**Author**: Robert A. Hanneman,Augustine J. Kposowa,Mark D. Riddle

**Publisher:** John Wiley & Sons

**ISBN:** 1118234154

**Category:** Social Science

**Page:** 560

**View:** 7352

A core statistics text that emphasizes logical inquiry, notmath Basic Statistics for Social Research teaches core generalstatistical concepts and methods that all social science majorsmust master to understand (and do) social research. Its use ofmathematics and theory are deliberately limited, as the authorsfocus on the use of concepts and tools of statistics in theanalysis of social science data, rather than on the mathematicaland computational aspects. Research questions and applications aretaken from a wide variety of subfields in sociology, and eachchapter is organized around one or more general ideas that areexplained at its beginning and then applied in increasing detail inthe body of the text. Each chapter contains instructive features to aid students inunderstanding and mastering the various statistical approachespresented in the book, including: Learning objectives Check quizzes after many sections and an answer key at the endof the chapter Summary Key terms End-of-chapter exercises SPSS exercises (in select chapters) Ancillary materials for both the student and the instructor areavailable and include a test bank for instructors and downloadablevideo tutorials for students.

Both students and professionals are increasingly reliant on computers for the analysis of data. This accessible introduction to statistics using the program Minitab assumes no prior knowledge of statistics or computing, and has details of the different versions and options available. It also explains when to apply and how to calculate and interpret a wide range of statistical procedures commonly used in the social sciences. Ranging from chi-square and the t test to analysis of covariance and multiple regression, Duncan Cramer covers a wide choice of statistics, including tests not found in other introductory texts, such as tests for determining whether correlations differ and the extent of agreement between observers. Important statistical points are illustrated with worked numerical examples, and exercises are provided at the end of chapters.

Focused on principles and techniques, this book provides a conceptual, intuitive approach to applied statistics that replaces proofs and derivations with examples and illustrations. The focus throughout is on the usefulness of statistics and content is organized according to statistical applications, not statistical assumptions. Emphasizes informed applications of statistics — but provides a balance of applications and theory. Explores the statistical procedures that are most useful in the social and behavioral sciences — with a focus on essential concepts and techniques needed in order to begin to evaluate data and read research literature in the behavior sciences. Groups statistics by purpose, not assumption. Demonstrates appropriate applications as well as computational mechanics and interpretation. Shows that statistics is not the study of numbers, but the study of people, cities, and the concerns of the everyday world.

Using Basic Statistics in the Behavioral and Social Sciences, Fifth Edition, by Annabel Ness Evans, presents introductory statistics in a practical, conceptual, and humorous way, reducing the anxiety that many students experience in introductory courses. Avoiding complex notation and derivation, the book focuses on helping readers develop an understanding of the underlying logic of statistics. Practical Focus on Research boxes engage students with realistic applications of statistics, and end-of-chapter exercises ensure student comprehension. This exciting new edition includes a greater number of realistic and engaging global examples within the social and behavioral sciences, making it ideal for use within many departments or in interdisciplinary settings.

This book covers applied statistics for the social sciences with upper-level undergraduate students in mind. The chapters are based on lecture notes from an introductory statistics course the author has taught for a number of years. The book integrates statistics into the research process, with early chapters covering basic philosophical issues underpinning the process of scientific research. These include the concepts of deductive reasoning and the falsifiability of hypotheses, the development of a research question and hypotheses, and the process of data collection and measurement. Probability theory is then covered extensively with a focus on its role in laying the foundation for statistical reasoning and inference. After illustrating the Central Limit Theorem, later chapters address the key, basic statistical methods used in social science research, including various z and t tests and confidence intervals, nonparametric chi square tests, one-way analysis of variance, correlation, simple regression, and multiple regression, with a discussion of the key issues involved in thinking about causal processes. Concepts and topics are illustrated using both real and simulated data. The penultimate chapter presents rules and suggestions for the successful presentation of statistics in tabular and graphic formats, and the final chapter offers suggestions for subsequent reading and study.

Applied Statistics for the Social and Health Sciences provides graduate students in the social and health sciences with the basic skills that they need to estimate, interpret, present, and publish statistical models using contemporary standards. The book targets the social and health science branches such as human development, public health, sociology, psychology, education, and social work in which students bring a wide range of mathematical skills and have a wide range of methodological affinities. For these students, a successful course in statistics will not only offer statistical content but will also help them develop an appreciation for how statistical techniques might answer some of the research questions of interest to them. This book is for use in a two-semester graduate course sequence covering basic univariate and bivariate statistics and regression models for nominal and ordinal outcomes, in addition to covering ordinary least squares regression. Key features of the book include: interweaving the teaching of statistical concepts with examples developed for the course from publicly-available social science data or drawn from the literature thorough integration of teaching statistical theory with teaching data processing and analysis teaching of both SAS and Stata "side-by-side" and use of chapter exercises in which students practice programming and interpretation on the same data set and course exercises in which students can choose their own research questions and data set. This book is for a two-semester course. For a one-semester course, see http://www.routledge.com/9780415991544/

A comprehensive guide to the practical applications of statistics in social sciences This book brings out the relevance of statistical tools and methods in social sciences. Describing the various statistical techniques, it highlights their purpose and application along with a brief overview on how to interpret results and draw inferences. Topical and up-to-date, it examines: • different types of statistical variables and their treatment • tabulation and graphical presentation of data • theoretical distributions and common parametric and non-parametric tests, including analysis of variance and correlation ratio • linear regression including checking for violation of assumptions, transformations of variables and predictions • inequality measures such as Lorenz curve, Gini coefficient, dissimilarity index and human development index among others. It will be indispensable for students and scholars of statistics, econometrics, psychology and those interested in the application of statistics in social sciences.

Aimed at undergraduate students taking course in statistics for sociology and the social sciences, this work assumes only high school algebra. This edition features a more applied social science perspective, especially with regard to multivariate analysis and the interpretation of results.

This accessible introduction to statistics using the program SPSS for Windows explains when to apply and how to calculate and interpret a wide range of statistical procedures commonly used in the social sciences. Keeping statistical symbols and formulae to a minimum and using simple examples, this book: * assumes no prior knowledge of statistics or computing * includes a concise introduction to the program SPSS for Windows * describes a wider range of tests than other introductory texts * contains a comprehensive range of exercises with answers Fundamental Statistics for Social Research covers SPSS Release 6 for Windows 3.1 and Release 7 for Windows 95. It will prove an invaluable introductory statistics text for students, and a useful resource for graduates and professionals engaged in research in the social sciences.

This basic social science statistics text uses illustrations and exercises for sociology, social work, political science, and criminal justice. Praised for a writing style that takes the anxiety out of statistics courses, the author explains basic statistical principles through a variety of engaging exercises, each designed to illuminate the unique theme of examining society both creatively and logically. In an effort to make the study of statistics relevant to students of the social sciences, the author encourages readers to interpret the results of calculations in the context of more substantive social issues, while continuing to value precise and accurate research.

In this comprehensive introduction to using statistics in the social sciences, Daniel B Wright describes the most popular statistical techniques, explaining their basic principles and demonstrating their use in a wide range of social research. The book is divided into four sections. Part One explains the theoretical relationship between statistics and research, outlining the place of statistics in the research process and introducing hypothesis testing. In Part Two the two "t"-tests are described in detail. This serves as a foundation for the rest of the book and develops skills that are called upon in later chapters. Part Three outlines the three main families of statistical tests - regression, analysis of variance, and two-variable tests. Finally, Part Four offers a guide to more advanced techniques.

The new edition of this bestselling text continues to emphasize intuition and common sense, while demonstrating the link between the practice of statistics and important social issues. The authors help students learn key sociological concepts through real research examples related to the dynamic interplay of race, class, gender, and other social variables.

This pocket guide introduces readers to linear regression analysis, analysis of variance and covariance, and path analysis with an emphasis on the basic statistics. It prepares doctoral students and early career social work researchers with limited statistics exposure in the use of multivariate methods by providing an easy-to-understand presentation.

For many years now I have been required to give a series of elementary lectures on statistics to medical students about to undertake a postgraduate course in psychiatry. The declared aim of the course, for which very limited time was available, was to provide the students with some initial understanding of the statistical terminology and elementary techniques to which other teachers, in particular psychologists and sociologists, would be likely to refer in the course of their lectures. The task was tricky for two reasons. In the first place most of the students involved, despite their best intentions, had forgotten their school mathematics, and secondly no textbook existed at the right level of difficulty which contained examples appropriate to these students' needs and experience. The present book was written to fill the gap. Though pri marily intended for psychiatrists, the book should prove very useful to any student of the behavioural sciences who wants a simple introductory course on the principles of experimental design and data analysis. It must be one of the simplest text books on elementary statistics ever written. I am indebted to the literary executor of the late Sir Ronald A. Fisher, F.R.S., to Dr Frank Yates, F.R.S., and to Oliver & Boyd Ltd for permission to reprint Tables 3 and 5 from their book Statistical Tables for Biological, Agricultural and Medical Research.

Basic Statistics for Social Workers, now in a revised edition, was developed by Schneider after teaching statistics to undergraduate and graduate social work students for over ten years. The statistical concepts that are necessary for students to know are covered, ranging from simple descriptive statistics such as crosstabs and tabular data up to a limited discussion of multiple regression. The text is written simply for students who may not have a strong quantitative background. The text is simple enough that with the practice problems and perhaps a little consultation a motivated student could self-teach the content.

A user-friendly, hands-on guide to recognizing and conducting proper research techniques in data collection Offering a unique approach to numerical research methods, Analyzing Quantitative Data: An Introduction for Social Researchers presents readers with the necessary statistical applications for carrying out the key phases of conducting and evaluating a research project. The book guides readers through the steps of data analysis, from organizing raw data to utilizing descriptive statistics and tests of significance, drawing valid conclusions, and writing research reports. The author successfully provides a presentation that is accessible and hands-on rather than heavily theoretical, outlining the key quantitative processes and the use of software to successfully draw valid conclusions from gathered data. In its discussion of methods for organizing data, the book includes suggestions for coding and entry into spreadsheets or databases while also introducing commonly used descriptive statistics and clarifying their roles in data analysis. Next, inferential statistics is explored in-depth with explanations of and instructions for performing chi-square tests, t-tests, analyses of variance, correlation and regression analyses, and a number of advanced statistical procedures. Each chapter contains explanations of when to use the tests described, relevant formulas, and sample computations. The book concludes with guidance on extracting meaningful conclusions from statistical tests and writing research reports that describe procedures and analyses. Throughout the book, Statistical Resources for SPSS® sections provide fundamental instruction for using SPSS® to obtain the results presented. Where necessary, the author provides basic theoretical explanations for distributions and background information regarding formulas. Each chapter concludes with practice problems, and a related website features derivations of the book's formulas along with additional resources for performing the discussed processes. Analyzing Quantitative Data is an excellent book for social sciences courses on data analysis and research methods at the upper-undergraduate and graduate levels. It also serves as a valuable reference for applied statisticians and practitioners working in the fields of education, medicine, business and public service who analyze, interpret, and evaluate data in their daily work.