Download or read book Statistics for the Social Sciences written by R. Mark Sirkin and published by SAGE. This book was released on 2006 with total page 636 pages. Available in PDF, EPUB and Kindle. Book excerpt: Do your students lack confidence in their ability to handle quantitative work? Do they get confused about how to enter statistical data on SAS, SPSS, and Excel programs? The new Third Edition of the bestselling Statistics for the Social Sciences is the solution to these dilemmas Popular in previous editions, this Third Edition continues to help build students' confidence and ability in doing statistical analysis by slowly moving from concepts that require little computational work to those that require more. Author R. Mark Sirkin once again demonstrates how statistics can be used so that students come to appreciate their usefulness rather than fearing them. Statistics for the Social Sciences emphasizes the analysis and interpretation of data to give students a feel for how data interpretation is related to the methods by which the information was obtained. The book includes lists of key concepts, chapter exercises, topic boxes, and more

Download or read book Statistics for the Social Sciences written by Russell T. Warne and published by Cambridge University Press. This book was released on 2020-12-17 with total page 612 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second edition of Statistics for the Social Sciences prepares students from a wide range of disciplines to interpret and learn the statistical methods critical to their field of study. By using the General Linear Model (GLM), the author builds a foundation that enables students to see how statistical methods are interrelated enabling them to build on the basic skills. The author makes statistics relevant to students' varying majors by using fascinating real-life examples from the social sciences. Students who use this edition will benefit from clear explanations, warnings against common erroneous beliefs about statistics, and the latest developments in the philosophy, reporting, and practice of statistics in the social sciences. The textbook is packed with helpful pedagogical features including learning goals, guided practice, and reflection questions.

Download or read book Data Analysis for Social Science written by Elena Llaudet and published by Princeton University Press. This book was released on 2022-11-29 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Data analysis has become a necessary skill across the social sciences, and recent advancements in computing power have made knowledge of programming an essential component. Yet most data science books are intimidating and overwhelming to a non-specialist audience, including most undergraduates. This book will be a shorter, more focused and accessible version of Kosuke Imai's Quantitative Social Science book, which was published by Princeton in 2018 and has been adopted widely in graduate level courses of the same title. This book uses the same innovative approach as Quantitative Social Science , using real data and 'R' to answer a wide range of social science questions. It assumes no prior knowledge of statistics or coding. It starts with straightforward, simple data analysis and culminates with multivariate linear regression models, focusing more on the intuition of how the math works rather than the math itself. The book makes extensive use of data visualizations, diagrams, pictures, cartoons, etc., to help students understand and recall complex concepts, provides an easy to follow, step-by-step template of how to conduct data analysis from beginning to end, and will be accompanied by supplemental materials in the appendix and online for both students and instructors"--

Download or read book Statistics for Social Sciences written by T. Rajaretnam and published by SAGE Publishing India. This book was released on 2015-12-08 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive guide to the practical applications of statistics in social sciences This book brings out the relevance of statistical tools and methods in social sciences. Describing the various statistical techniques, it highlights their purpose and application along with a brief overview on how to interpret results and draw inferences. Topical and up-to-date, it examines: • different types of statistical variables and their treatment • tabulation and graphical presentation of data • theoretical distributions and common parametric and non-parametric tests, including analysis of variance and correlation ratio • linear regression including checking for violation of assumptions, transformations of variables and predictions • inequality measures such as Lorenz curve, Gini coefficient, dissimilarity index and human development index among others. It will be indispensable for students and scholars of statistics, econometrics, psychology and those interested in the application of statistics in social sciences.

Download or read book Basic Statistics for Social Research written by Robert A. Hanneman and published by John Wiley & Sons. This book was released on 2012-12-04 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: A core statistics text that emphasizes logical inquiry, not math Basic Statistics for Social Research teaches core general statistical concepts and methods that all social science majors must master to understand (and do) social research. Its use of mathematics and theory are deliberately limited, as the authors focus on the use of concepts and tools of statistics in the analysis of social science data, rather than on the mathematical and computational aspects. Research questions and applications are taken from a wide variety of subfields in sociology, and each chapter is organized around one or more general ideas that are explained at its beginning and then applied in increasing detail in the body of the text. Each chapter contains instructive features to aid students in understanding and mastering the various statistical approaches presented in the book, including: Learning objectives Check quizzes after many sections and an answer key at the end of the chapter Summary Key terms End-of-chapter exercises SPSS exercises (in select chapters) Ancillary materials for both the student and the instructor are available and include a test bank for instructors and downloadable video tutorials for students.

Download or read book Bayesian Statistics for the Social Sciences written by David Kaplan and published by Guilford Publications. This book was released on 2023-10-02 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second edition of this practical book equips social science researchers to apply the latest Bayesian methodologies to their data analysis problems. It includes new chapters on model uncertainty, Bayesian variable selection and sparsity, and Bayesian workflow for statistical modeling. Clearly explaining frequentist and epistemic probability and prior distributions, the second edition emphasizes use of the open-source RStan software package. The text covers Hamiltonian Monte Carlo, Bayesian linear regression and generalized linear models, model evaluation and comparison, multilevel modeling, models for continuous and categorical latent variables, missing data, and more. Concepts are fully illustrated with worked-through examples from large-scale educational and social science databases, such as the Program for International Student Assessment and the Early Childhood Longitudinal Study. Annotated RStan code appears in screened boxes; the companion website (www.guilford.com/kaplan-materials) provides data sets and code for the book's examples. New to This Edition *Utilizes the R interface to Stan--faster and more stable than previously available Bayesian software--for most of the applications discussed. *Coverage of Hamiltonian MC; Cromwell’s rule; Jeffreys' prior; the LKJ prior for correlation matrices; model evaluation and model comparison, with a critique of the Bayesian information criterion; variational Bayes as an alternative to Markov chain Monte Carlo (MCMC) sampling; and other new topics. *Chapters on Bayesian variable selection and sparsity, model uncertainty and model averaging, and Bayesian workflow for statistical modeling.

Download or read book Quantitative Social Science written by Kosuke Imai and published by Princeton University Press. This book was released on 2021-03-16 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Princeton University Press published Imai's textbook, Quantitative Social Science: An Introduction, an introduction to quantitative methods and data science for upper level undergrads and graduates in professional programs, in February 2017. What is distinct about the book is how it leads students through a series of applied examples of statistical methods, drawing on real examples from social science research. The original book was prepared with the statistical software R, which is freely available online and has gained in popularity in recent years. But many existing courses in statistics and data sciences, particularly in some subject areas like sociology and law, use STATA, another general purpose package that has been the market leader since the 1980s. We've had several requests for STATA versions of the text as many programs use it by default. This is a "translation" of the original text, keeping all the current pedagogical text but inserting the necessary code and outputs from STATA in their place"--

Download or read book An Introduction to Statistics for the Social Sciences written by T. G. Connolly and published by MacMillan Publishing Company. This book was released on 1971-01-01 with total page 213 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Using Basic Statistics in the Behavioral and Social Sciences written by Annabel Ness Evans and published by SAGE Publications. This book was released on 2013-06-06 with total page 605 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this fully updated edition of Using Basic Statistics in the Behavioral and Social Sciences, Annabel Ness Evans presents introductory statistics in a practical, conceptual, and humorous way, reducing the anxiety that many students experience in introductory courses. Avoiding complex notation and derivations, the book focuses on helping readers develop an understanding of the underlying logic of statistics, rather than rote memorization. Focus on Research boxes engage students with realistic applications of statistics, and end-of-chapter exercises ensure student comprehension. This exciting new edition includes a greater number of realistic and engaging global examples within the social and behavioral sciences, making it ideal for use within many departments or in interdisciplinary settings.

Download or read book Applied Multivariate Statistics for the Social Sciences written by Keenan A. Pituch and published by Routledge. This book was released on 2015-12-07 with total page 814 pages. Available in PDF, EPUB and Kindle. Book excerpt: Now in its 6th edition, the authoritative textbook Applied Multivariate Statistics for the Social Sciences, continues to provide advanced students with a practical and conceptual understanding of statistical procedures through examples and data-sets from actual research studies. With the added expertise of co-author Keenan Pituch (University of Texas-Austin), this 6th edition retains many key features of the previous editions, including its breadth and depth of coverage, a review chapter on matrix algebra, applied coverage of MANOVA, and emphasis on statistical power. In this new edition, the authors continue to provide practical guidelines for checking the data, assessing assumptions, interpreting, and reporting the results to help students analyze data from their own research confidently and professionally. Features new to this edition include: NEW chapter on Logistic Regression (Ch. 11) that helps readers understand and use this very flexible and widely used procedure NEW chapter on Multivariate Multilevel Modeling (Ch. 14) that helps readers understand the benefits of this "newer" procedure and how it can be used in conventional and multilevel settings NEW Example Results Section write-ups that illustrate how results should be presented in research papers and journal articles NEW coverage of missing data (Ch. 1) to help students understand and address problems associated with incomplete data Completely re-written chapters on Exploratory Factor Analysis (Ch. 9), Hierarchical Linear Modeling (Ch. 13), and Structural Equation Modeling (Ch. 16) with increased focus on understanding models and interpreting results NEW analysis summaries, inclusion of more syntax explanations, and reduction in the number of SPSS/SAS dialogue boxes to guide students through data analysis in a more streamlined and direct approach Updated syntax to reflect newest versions of IBM SPSS (21) /SAS (9.3) A free online resources site at www.routledge.com/9780415836661 with data sets and syntax from the text, additional data sets, and instructor’s resources (including PowerPoint lecture slides for select chapters, a conversion guide for 5th edition adopters, and answers to exercises) Ideal for advanced graduate-level courses in education, psychology, and other social sciences in which multivariate statistics, advanced statistics, or quantitative techniques courses are taught, this book also appeals to practicing researchers as a valuable reference. Pre-requisites include a course on factorial ANOVA and covariance; however, a working knowledge of matrix algebra is not assumed.

Download or read book Statistical Modeling and Inference for Social Science written by Sean Gailmard and published by Cambridge University Press. This book was released on 2014-06-09 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written specifically for graduate students and practitioners beginning social science research, Statistical Modeling and Inference for Social Science covers the essential statistical tools, models and theories that make up the social scientist's toolkit. Assuming no prior knowledge of statistics, this textbook introduces students to probability theory, statistical inference and statistical modeling, and emphasizes the connection between statistical procedures and social science theory. Sean Gailmard develops core statistical theory as a set of tools to model and assess relationships between variables - the primary aim of social scientists - and demonstrates the ways in which social scientists express and test substantive theoretical arguments in various models. Chapter exercises guide students in applying concepts to data, extending their grasp of core theoretical concepts. Students will also gain the ability to create, read and critique statistical applications in their fields of interest.

Download or read book A Mathematical Primer for Social Statistics written by John Fox and published by SAGE. This book was released on 2009 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ideal primer for students and researchers across the social sciences who wish to master the necessary maths in order to pursue studies involving advanced statistical methods

Download or read book Statistical Methods for the Social Sciences written by Alan Agresti and published by . This book was released on 2013-07-30 with total page 576 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fourth edition has an even stronger emphasis on concepts and applications, with greater attention to "real data" both in the examples and exercises. The mathematics is still downplayed, in particular probability, which is all too often a stumbling block for students. On the other hand, the text is not a cookbook. Reliance on an overly simplistic recipe-based approach to statistics is not the route to good statistical practice. Changes in the Fourth Edition: Since the first edition, the increase in computer power coupled with the continued improvement and accessibility of statistical software has had a major impact on the way social scientists analyze data. Because of this, this book does not cover the traditional shortcut hand-computational formulas and approximations. The presentation of computationally complex methods, such as regression, emphasizes interpretation of software output rather than the formulas for performing the analysis. Teh text contains numerous sample printouts, mainly in the style of SPSS and occasionaly SAS, both in chapter text and homework problems. This edition also has an appendix explaining how to apply SPSS and SAS to conduct the methods of each chapter and a website giving links to information about other software.

Download or read book Modern Statistics for the Social and Behavioral Sciences written by Rand Wilcox and published by CRC Press. This book was released on 2011-08-05 with total page 862 pages. Available in PDF, EPUB and Kindle. Book excerpt: In addition to learning how to apply classic statistical methods, students need to understand when these methods perform well, and when and why they can be highly unsatisfactory. Modern Statistics for the Social and Behavioral Sciences illustrates how to use R to apply both standard and modern methods to correct known problems with classic techniques. Numerous illustrations provide a conceptual basis for understanding why practical problems with classic methods were missed for so many years, and why modern techniques have practical value. Designed for a two-semester, introductory course for graduate students in the social sciences, this text introduces three major advances in the field: Early studies seemed to suggest that normality can be assumed with relatively small sample sizes due to the central limit theorem. However, crucial issues were missed. Vastly improved methods are now available for dealing with non-normality. The impact of outliers and heavy-tailed distributions on power and our ability to obtain an accurate assessment of how groups differ and variables are related is a practical concern when using standard techniques, regardless of how large the sample size might be. Methods for dealing with this insight are described. The deleterious effects of heteroscedasticity on conventional ANOVA and regression methods are much more serious than once thought. Effective techniques for dealing heteroscedasticity are described and illustrated. Requiring no prior training in statistics, Modern Statistics for the Social and Behavioral Sciences provides a graduate-level introduction to basic, routinely used statistical techniques relevant to the social and behavioral sciences. It describes and illustrates methods developed during the last half century that deal with known problems associated with classic techniques. Espousing the view that no single method is always best, it imparts a general understanding of the relative merits of various techniques so that the choice of method can be made in an informed manner.

Download or read book Applied Statistics for the Social and Health Sciences written by Rachel A. Gordon and published by Taylor & Francis. This book was released on 2023-11-15 with total page 800 pages. Available in PDF, EPUB and Kindle. Book excerpt: For graduate students in the social and health sciences, featuring essential concepts and equations most often needed in scholarly publications. Uses excerpts from the scholarly literature in these fields to introduce new concepts. Uses publicly-available data that are regularly used in social and health science publications to introduce Stata code and illustrate concepts and interpretation. Thoroughly integrates the teaching of statistical theory with teaching data processing and analysis. Offers guidance about planning projects and organizing code for reproducibility Shows how to recognize critiques of the constructions, terminology, and interpretations of statistics. New edition focuses on Stata, with code integrated into the chapters (rather than appendices, as in the first edition) includes Stata’s factor variables and margins commands and Long and Freese’s (2014) spost13 commands, to simplify programming and facilitate interpretation.

Download or read book Statistics in the Social Sciences written by Stanislav Kolenikov and published by John Wiley & Sons. This book was released on 2010-02-22 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: A one-of-a-kind compilation of modern statistical methods designed to support and advance research across the social sciences Statistics in the Social Sciences: Current Methodological Developments presents new and exciting statistical methodologies to help advance research and data analysis across the many disciplines in the social sciences. Quantitative methods in various subfields, from psychology to economics, are under demand for constant development and refinement. This volume features invited overview papers, as well as original research presented at the Sixth Annual Winemiller Conference: Methodological Developments of Statistics in the Social Sciences, an international meeting that focused on fostering collaboration among mathematical statisticians and social science researchers. The book provides an accessible and insightful look at modern approaches to identifying and describing current, effective methodologies that ultimately add value to various fields of social science research. With contributions from leading international experts on the topic, the book features in-depth coverage of modern quantitative social sciences topics, including: Correlation Structures Structural Equation Models and Recent Extensions Order-Constrained Proximity Matrix Representations Multi-objective and Multi-dimensional Scaling Differences in Bayesian and Non-Bayesian Inference Bootstrap Test of Shape Invariance across Distributions Statistical Software for the Social Sciences Statistics in the Social Sciences: Current Methodological Developments is an excellent supplement for graduate courses on social science statistics in both statistics departments and quantitative social sciences programs. It is also a valuable reference for researchers and practitioners in the fields of psychology, sociology, economics, and market research.

Download or read book Applied Statistics Using R written by Mehmet Mehmetoglu and published by SAGE. This book was released on 2021-11-10 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you want to learn to use R for data analysis but aren’t sure how to get started, this practical book will help you find the right path through your data. Drawing on real-world data to show you how to use different techniques in practice, it helps you progress your programming and statistics knowledge so you can apply the most appropriate tools in your research. It starts with descriptive statistics and moves through regression to advanced techniques such as structural equation modelling and Bayesian statistics, all with digestible mathematical detail for beginner researchers. The book: Shows you how to use R packages and apply functions, adjusting them to suit different datasets. Gives you the tools to try new statistical techniques and empowers you to become confident using them. Encourages you to learn by doing when running and adapting the authors’ own code. Equips you with solutions to overcome the potential challenges of working with real data that may be messy or imperfect. Accompanied by online resources including screencast tutorials of R that give you step by step guidance and R scripts and datasets for you to practice with, this book is a perfect companion for any student of applied statistics or quantitative research methods courses.