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Contrasts are statistical procedures for asking focused questions of data. Compared to diffuse or omnibus questions, focused questions are characterized by greater conceptual clarity and greater statistical power when examining those focused questions. If an effect truly exists, we are more likely to discover it and to believe it to be real when asking focused questions rather than omnibus ones. Researchers, teachers of research methods and graduate students will be familiar with the principles and procedures of contrast analysis, but will also be introduced to a series of newly developed concepts, measures, and indices that permit a wider and more useful application of contrast analysis. This volume takes on this new approach by introducing a family of correlational effect size estimates.

Analysis of variance. --- Psychology --- Psychometrics. --- Social sciences --- Methoden en technieken --- Statistical methods. --- statistiek. --- Psychometrics --- Analysis of variance --- Psychométrie --- Analyse de variance --- Psychologie --- Sciences sociales --- Statistical methods --- Méthodes statistiques --- #PBIB:2000.2 --- Measurement, Mental --- Measurement, Psychological --- Psychological measurement --- Psychological scaling --- Psychological statistics --- Psychometry (Psychophysics) --- Scaling, Psychological --- Psychological tests --- Scaling (Social sciences) --- ANOVA (Analysis of variance) --- Variance analysis --- Mathematical statistics --- Experimental design --- Measurement --- Scaling --- Methodology --- Health Sciences --- Psychiatry & Psychology

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519.2 --- Experimental design --- Design of experiments --- Statistical design --- Mathematical optimization --- Research --- Science --- Statistical decision --- Statistics --- Analysis of means --- Analysis of variance --- Probability. Mathematical statistics --- Experiments --- Methodology --- Experimental design. --- 519.2 Probability. Mathematical statistics

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This text stands apart from other books on experiment design. It presents theory and methods, emphasizes both the design selection for an experiment and the analysis of data, and integrates the analysis for the various designs with the general theory for linear models. It begins with a general introduction to the subject, then leads readers through the theoretical results, the various design models, and the analytical concepts that provide the techniques that enable them to analyze virtually any design. Rife with examples and exercises illustrating its concepts, the text also encourages using computers to analyze data. It features the SAS software package, but also demonstrate how any regression program can be used for analysis. With its balanced, integrated presentation of theory, methods, and applications, criteria for selecting the appropriate experimental design, and clear, highly readable style, A First Course in the Design of Experiments proves ideal as both a reference and a text.

Mathematical statistics --- 519.2 --- Experimental design --- Linear models (Statistics) --- Models, Linear (Statistics) --- Mathematical models --- Statistics --- Design of experiments --- Statistical design --- Mathematical optimization --- Research --- Science --- Statistical decision --- Analysis of means --- Analysis of variance --- Probability. Mathematical statistics --- Experiments --- Methodology --- Experimental design. --- Basic Sciences. Statistics --- Experimental Design --- Linear models (Statistics). --- Experimental Design. --- 519.2 Probability. Mathematical statistics

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Multivariate statistics and mathematical models provide flexible and powerful tools essential in most disciplines. Nevertheless, many practicing researchers lack an adequate knowledge of these techniques, or did once know the techniques, but have not been able to keep abreast of new developments. The Handbook of Applied Multivariate Statistics and Mathematical Modeling explains the appropriate uses of multivariate procedures and mathematical modeling techniques, and prescribe practices that enable applied researchers to use these procedures effectively without needing to concern themsel

Mathematical statistics --- Mathematical models. --- Multivariate analysis. --- Mathematical models --- Multivariate analysis --- 519.535 --- #SBIB:002.AANKOOP --- #SBIB:303H510 --- #SBIB:303H520 --- 519.2 --- 519.2 Probability. Mathematical statistics --- Probability. Mathematical statistics --- Multivariate distributions --- Multivariate statistical analysis --- Statistical analysis, Multivariate --- Analysis of variance --- Matrices --- Models, Mathematical --- Simulation methods --- Methoden sociale wetenschappen: statistische technieken, algemeen --- Methoden sociale wetenschappen: techniek van de analyse, algemeen

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Quantitative methods in social research --- Mathematical statistics --- Social psychology --- Multivariate analysis --- Psychometrics --- Measurement, Mental --- Measurement, Psychological --- Psychological measurement --- Psychological scaling --- Psychological statistics --- Psychology --- Psychometry (Psychophysics) --- Scaling, Psychological --- Psychological tests --- Scaling (Social sciences) --- Multivariate distributions --- Multivariate statistical analysis --- Statistical analysis, Multivariate --- Analysis of variance --- Matrices --- Measurement --- Scaling --- Methodology --- Multivariate analysis. --- Psychometrics.