Introduction to statistics and SPSS in psychology / / Andrew Mayers

• Record Nr.: UNINA9910150208003321
• Autore: Mayers Andrew
• Pubbl/distr/stampa: Harlow, England : , : Pearson, , [2013]; ©2013
• ISBN: 0-273-73102-5
• Edizione: [1st ed.]
• Descrizione fisica: 1 online resource (626 pages) : illustrations (some color)
• Collana: Always learning
• Disciplina: 150.15195
• Soggetti: Psychometrics; Psychology - Statistical methods
• 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 and index.
• Nota di contenuto: Cover -- Contents -- About the author -- Acknowledgements -- Publisher's acknowledgments -- Guided tour -- 1 Introduction -- Why I wrote this book - what's in it for you? -- Why do psychologists need to know about statistics? -- How this book is laid out - what you can expect -- Online resources -- 2 SPSS - the basics -- Learning objectives -- Introduction -- Viewing options in SPSS -- Defining variable parameters -- Entering data -- SPSS menus (and icons) -- Syntax -- Chapter summary -- Extended learning task -- 3 Normal distribution -- Learning objectives -- What is normal distribution? -- Measuring normal distribution -- Statistical assessment of normal distribution -- Adjusting non-normal data -- Homogeneity of between-group variance -- Sphericity of within-group variance -- Chapter summary -- Extended learning task -- 4 Significance, effect size and power -- Learning objectives -- Introduction -- Statistical significance -- Significance and hypotheses -- Measuring statistical significance -- Effect size -- Statistical power -- Measuring effect size and power using G*Power -- Chapter summary -- Extended learning task -- 5 Experimental methods - how to choose the correct statistical test -- Learning objectives -- Introduction -- Conducting 'experiments' in psychology -- Factors that determine the appropriate statistical test -- Exploring differences -- Examining relationships -- Validity and reliability -- Chapter summary -- Extended learning task -- 6 ; Correlation -- Learning objectives -- What is correlation? -- Theory and rationale -- Pearson's correlation -- Spearman's rank correlation -- Kendall's Tau-b -- Biserial (and point-biserial) correlation -- Partial correlation -- Semi-partial correlation -- Chapter summary -- Research example -- Extended learning task -- 7 Independent t-test -- Learning objectives -- What is a t-test?.; Theory and rationale -- How SPSS performs an independent t-test -- Interpretation of output -- Effect size and power -- Writing up results -- Presenting data graphically -- Chapter summary -- Research example -- Extended learning task -- 8 Related t-test -- Learning objectives -- What is the related t-test? -- Theory and rationale -- How SPSS performs the related t-test -- Interpretation of output -- Effect size and power -- Writing up results -- Presenting data graphically -- Chapter summary -- Research example -- Extended learning task -- 9 Independent one-way ANOVA -- Learning objectives -- Setting the scene: what is ANOVA? -- Theory and rationale -- How SPSS performs independent one-way ANOVA -- Interpretation of output -- Effect size and power -- Writing up results -- Presenting data graphically -- Chapter summary -- Research example -- Extended learning task -- 10 Repeated-measures one-way ANOVA -- Learning objectives -- What is repeated-measures one-way ANOVA? -- Theory and rationale -- How SPSS performs repeated-measures one-way ANOVA -- Interpretation of output -- Effect size and power -- Writing up results -- Presenting data graphically -- Chapter summary -- Research example -- Extended learning task -- 11 Independent multi-factorial ANOVA -- Learning objectives -- What is independent multi-factorial ANOVA? -- Theory and rationale -- How SPSS performs independent multi-factorial ANOVA -- Interpretation of output -- Effect size and power -- Writing up results -- Chapter summary -- Research example -- Extended learning task -- Appendix to Chapter 11: Exploring simple effects -- 12 Repeated-measures multi-factorial ANOVA -- Learning objectives -- What is repeated-measures multi-factorial ANOVA? -- Theory and rationale -- How SPSS performs repeated-measures multi-factorial ANOVA -- Effect size and power -- Writing up results -- Chapter summary.; Research example -- Extended learning task -- 13 Mixed multi-factorial ANOVA -- Learning objectives -- What is mixed multi-factorial ANOVA? -- Theory and rationale -- How SPSS performs mixed multi-factorial ANOVA -- Effect size and power -- Writing up results -- Chapter summary -- Research example -- Extended learning task -- 14 Multivariate analyses -- Learning objectives -- What are multivariate analyses? -- What is MANOVA? -- Theory and rationale -- How SPSS performs MANOVA -- Interpretation of output -- Effect size and power -- Writing up results -- Presenting data graphically -- Repeated-measures MANOVA -- Theory and rationale -- How SPSS performs repeated-measures MANOVA -- Interpretation of output -- Effect size and power -- Writing up results -- Chapter summary -- Research example (MANOVA) -- Research example (repeated-measures MANOVA) -- Extended learning tasks -- Appendix to Chapter 14: Manual calculations for MANOVA -- 15 Analyses of covariance -- Learning objectives -- What are analyses of covariance? -- What is ANCOVA? -- Theory and rationale -- How SPSS performs ANCOVA -- Effect size and power -- Writing up results -- MANCOVA: multivariate analysis of covariance -- How SPSS performs MANCOVA -- Effect size and power -- Writing up results -- Chapter summary -- Research examples -- Extended learning tasks -- Appendix to Chapter 15: Mathematics behind (univariate) ANCOVA -- 16 Linear and multiple linear regression -- Learning objectives -- What is linear regression? -- ; Theory and rationale -- Simple linear regression -- Effect size and power -- Writing up results -- Multiple linear regression -- How SPSS performs multiple linear regression -- Chapter summary -- Research example -- Extended learning task -- Appendix to Chapter 16: Calculating multiple linear regression manually -- 17 Logistic regression -- Learning objectives.; What is (binary) logistic regression? -- Theory and rationale -- How SPSS performs logistic regression -- Writing up results -- Chapter summary -- Research example -- Extended learning task -- 18 Non-parametric tests -- Learning objectives -- Introduction -- Common issues in non-parametric tests -- Mann-Whitney U test -- How SPSS performs the Mann-Whitney U -- Wilcoxon signed-rank test -- How SPSS performs the Wilcoxon signed-rank test -- Kruskal-Wallis test -- How SPSS performs Kruskal-Wallis -- Friedman's ANOVA -- How SPSS performs Friedman's ANOVA -- Chapter summary -- 19 Tests for categorical variables -- Learning objectives -- What are tests for categorical variables? -- Theory and rationale -- Measuring outcomes statistically -- Categorical tests with more than two variables -- Loglinear analysis when saturated model is rejected -- Chapter summary -- Research example -- Extended learning task -- 20 Factor analysis -- Learning objectives -- What is factor analysis? -- Theory and rationale -- How SPSS performs principal components analysis -- Writing up results -- Chapter summary -- Research example -- Extended learning task -- 21 Reliability analysis -- Learning objectives -- What is reliability analysis? -- Theory and rationale -- How SPSS performs reliability analysis -- Writing up results -- Chapter summary -- Research example -- Extended learning task -- Appendix 1: Normal distribution (z-score) table -- Appendix 2: t-distribution table -- Appendix 3: r-distribution table -- Appendix 4: F-distribution table -- Appendix 5: U-distribution table -- Appendix 6: Chi-square ( X[sup(2)]) distribution table -- References -- Glossary -- Index -- A -- B -- C -- D -- E -- F -- G -- H -- I -- J -- K -- L -- M -- N -- O -- P -- Q -- R.; S -- T -- U -- V -- W -- Y -- Z.
• Sommario/riassunto: Introduction to Statistics and SPSS in Psychology guides the reader carefully and concisely up the statistics staircase to success. Each step is supported by helpful visuals as well as advice on how to overcome problems. Interactive, lively, but never patronising, this is the complete guide to statistics that will take readers through their degree course from beginning to end. Take a step in the right direction and tackle statistics head on with this visual introduction.

From Quantum to Classical : Essays in Honour of H.-Dieter Zeh / / edited by Claus Kiefer

• Record Nr.: UNINA9910552734103321
• Autore: Kiefer Claus
• Pubbl/distr/stampa: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022
• ISBN: 9783030887810; 9783030887803
• Edizione: [1st ed. 2022.]
• Descrizione fisica: 1 online resource (314 pages)
• Collana: Fundamental Theories of Physics, , 2365-6425 ; ; 204
• Disciplina: 530.12
• Soggetti: Quantum theory; Physics - Philosophy; Science - Philosophy; Quantum Physics; Philosophical Foundations of Physics and Astronomy; Philosophy of Science
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di contenuto: H. Dieter Zeh and the History of the Foundations of Quantum Mechanics -- Emergence of the Classical World from within our Quantum Universe -- Decoherence: From Interpretation to Experiment -- Experimental decoherence in molecule interferometry -- When Zeh meets Feynman: how to avoid the appearance of a classical world in gravity experiments -- Preferred basis, decoherence and the quantum state of the Universe -- Wave Function First - H.D. Zeh and the Foundations of Physics -- Geometrodynamics as Functionalism about Time -- Quantum Hierarchical Systems: Fluctuation Force by Coarse-Graining, Decoherence by Correlation Noise -- Decoherence and the puzzle of quantum Brownian motion in a gas -- On the statistical viewpoint concerning the second law of thermodynamics — a reminder on the Ehrenfests’ urn model -- Explanation, the Progress of Physical Theories and Computer Simulations -- Searching for Dieter Zeh.
• Sommario/riassunto: Quantum theory is at the foundation of the physical description of our world. One of the people who contributed significantly to our ; conceptual understanding of this theory was Heinz-Dieter Zeh (1932-2018). He was the pioneer of the process of decoherence, through which the classical appearance of our world can be understood. This volume presents a collection of essays dedicated to his memory, written by distinguished scientists and scholars. They cover all aspects of the interpretation of quantum theory in general and the quantum-to-classical transition in particular. This volume provides illuminating reading to anyone seeking a deep understanding of quantum theory and its relevance to the foundations of physics.