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Author:
Publisher:
ISBN: 9781878477538
Category : College attendance
Languages : en
Pages : 55
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Book Description
"The report examines retention and degree attainment of 210,056 first-time, full-time students at 356 four-year non-profit institutions, using a combination of CIRP (Cooperative Institutional Research Program) Freshman Survey data and student graduation data from the National Student Clearinghouse"--Publisher's web site.
Author:
Publisher:
ISBN: 9781878477538
Category : College attendance
Languages : en
Pages : 55
Get Book Here
Book Description
"The report examines retention and degree attainment of 210,056 first-time, full-time students at 356 four-year non-profit institutions, using a combination of CIRP (Cooperative Institutional Research Program) Freshman Survey data and student graduation data from the National Student Clearinghouse"--Publisher's web site.
Author: Karen L. Webber
Publisher: Johns Hopkins University Press
ISBN: 1421439034
Category : Education
Languages : en
Pages : 337
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Book Description
Webber, Henry Y. Zheng, Ying Zhou
Author: Charles M. Judd
Publisher: Routledge
ISBN: 1317591216
Category : Psychology
Languages : en
Pages : 379
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Book Description
Data Analysis: A Model Comparison Approach to Regression, ANOVA, and Beyond is an integrated treatment of data analysis for the social and behavioral sciences. It covers all of the statistical models normally used in such analyses, such as multiple regression and analysis of variance, but it does so in an integrated manner that relies on the comparison of models of data estimated under the rubric of the general linear model. Data Analysis also describes how the model comparison approach and uniform framework can be applied to models that include product predictors (i.e., interactions and nonlinear effects) and to observations that are nonindependent. Indeed, the analysis of nonindependent observations is treated in some detail, including models of nonindependent data with continuously varying predictors as well as standard repeated measures analysis of variance. This approach also provides an integrated introduction to multilevel or hierarchical linear models and logistic regression. Finally, Data Analysis provides guidance for the treatment of outliers and other problematic aspects of data analysis. It is intended for advanced undergraduate and graduate level courses in data analysis and offers an integrated approach that is very accessible and easy to teach. Highlights of the third edition include: a new chapter on logistic regression; expanded treatment of mixed models for data with multiple random factors; updated examples; an enhanced website with PowerPoint presentations and other tools that demonstrate the concepts in the book; exercises for each chapter that highlight research findings from the literature; data sets, R code, and SAS output for all analyses; additional examples and problem sets; and test questions.
Author: Vinit Kumar Gunjan
Publisher: Springer Nature
ISBN: 3030682919
Category : Technology & Engineering
Languages : en
Pages : 515
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Book Description
This book provides a systematic and comprehensive overview of machine learning with cognitive science methods and technologies which have played an important role at the core of practical solutions for a wide scope of tasks between handheld apps, industrial process control, autonomous vehicles, environmental policies, life sciences, playing computer games, computational theory, and engineering development. The chapters in this book focus on readers interested in machine learning, cognitive and neuro-inspired computational systems – theories, mechanisms, and architecture, which underline human and animal behaviour, and their application to conscious and intelligent systems. In the current version, it focuses on the successful implementation and step-by-step explanation of practical applications of the domain. It also offers a wide range of inspiring and interesting cutting-edge contributions to applications of machine learning and cognitive science such as healthcare products, medical electronics, and gaming. Overall, this book provides valuable information on effective, cutting-edge techniques and approaches for students, researchers, practitioners, and academicians working in the field of AI, neural network, machine learning, and cognitive science. Furthermore, the purpose of this book is to address the interests of a broad spectrum of practitioners, students, and researchers, who are interested in applying machine learning and cognitive science methods in their respective domains.
Author: Debbie L. Hahs-Vaughn
Publisher: Routledge
ISBN: 1000124436
Category : Psychology
Languages : en
Pages : 782
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Book Description
Statistical Concepts—A Second Course presents the last 10 chapters from An Introduction to Statistical Concepts, Fourth Edition. Designed for second and upper-level statistics courses, this book highlights how statistics work and how best to utilize them to aid students in the analysis of their own data and the interpretation of research results. In this new edition, Hahs-Vaughn and Lomax discuss sensitivity, specificity, false positive and false negative errors. Coverage of effect sizes has been expanded upon and more organizational features (to summarize key concepts) have been included. A final chapter on mediation and moderation has been added for a more complete presentation of regression models. In addition to instructions and screen shots for using SPSS, new to this edition is annotated script for using R. This book acts as a clear and accessible instructional tool to help readers fully understand statistical concepts and how to apply them to data. It is an invaluable resource for students undertaking a course in statistics in any number of social science and behavioral science disciplines.
Author: Bovas Abraham
Publisher: John Wiley & Sons
ISBN: 0470317299
Category : Mathematics
Languages : en
Pages : 474
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Book Description
The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "This book, it must be said, lives up to the words on its advertising cover: 'Bridging the gap between introductory, descriptive approaches and highly advanced theoretical treatises, it provides a practical, intermediate level discussion of a variety of forecasting tools, and explains how they relate to one another, both in theory and practice.' It does just that!" -Journal of the Royal Statistical Society "A well-written work that deals with statistical methods and models that can be used to produce short-term forecasts, this book has wide-ranging applications. It could be used in the context of a study of regression, forecasting, and time series analysis by PhD students; or to support a concentration in quantitative methods for MBA students; or as a work in applied statistics for advanced undergraduates." -Choice Statistical Methods for Forecasting is a comprehensive, readable treatment of statistical methods and models used to produce short-term forecasts. The interconnections between the forecasting models and methods are thoroughly explained, and the gap between theory and practice is successfully bridged. Special topics are discussed, such as transfer function modeling; Kalman filtering; state space models; Bayesian forecasting; and methods for forecast evaluation, comparison, and control. The book provides time series, autocorrelation, and partial autocorrelation plots, as well as examples and exercises using real data. Statistical Methods for Forecasting serves as an outstanding textbook for advanced undergraduate and graduate courses in statistics, business, engineering, and the social sciences, as well as a working reference for professionals in business, industry, and government.
Author:
Publisher:
ISBN:
Category : Education
Languages : en
Pages : 288
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Book Description
Author:
Publisher: DIANE Publishing
ISBN: 1428926461
Category :
Languages : en
Pages : 103
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Book Description
Author: Jay L. Devore
Publisher: Springer Nature
ISBN: 3030551563
Category : Mathematics
Languages : en
Pages : 981
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Book Description
This 3rd edition of Modern Mathematical Statistics with Applications tries to strike a balance between mathematical foundations and statistical practice. The book provides a clear and current exposition of statistical concepts and methodology, including many examples and exercises based on real data gleaned from publicly available sources. Here is a small but representative selection of scenarios for our examples and exercises based on information in recent articles: Use of the “Big Mac index” by the publication The Economist as a humorous way to compare product costs across nations Visualizing how the concentration of lead levels in cartridges varies for each of five brands of e-cigarettes Describing the distribution of grip size among surgeons and how it impacts their ability to use a particular brand of surgical stapler Estimating the true average odometer reading of used Porsche Boxsters listed for sale on www.cars.com Comparing head acceleration after impact when wearing a football helmet with acceleration without a helmet Investigating the relationship between body mass index and foot load while running The main focus of the book is on presenting and illustrating methods of inferential statistics used by investigators in a wide variety of disciplines, from actuarial science all the way to zoology. It begins with a chapter on descriptive statistics that immediately exposes the reader to the analysis of real data. The next six chapters develop the probability material that facilitates the transition from simply describing data to drawing formal conclusions based on inferential methodology. Point estimation, the use of statistical intervals, and hypothesis testing are the topics of the first three inferential chapters. The remainder of the book explores the use of these methods in a variety of more complex settings. This edition includes many new examples and exercises as well as an introduction to the simulation of events and probability distributions. There are more than 1300 exercises in the book, ranging from very straightforward to reasonably challenging. Many sections have been rewritten with the goal of streamlining and providing a more accessible exposition. Output from the most common statistical software packages is included wherever appropriate (a feature absent from virtually all other mathematical statistics textbooks). The authors hope that their enthusiasm for the theory and applicability of statistics to real world problems will encourage students to pursue more training in the discipline.
Author: Matthew J. Mayhew
Publisher: John Wiley & Sons
ISBN: 1119101972
Category : Education
Languages : en
Pages : 784
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Book Description
The bestselling analysis of higher education's impact, updated with the latest data How College Affects Students synthesizes over 1,800 individual research investigations to provide a deeper understanding of how the undergraduate experience affects student populations. Volume 3 contains the findings accumulated between 2002 and 2013, covering diverse aspects of college impact, including cognitive and moral development, attitudes and values, psychosocial change, educational attainment, and the economic, career, and quality of life outcomes after college. Each chapter compares current findings with those of Volumes 1 and 2 (covering 1967 to 2001) and highlights the extent of agreement and disagreement in research findings over the past 45 years. The structure of each chapter allows readers to understand if and how college works and, of equal importance, for whom does it work. This book is an invaluable resource for administrators, faculty, policymakers, and student affairs practitioners, and provides key insight into the impact of their work. Higher education is under more intense scrutiny than ever before, and understanding its impact on students is critical for shaping the way forward. This book distills important research on a broad array of topics to provide a cohesive picture of student experiences and outcomes by: Reviewing a decade's worth of research; Comparing current findings with those of past decades; Examining a multifaceted analysis of higher education's impact; and Informing policy and practice with empirical evidence Amidst the current introspection and skepticism surrounding higher education, there is a massive body of research that must be synthesized to enhance understanding of college's effects. How College Affects Students compiles, organizes, and distills this information in one place, and makes it available to research and practitioner audiences; Volume 3 provides insight on the past decade, with the expert analysis characteristic of this seminal work.
