Just Plain Data Analysis teaches students statistical literacy skills that they can use to evaluate and construct arguments about public affairs issues grounded in numerical evidence. The book addresses skills that are often not taught in introductory social science research methods courses and that are often covered sketchily in the research methods textbooks: where to find commonly used measures of political and social conditions; how to assess the reliability and validity of specific indicators; how to present data efficiently in charts and tables; how to avoid common misinterpretations and misrepresentations of data; and how to evaluate causal arguments based on numerical data. With a new chapter on statistical fallacies and updates throughout the text, the new edition teaches students how to find, interpret, and present commonly used social indicators in an even clearer and more practical way.
Rezensionen / Stimmen
This short book is a useful supplement to traditional statistics and research method texts....Recommended. * CHOICE * In Just Plain Data Analysis, Gary Klass analyzes simple statistics that involve sophisticated reasoning. This book cuts through paradoxes, fallacies and socially-constructed statistics to uncover the basic elements of data analysis. A must-read for anyone interested in statistical literacy. -- Milo Schield, director of the W. M. Keck Statistical Literacy Project, Augsburg College As a teacher of research methods, I have been waiting for a book like Just Plain Data Analysis. By focusing on finding, presenting and interpreting data, Klass encourages students to develop the critical thinking skills that they will need once they leave the university. The writing is clear and the examples are excellent. The discussion of reliability, validity, and ecological fallacy is the best I have read in an undergraduate text. The many table and chart examples will help students improve their skills. -- Bill Wilkerson, College at Oneonta, SUNY With humor and political balance, Just Plain Data Analysis offers a pithy guide to finding, presenting and interpreting social science data ranging from crime to elections. Recommended for students, teachers and policymakers who want to understand where the data comes from and how to use it responsibly. -- Mark Maier, author of The Data Game: Controversies in Social Science Statistics Just Plain Data Analysis: Finding, Presenting, and Interpreting Social Science by Gary M. Klass is an exploration of the types of quantitative research (which is rooted in data and statistical analysis) that can be used to draw conclusions about such social science issues as crime rates and measuring educational achievement. Klass uses examples of statistical claims to demonstrate how changing the time frame for data collection or looking at different correlations can result in varying or misleading statements. He also has chapters to how to tabulate and display numbers and how to use graphical presentation effectively. * American Libraries *
Auflage
Sprache
Verlagsort
Verlagsgruppe
Bloomsbury Publishing Plc
Zielgruppe
Für höhere Schule und Studium
US School Grade: From College Freshman to College Graduate Student, Interest Age: From 18 to 22 years
Maße
Höhe: 229 mm
Breite: 152 mm
Dicke: 12 mm
Gewicht
ISBN-13
978-1-4422-1508-5 (9781442215085)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
Gary M. Klass teaches public policy, race and ethnicity, and quantitative research methods at Illinois State University. He is past president of the APSA Computers and Multimedia Section and co-editor of the Political Science Research and Teaching List.
Preface
Chapter 1: Measuring Political, Social and Economic Conditions
Chapter 2: Measuring Racial and Ethnic Inequality
Chapter 3: Statistical Fallacies, Paradoxes and Threats to Validity
Chapter 4: Examining a Relationship: New York City Crime Rates
Chapter 5: Tabulating the Data and Writing about the Numbers
Chapter 6: The Graphical Display of Data
Chapter 7: Voting and Elections
Chapter 8: Measuring Educational Achievement
Chapter 9: Measuring Poverty and Inequality
