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Quantitative Psychology
Authors: --- --- --- --- --- et al.
ISBN: 9783031555480 9783031555473 9783031555497 9783031555503 Year: 2024 Publisher: Cham Springer Nature Switzerland :Imprint: Springer

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This book includes presentations given at the 88th annual meeting of the Psychometric Society, held in Maryland, USA on July 24–28, 2023. The proceeding covers a diverse set of psychometric topics. The topics include, but are not limited to item response theory, cognitive diagnostic models, Bayesian estimation, validity and reliability issues, and several applications within different fields. The authors are from all over the world, they work in different psychometrics areas, as well as having diverse professional and academic experiences.


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Make Your Data Speak
Authors: ---
ISBN: 9781484289426 9781484289419 9781484289433 9781484299340 1484289420 Year: 2023 Publisher: Berkeley, CA Apress :Imprint: Apress

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Gather and analyze data successfully, identify trends, and then create overarching strategies and actionable next steps - all through Excel. This book will show even those who lack a technical background how to make advanced interactive reports with only Excel at hand. Advanced visualization is available to everyone, and this step-by-step guide will show you how. The information in this book is presented in an accessible and understandable way for everyone, regardless of the level of technical skills and proficiency in MS Excel. The dashboard development process is given in the format of step-by-step instructions, taking you through each step in detail. Universal checklists and recommendations of a practicing business analyst and trainer will help in solving various tasks when working with data visualization. Illustrations will help you perceive information easily and quickly. Make Your Data Speak will show you how to master the main rules, techniques and tricks of professional data visualization in just a few days. You will: See how interactive dashboards can be useful for a business Review basic rules for building dashboards Understand why it's important to pay attention to colors and fonts when developing a dashboard Create interactive management reports in Excel .


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Large sample techniques for statistics
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ISBN: 9783030916954 9783030916947 9783030916961 9783030916978 3030916979 3030916944 Year: 2022 Publisher: Cham: Springer,

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This book offers a comprehensive guide to large sample techniques in statistics. With a focus on developing analytical skills and understanding motivation, Large Sample Techniques for Statistics begins with fundamental techniques, and connects theory and applications in engaging ways. The first five chapters review some of the basic techniques, such as the fundamental epsilon-delta arguments, Taylor expansion, different types of convergence, and inequalities. The next five chapters discuss limit theorems in specific situations of observational data. Each of the first ten chapters contains at least one section of case study. The last six chapters are devoted to special areas of applications. This new edition introduces a final chapter dedicated to random matrix theory, as well as expanded treatment of inequalities and mixed effects models. The book's case studies and applications-oriented chapters demonstrate how to use methods developed from large sample theory in real world situations. The book is supplemented by a large number of exercises, giving readers opportunity to practice what they have learned. Appendices provide context for matrix algebra and mathematical statistics. The Second Edition seeks to address new challenges in data science. This text is intended for a wide audience, ranging from senior undergraduate students to researchers with doctorates. A first course in mathematical statistics and a course in calculus are prerequisites..


Book
Machine learning : a probabilistic perspective
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ISBN: 9780262018029 0262018020 0262305240 0262304325 9780262305242 9780262304320 Year: 2012 Publisher: Cambridge (Mass.): MIT Press,

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Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach. The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package--PMTK (probabilistic modeling toolkit)--that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.


Multi
Unity from Diversity
Authors: ---
ISBN: 9789819734627 9789819734610 9789819734634 9789819734641 Year: 2024 Publisher: Singapore Springer Nature Singapore :Imprint: Springer

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This book is about the choices that researchers can make when building knowledge in social and behavioural spaces. Knowledge is the unity we seek and, given that social and behavioural research is a human endeavour focusing on human lives and experiences, there are diverse and ever-evolving pathways towards achieving that unity. Any one pathway will only ever yield partial glimpses into human life and diversity of potential choices serves to enrich, expand, and enlarge those glimpses in pursuit of more complete understanding. The book shows that researchers and the researched are far more connected than disconnected in this world and those connections are spread out through a network of interlinked complex systems. The book argues that pluralist systemic thinking provides the means by which a researcher’s methodological choices for navigating the ‘Data Triangle’ (comprising data source, data gathering, and data analysis strategies) and the learning they provide can be fully and robustly contextualised with respect to those systems and the expectations and influences that emerge from them. Such contextualisations facilitate the refinement, augmentation, and/or narrowing of those choices during the researcher’s journey. Anticipating choices downstream may have implications for more immediate choices and more immediate choices may create a cascade of necessary downstream choices. An essential part of contextualisation involves making choices about patterns of guiding assumptions, modes of knowledge building, and research frames. Researchers must develop the capacity to be flexible and adapt to unanticipated emergent events, obstacles, and political influences, making trade-offs where necessary throughout their research journey, always with an eye on both feasibility and quality. Importantly, research has no meaning unless the researcher can ensure that it connects with intended audiences via specific research outcomes, especially since the ultimate judgments about the convincingness, meaningfulness, quality, and utility of the research are vested in those audiences. Throughout the book, special attention is devoted to the role(s) that stakeholders and gatekeepers play in shaping the researcher’s journey as well as to what can be learned from Indigenous/First Nations perspectives on social and behavioural research.


Book
Sampling for microbiological analysis: principles and specific applications
Author:
ISBN: 0632015675 Year: 1986 Publisher: Oxford Blackwell Scientific Publications


Periodical
Journal of probability and statistics.
ISSN: 1687952X 16879538 Year: 2009 Publisher: New York, N.Y. : Hindawi Pub. Corp.


Periodical
Advances in data analysis and classification
ISSN: 18625355 18625347 Year: 2007 Publisher: Berlin Springer


Periodical
International Journal of Quality Innovation.
ISSN: 23637021 Publisher: Heidelberg : Springer

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