With a clear and engaging writing style and strong examples from the real world, this text covers current statistical techniques at an introductory level and emphasizes the clear presentation of results to a variety of audiences, making the course more useful to students and their careers. Interconnection features among chapters help students understand how all of the techniques fit together. Using varied data sets, the text features a highly rated companion website that includes videos of the author offering step-by-step explanations of how to carry out the techniques, interpret the results, and present them to varied audiences. NEW TO THIS EDITION More inter-chapter connections have been added to improve students’ conceptual learning. Several examples (on immigration, health, and civil rights) now permeate the text for easy comparison of techniques across chapters. The section on managing data is considerably expanded to cover topics such as finding new sources of data, dealing with missing data, and how to combine data reliably. Very current examples from the scholarly literature from criminology, education, and health show how researchers use each chapter’s techniques to tell compelling stories. Instructors can choose from a variety of greatly expanded materials to enhance their lectures: engaging animations of key concepts; dynamic demonstrations of how statistics change in line with the data; short lectures on difficult-to-explain topics; and in-class exercises that will help students learn how to make sense of statistical results.
With a clear, engaging writing style and fascinating examples using a variety of real data, this text covers the contemporary statistical techniques that students will encounter in the world of social research. It covers these techniques at an introductory level and carefully guides students through increasingly complex examples without intimidating them. Recurrent examples using four timely topics—health, immigration, income inequality, and everyday harassment—help students understand how the techniques fit together, and how to use the techniques in combination with one another. A superb author-created web resource accompanies the text. How to make clear presentations of research results is also a feature of the text. New to this edition: New research shows how the techniques has changed over time in the academic literature, showing students that social scientists really do use the statistical techniques the book teaches and giving them ample motivation to learn the techniques. Examples throughout the book use the most recent data from the General Social Survey. Four timely topics are threaded throughout the book: immigration, health, income inequality, and everyday harassment. Linneman uses these topics recurrently with different statistical techniques to illustrate how the techniques are related to one another. The new edition more explicitly emphasizes that the various techniques the students are learning are often used in combination with one another. After introducing a new technique and showing how to use it on its own, Linneman then systematically offers examples of how to combine that technique with techniques students learned in previous chapters. Most of the literature examples that end each chapter are new and use very recent research from top academic journals (three quarters from 2015 or later, nearly half from 2019). They feature research that covers timely topics such as Black Lives Matter, transgender health, social media, police behavior, and climate change. The SPSS demonstrations are completely redone, both in the book and on the website’s demonstration videos, using more recent data. Linneman applies his experience teaching his own students SPSS (knowing where students get confused) to clarify his explanations in these demonstrations.
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