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Statistics Using Stata
Engaging and accessible to students from a wide variety of mathematical backgrounds, Statistics Using Stata combines the teaching of statistical concepts with the acquisition of the popular Stata software package. It closely aligns Stata commands with numerous examples based on real data, enabling students to develop a deep understanding of statistics in a way that reflects statistical practice. Capitalizing on the fact that Stata has both a menu-driven 'point and click' and program syntax interface, the text guides students effectively from the comfortable 'point and click' environment to the beginnings of statistical programming. Its comprehensive coverage of essential topics gives instructors flexibility in curriculum planning and provides students with more advanced material to prepare them for future work. Online resources - including complete solutions to exercises, PowerPoint slides, and Stata syntax (do-files) for each chapter - allow students to review independently and adapt codes to solve new problems, reinforcing their programming skills.
Statistics Using IBM SPSS
Written in a clear and lively tone, Statistics Using IBM SPSS provides a data-centric approach to statistics with integrated SPSS (version 22) commands, ensuring that students gain both a deep conceptual understanding of statistics and practical facility with the leading statistical software package. With one hundred worked examples, the textbook guides students through statistical practice using real data and avoids complicated mathematics. Numerous end-of-chapter exercises allow students to apply and test their understanding of chapter topics, with detailed answers available online. The third edition has been updated throughout and includes a new chapter on research design, new topics (including weighted mean, resampling with the bootstrap, the role of the syntax file in workflow management, and regression to the mean) and new examples and exercises. Student learning is supported by a rich suite of online resources, including answers to end-of-chapter exercises, real data sets, PowerPoint slides, and a test bank.
Statistics Using SPSS
Applied statistics text updated to be consistent with SPSS version 15, ideal for classroom use or self study.
Data Analysis for the Behavioral Sciences Using SPSS
An introductory applied statistics text that can be used at either undergraduate or graduate level.
New Cambridge Statistical Tables
This second edition has all the tables required for elementary statistical methods in the social, business and natural sciences.
Statistical Modeling and Inference for Social Science
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.
The Fundamentals of Political Science Research
This textbook introduces the scientific study of politics, supplying students with the basic tools to be critical consumers and producers of scholarly research.
Biostatistics with R
A straightforward introduction to a wide range of statistical methods for field biologists, using thoroughly explained R code.
Talking Mathematics in School
The teaching and learning of mathematics in K-12 classrooms is changing. New curricula and methods engage learners in working on real problems. An essential feature of this work involves teacher and students in "talking mathematics". How can students learn to do this kind of talking? What can they learn from doing it? This book addresses these questions by looking at the processes of formulating problems, interpreting contexts in which problems arise, and arguing about the reasonableness of proposed solutions. The studies in this volume seek to retain the complexity of classroom practice rather than looking at it through a particular academic lens.
Regression and Other Stories
A practical approach to using regression and computation to solve real-world problems of estimation, prediction, and causal inference.
