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Author: Elena Llaudet Publisher: Princeton University Press ISBN: 0691199434 Category : Computers Languages : en Pages : 256
Book Description
"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"--
Author: Elena Llaudet Publisher: Princeton University Press ISBN: 0691199434 Category : Computers Languages : en Pages : 256
Book Description
"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"--
Author: R. Mark Sirkin Publisher: SAGE ISBN: 9781412905466 Category : Mathematics Languages : en Pages : 636
Book Description
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
Author: Russell T. Warne Publisher: Cambridge University Press ISBN: 110889853X Category : Psychology Languages : en Pages : 612
Book Description
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.
Author: Douglas Bors Publisher: SAGE ISBN: 1526422301 Category : Social Science Languages : en Pages : 1115
Book Description
′This book fosters in-depth understanding of the logic underpinning the most common statistical tests within the behavioural sciences. By emphasising the shared ground between these tests, the author provides crucial scaffolding for students as they embark upon their research journey.′ —Ruth Horry, Psychology, Swansea University ′This unique text presents the conceptual underpinnings of statistics as well as the computation and application of statistics to real-life situations--a combination rarely covered in one book. A must-have for students learning statistical techniques and a go-to handbook for experienced researchers.′ —Barbra Teater, Social Work, College of Staten Island, City University of New York Accessible, engaging, and informative, this book will help any social science student approach statistics with confidence. With a well-paced and well-judged integrated approach rather than a simple linear trajectory, this book progresses at a realistic speed that matches the pace at which statistics novices actually learn. Packed with global, interdisciplinary examples that ground statistical theory and concepts in real-world situations, it shows students not only how to apply newfound knowledge using IBM SPSS Statistics, but also why they would want to. Spanning statistics basics like variables, constants, and sampling through to t-tests, multiple regression and factor analysis, it builds statistical literacy while also covering key research principles like research questions, error types and results reliability. It shows you how to: Describe data with graphs, tables, and numbers Calculate probability and value distributions Test a priori and post hoc hypotheses Conduct Chi-squared tests and observational studies Structure ANOVA, ANCOVA, and factorial designs Supported by lots of visuals and a website with interactive demonstrations, author video, and practice datasets, this book is the student-focused companion to support students through their statistics journeys.
Author: Norman R. Kurtz Publisher: Prentice Hall ISBN: Category : Business & Economics Languages : en Pages : 410
Book Description
People are bombarded with statistical data every day, but not many have had training in how to interpret or analyze this information. Kurtz's accessible writing style provides a basic yet sophisticated introduction to understanding and analyzing statistical applications. The book gives careful attention to the flow of ideas and concepts so there is a stream of logic which flows throughout, adding to the book's readability. The book begins with a discussion of methods for describing the distribution of a variable. The introduction of probability avoids the traditional discussion of the basic laws of probability, providing instead an explanation which can be directly applied in the everyday use of statistical probability. The discussion of the book is focused primarily on the relationship of probability to outcomes. Sociologists, psychologists, social workers, political scientists, educators, as well as anyone who wants to analyze data.
Author: Kosuke Imai Publisher: Princeton University Press ISBN: 0691191093 Category : Political Science Languages : en Pages : 464
Book Description
"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"--
Author: Carol S. Aneshensel Publisher: SAGE ISBN: 1412994357 Category : Reference Languages : en Pages : 473
Book Description
This book presents the elaboration model for the multivariate analysis of observational quantitative data. This model entails the systematic introduction of "third variables" to the analysis of a focal relationship between one independent and one dependent variable to ascertain whether an inference of causality is justified. Two complementary strategies are used: an exclusionary strategy that rules out alternative explanations such as spuriousness and redundancy with competing theories, and an inclusive strategy that connects the focal relationship to a network of other relationships, including the hypothesized causal mechanisms linking the focal independent variable to the focal dependent variable. The primary emphasis is on the translation of theory into a logical analytic strategy and the interpretation of results. The elaboration model is applied with case studies drawn from newly published research that serve as prototypes for aligning theory and the data analytic plan used to test it; these studies are drawn from a wide range of substantive topics in the social sciences, such as emotion management in the workplace, subjective age identification during the transition to adulthood, and the relationship between religious and paranormal beliefs. The second application of the elaboration model is in the form of original data analysis presented in two Analysis Journals that are integrated throughout the text and implement the full elaboration model. Using real data, not contrived examples, the text provides a step-by-step guide through the process of integrating theory with data analysis in order to arrive at meaningful answers to research questions.
Author: Alan Agresti Publisher: ISBN: 9781292021669 Category : Business & Economics Languages : en Pages : 576
Book Description
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.
Author: R. Mark Sirkin Publisher: SAGE Publications, Incorporated ISBN: 9780761914181 Category : Social Science Languages : en Pages : 0
Book Description
Do your students lack confidence in handling quantitative work? Do they get confused about how to enter statistical data on SAS and SPSS programs? This Second Edition of Mark Sirkin's popular textbook is the solution for these dilemmas. The book progresses from concepts that require little computational work to the more demanding. It emphasizes utilization so that students appreciate the usefulness of statistics and shows how the interpretation of data is related to the methods by which data was obtained. The author includes coverage of the scientific method, levels of measurement and the interpretation of tables.
Author: McKee J. McClendon Publisher: Wadsworth Publishing ISBN: 9780534637835 Category : Social sciences Languages : en Pages : 0
Book Description
Statistical Analysis in the Social Sciences imbeds basic descriptive and inferential statistical concepts within a unified framework: the linear regression model. The regression model is used not only for conducting standard regression analyses but also for other statistical analyses that are ordinarily taught as separate and distinct techniques, such as correlation, difference of means, analysis of variance, and certain nonparametric tests. This extensive use of a single statistical model will increase students' depth of understanding and give them a sense of mastery and self-confidence that they might otherwise fail to achieve in their first statistics course.
Author: Elena Llaudet
Author: Elena Llaudet
Author: R. Mark Sirkin
Author: Russell T. Warne
Author: Douglas Bors
Author: Norman R. Kurtz
Author: Kosuke Imai
Author: Carol S. Aneshensel
Author: Alan Agresti
Author: R. Mark Sirkin
Author: McKee J. McClendon