Stereotyping as inductive hypothesis testing / / Klaus Fiedler & Eva Walther

• Record Nr.: UNINA9910450741503321
• Autore: Fiedler Klaus <1951, >
• Pubbl/distr/stampa: Hove ; ; New York : , : Psychology Press, , 2004
• ISBN: 1-135-47105-3; 1-280-07741-7; 0-203-64153-1; 0-86377-832-1
• Descrizione fisica: x, 198 p. : ill
• Altri autori (Persone): WaltherEva <1964->
• Disciplina: 303.3/85/072
• Soggetti: Stereotypes (Social psychology); Hypothesis; Social sciences - Research - Methodology; Electronic books.
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Bibliographic Level Mode of Issuance: Monograph
• Nota di bibliografia: Includes bibliographical references (p. [171]-186) and indexes.
• Nota di contenuto: The topic of social hypothesis testing -- Stereotyping as a cognitive-environmental learning process : delineating the conceptual framework -- Learning of social hypotheses stereotypes as illusory correlations -- The auto-verification of social hypotheses -- Information search in the "inner world" : the origin of stereotypes in memory -- Testing social hypotheses in tri-variate problem space : further variants of environmental stereotype learning -- Explicit and implicit hypothesis testing in a complex environment -- The vicissitudes of information sampling in a fallible environment : an integrative framework -- Epilogue: Locating CELA in modern stereotype research.

Scientific Computing : Vol. III - Approximation and Integration / / by John A. Trangenstein

• Record Nr.: UNINA9910279754603321
• Autore: Trangenstein J. A (John Arthur), <1949->
• Pubbl/distr/stampa: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
• ISBN: 3-319-69110-4
• Edizione: [1st ed. 2017.]
• Descrizione fisica: 1 online resource (XXV, 592 p. 42 illus., 40 illus. in color.)
• Collana: Texts in Computational Science and Engineering, , 1611-0994 ; ; 20
• Disciplina: 511.4
• Soggetti: Computer science - Mathematics; Differential equations; Mathematical optimization; Computational Mathematics and Numerical Analysis; Ordinary Differential Equations; Optimization
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di bibliografia: Includes bibliographical references and indexes.
• Nota di contenuto: 1. Interpolation and Approximation -- Differentiation and Integration -- Initial Value Problems -- Boundary Value Problems -- References -- Author Index.
• Sommario/riassunto: This is the third of three volumes providing a comprehensive presentation of the fundamentals of scientific computing. This volume discusses topics that depend more on calculus than linear algebra, in order to prepare the reader for solving differential equations. This book and its companions show how to determine the quality of computational results, and how to measure the relative efficiency of competing methods. Readers learn how to determine the maximum attainable accuracy of algorithms, and how to select the best method for computing problems. This book also discusses programming in several languages, including C++, Fortran and MATLAB. There are 90 examples, 200 exercises, 36 algorithms, 40 interactive JavaScript programs, 91 references to software programs and 1 case study. Topics are introduced with goals, literature references and links to public software. There are descriptions of the current algorithms in ; GSLIB and MATLAB. This book could be used for a second course in numerical methods, for either upper level undergraduates or first year graduate students. Parts of the text could be used for specialized courses, such as nonlinear optimization or iterative linear algebra.