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Author :
Release : 2005
Genre : Science
Kind : eBook
Book Rating : 834/5 ( reviews)
Book Synopsis X-Kit Undergraduate Stats for the Social Sciences by :
Download or read book X-Kit Undergraduate Stats for the Social Sciences written by . This book was released on 2005. Available in PDF, EPUB and Kindle. Book excerpt:
Author :
Release :
Genre :
Kind : eBook
Book Rating : /5 ( reviews)
Book Synopsis X-Kit, Statistics for the social sciences by :
Download or read book X-Kit, Statistics for the social sciences written by . This book was released on . Available in PDF, EPUB and Kindle. Book excerpt:
Author : R. Mark Sirkin
Release : 2006
Genre : Mathematics
Kind : eBook
Book Rating : 466/5 ( reviews)
Book Synopsis Statistics for the Social Sciences by : R. Mark Sirkin
Download or read book Statistics for the Social Sciences written by R. Mark Sirkin. This book was released on 2006. 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
Author : Elena Llaudet
Release : 2022-11-29
Genre : Computers
Kind : eBook
Book Rating : 434/5 ( reviews)
Book Synopsis Data Analysis for Social Science by : Elena Llaudet
Download or read book Data Analysis for Social Science written by Elena Llaudet. This book was released on 2022-11-29. 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"--
Author : Sean Gailmard
Release : 2014-06-09
Genre : Business & Economics
Kind : eBook
Book Rating : 148/5 ( reviews)
Book Synopsis Statistical Modeling and Inference for Social Science by : Sean Gailmard
Download or read book Statistical Modeling and Inference for Social Science written by Sean Gailmard. This book was released on 2014-06-09. 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.
