statistical science --- Econometrics --- Community health --- Health services --- Hygiene, Public --- Hygiene, Social --- Public health services --- Public hygiene --- Social hygiene --- Health --- Human services --- Biosecurity --- Health literacy --- Medicine, Preventive --- National health services --- Sanitation --- Probability --- Combinations --- Chance --- Least squares --- Risk --- Statistical hypothesis testing

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The primary purpose of this book is to introduce the reader to a wide variety of interesting and useful connections, relationships, and equivalencies between and among conventional and permutation statistical methods. There are approximately 320 statistical connections and relationships described in this book. For each connection or connections the tests are described, the connection is explained, and an example analysis illustrates both the tests and the connection(s). The emphasis is more on demonstrations than on proofs, so little mathematical expertise is assumed. While the book is intended as a stand-alone monograph, it can also be used as a supplement to a standard textbook such as might be used in a second- or third-term course in conventional statistical methods. Students, faculty, and researchers in the social, natural, or hard sciences will find an interesting collection of statistical connections and relationships - some well-known, some more obscure, and some presented here for the first time.

Statistics. --- History. --- Statistical Theory and Methods. --- History of Statistics. --- Estadística matemàtica

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The primary purpose of this book is to introduce the reader to a wide variety of interesting and useful connections, relationships, and equivalencies between and among conventional and permutation statistical methods. There are approximately 320 statistical connections and relationships described in this book. For each connection or connections the tests are described, the connection is explained, and an example analysis illustrates both the tests and the connection(s). The emphasis is more on demonstrations than on proofs, so little mathematical expertise is assumed. While the book is intended as a stand-alone monograph, it can also be used as a supplement to a standard textbook such as might be used in a second- or third-term course in conventional statistical methods. Students, faculty, and researchers in the social, natural, or hard sciences will find an interesting collection of statistical connections and relationships - some well-known, some more obscure, and some presented here for the first time.

Statistics. --- History. --- Statistical Theory and Methods. --- History of Statistics. --- Estadística matemàtica

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The focus of this book is on the birth and historical development of permutation statistical methods from the early 1920s to the near present. Beginning with the seminal contributions of R.A. Fisher, E.J.G. Pitman, and others in the 1920s and 1930s, permutation statistical methods were initially introduced to validate the assumptions of classical statistical methods. Permutation methods have advantages over classical methods in that they are optimal for small data sets and non-random samples, are data-dependent, and are free of distributional assumptions. Permutation probability values may be exact, or estimated via moment- or resampling-approximation procedures. Because permutation methods are inherently computationally-intensive, the evolution of computers and computing technology that made modern permutation methods possible accompanies the historical narrative. Permutation analogs of many well-known statistical tests are presented in a historical context, including multiple correlation and regression, analysis of variance, contingency table analysis, and measures of association and agreement. A non-mathematical approach makes the text accessible to readers of all levels.

Resampling (Statistics) --- Statistical hypothesis testing. --- Hypothesis testing (Statistics) --- Significance testing (Statistics) --- Statistical significance testing --- Testing statistical hypotheses --- Distribution (Probability theory) --- Hypothesis --- Mathematical statistics --- Resampling methods (Statistics) --- Nonparametric statistics --- Statistics. --- Statistics, general. --- History of Mathematical Sciences. --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Mathematics --- Econometrics --- Statistics . --- Mathematics. --- History. --- Annals --- Auxiliary sciences of history --- Math --- Science