Author: John T. Kulas
Publisher: John Wiley & Sons
Release Date: 2009
Written by a highly experienced researcher and teachers, this book provides a much–needed guide to the proper use of Statistical Package for the Social Sciences (SPSS) software in social research, particularly where data may not be presented in the most convenient way. The book focuses on data manipulations and covers the majority of real–world use of SPSS use. Among the book′s many unique features are its ′syntax diary′ method for organization of manipulations and analyses. Offers both novices and intermediate users a framework within which they can safely and comfortably work with SPSS.
Author: William Edward Wagner
Release Date: 2011
Genre: Social Science
Ideal as a companion to a statistics or research methods text or as a stand-alone guide, Using SPSS for Social Statistics and Research Methods shows readers how to use images and directions drawn from SPSS Version 18.0 and now uses the latest version of the GSS (General Social Survey) as a secondary data set. This supplementary text is designed as a manual for SPSS use for social statistics and research methods classes and is an excellent companion to any undergraduate statistics or research methods textbook. It will also serve as a useful reference for those learning to use the SPSS software for the first time. Features and Benefits: • Offers a fully updated graphics chapter that highlights new features available in SPSS 18.0, including information on alternative routes to creating graphics • Includes updated examples, screenshots and tables throughout • Expanded coverage of output interpretation • Refers to several kinds of computer files, including data files, output files and syntax files • Covers a wide range of data analysis topics to help students who are working independently on a research proposal, project or paper.
Author: Professor David de Vaus
Release Date: 2002-06-01
In this novel and refreshing textbook, David de Vaus directs students to the core of data analysis. The book is an authoritative guide to the problems facing beginners in the field. Analyzing Social Science Data guides students in: problems with the initial data; problems with the initial variables; how to handle too much data; how to generalize; problems of analyzing single variables; problems examining bivariate relationships; and problems examining multivariate relationships The book is a "tour de force" in making data analysis manageable and rewarding for today's undergraduate studying research methods. I'm full of admiration for this book. Once again, David de Vaus has come up with a superb book that is well written and organized and which will be a boon to a wide range of students. He has taken a vast array of problems that users of quantitative data analysis procedures are likely to encounter. The selection of issues and problems ... reflects the experience of a true practitioner with a grasp of his field and of the intricacies of the research process. The selection of issues clearly derives also from experience of teaching students how to do research and analyse data....A large number of practitioners will want the book. I was surprised at how much I learned from this. This will be a vital book for the bookshelves of practitioners of the craft of quantitative data analysis' - "Alan Bryman, Professor of Social Research, Loughborough University
Author: Douglas Bors
Release Date: 2018-01-08
Genre: Social Science
'This book fosters in-depth understanding of the logic underpinning the most common statistical tests within the behavioural sciences. By emphasising the shared ground between these tests, the author provides crucial scaffolding for students as they embark upon their research journey.' —Ruth Horry, Psychology, Swansea University 'This unique text presents the conceptual underpinnings of statistics as well as the computation and application of statistics to real-life situations--a combination rarely covered in one book. A must-have for students learning statistical techniques and a go-to handbook for experienced researchers.' —Barbra Teater, Social Work, College of Staten Island, City University of New York Accessible, engaging, and informative, this book will help any social science student approach statistics with confidence. With a well-paced and well-judged integrated approach rather than a simple linear trajectory, this book progresses at a realistic speed that matches the pace at which statistics novices actually learn. Packed with global, interdisciplinary examples that ground statistical theory and concepts in real-world situations, it shows students not only how to apply newfound knowledge using IBM SPSS Statistics, but also why they would want to. Spanning statistics basics like variables, constants, and sampling through to t-tests, multiple regression and factor analysis, it builds statistical literacy while also covering key research principles like research questions, error types and results reliability. It shows you how to: Describe data with graphs, tables, and numbers Calculate probability and value distributions Test a priori and post hoc hypotheses Conduct Chi-squared tests and observational studies Structure ANOVA, ANCOVA, and factorial designs Supported by lots of visuals and a website with interactive demonstrations, author video, and practice datasets, this book is the student-focused companion to support students through their statistics journeys.
Author: Soleman H. Abu-Bader
Publisher: Oxford University Press
Release Date: 2011-07-01
Genre: Social Science
In Using Statistical Methods, Soleman Abu-Bader detects and addresses the gaps between the research and data analysis of the classroom environment and the practitioner's office. This book not only guides social scientists through different tests, but also provides students and researchers alike with information that will help them in their own practice. With focus on the purpose, rationale, and assumptions made by each statistical test, and a plethora of research examples that clearly display their applicability and function in real-world practice, Professor Abu-Bader creates a step-by-step description of the process needed to clearly organize, choose a test or statistical technique, analyze, interpret, and report research findings.
Author: Daniel J. Denis
Publisher: John Wiley & Sons
Release Date: 2018-07-31
Enables readers to start doing actual data analysis fast for a truly hands-on learning experience This concise and very easy-to-use primer introduces readers to a host of computational tools useful for making sense out of data, whether that data come from the social, behavioral, or natural sciences. The book places great emphasis on both data analysis and drawing conclusions from empirical observations. It also provides formulas where needed in many places, while always remaining focused on concepts rather than mathematical abstraction. SPSS Data Analysis for Univariate, Bivariate, and Multivariate Statistics offers a variety of popular statistical analyses and data management tasks using SPSS that readers can immediately apply as needed for their own research, and emphasizes many helpful computational tools used in the discovery of empirical patterns. The book begins with a review of essential statistical principles before introducing readers to SPSS. The book then goes on to offer chapters on: Exploratory Data Analysis, Basic Statistics, and Visual Displays; Data Management in SPSS; Inferential Tests on Correlations, Counts, and Means; Power Analysis and Estimating Sample Size; Analysis of Variance – Fixed and Random Effects; Repeated Measures ANOVA; Simple and Multiple Linear Regression; Logistic Regression; Multivariate Analysis of Variance (MANOVA) and Discriminant Analysis; Principal Components Analysis; Exploratory Factor Analysis; and Non-Parametric Tests. This helpful resource allows readers to: Understand data analysis in practice rather than delving too deeply into abstract mathematical concepts Make use of computational tools used by data analysis professionals. Focus on real-world application to apply concepts from the book to actual research Assuming only minimal, prior knowledge of statistics, SPSS Data Analysis for Univariate, Bivariate, and Multivariate Statistics is an excellent “how-to” book for undergraduate and graduate students alike. This book is also a welcome resource for researchers and professionals who require a quick, go-to source for performing essential statistical analyses and data management tasks.
This is a complete guide to statistics and SPSS for social science students. Statistics with SPSS for Social Science provides a step-by-step explanation of all the important statistical concepts, tests and procedures. It is also a guide to getting started with SPSS, and includes screenshots to illustrate explanations. With examples specific to social sciences, this text is essential for any student in this area.
Author: Ajai S Gaur
Publisher: SAGE Publications India
Release Date: 2009-05-13
Genre: Business & Economics
There is a growing trend these days to use statistical methods to comprehend and explain various situations and phenomena in different disciplines. Managers, social scientists and practicing researchers are increasingly collecting information and applying scientific methods to analyze the data. The ability to use statistical methods and tools becomes a crucial skill for the success of such efforts. This book is designed to assist students, managers, academics and researchers in solving statistical problems using SPSS and to help them understand how they can apply various statistical tools for their own research problems. SPSS is a very powerful and user friendly computer package for data analyses. It can take data from most other file types and generate tables, charts, plots, and descriptive statistics, and conduct complex statistical analyses. After providing a brief overview of SPSS and basic statistical concepts, the book covers: - Descriptive statistics - t-tests, chi-square tests and ANOVA - Correlation analysis - Multiple and logistics regression - Factor analysis and testing scale reliability - Advanced data handling Illustrated with simple, practical problems, and screen shots, this book outlines the steps for solving statistical problems using SPSS. Although the illustrations are based on version 16.0 of SPSS, users of the earlier versions will find the book equally useful and relevant. Written in a reader-friendly, non-technical style, this book will serve as a companion volume to any statistics textbook.
Author: Carol S. Parke
Publisher: SAGE Publications
Release Date: 2012-12-13
Genre: Social Science
Carol S. Parke's Essential First Steps to Data Analysis: Scenario-Based Examples Using SPSS provides instruction and guidance on preparing quantitative data sets prior to answering a study's research questions. Such preparation may involve data management and manipulation tasks, data organization, structural changes to the data files, or conducting preliminary analysis. Twelve research-based scenarios are used to present the content. Each scenario tells the "story" of a researcher who thoroughly examined their data and the decisions they made along the way. The scenario begins with a description of the researcher's study and his/her data file(s), then describes the issues the researcher must address, explains why they are important, shows how SPSS was used to address the issues and prepare data, and shares the researcher's reflections and any additional decision-making. Finally, each scenario ends with the researcher's written summary of the procedures and outcomes from the initial data preparation or analysis.
This new edition has been completely updated to accommodate the needs of users of SPSS Release 12 and 13 for Windows, whilst still being applicable to those using SPSS Release 11 and 10. Alan Bryman and Duncan Cramer provide a non-technical approach to quantitative data analysis and a user-friendly introduction to the widely used SPSS. No previous familiarity with computing or statistics is required to benefit from this step-by-step guide to techniques including: Non-parametric tests Correlation Simple and multiple regression Multivarate analysis of variance and covariance Factor analysis The authors discuss key issues facing the newcomer to research, such as how to decide which statistical procedure is suitable, and how to interpret the subsequent results. Each chapter contains worked examples to illustrate the points raised and ends with a comprehensive range of exercises which allow the reader to test their understanding of the topic. This new edition of this hugely successful textbook will guide the reader through the basics of quantitative data analysis and become an essential reference tool for both students and researchers in the social sciences. The datasets used in Quantitative Data Analysis for SPSS Release 12 and 13 are available online at www.psypress.com/brymancramer/ .
Author: Alan Bryman
Publisher: Psychology Press
Release Date: 1994
Genre: Social Science
Most introductions to the techniques of statistical analysis concentrate on the often complex statistical formulae involved. Many students find these formulae extremely daunting, yet in practice computers are increasingly used to perform the same calculations in seconds. Quantitative Data Analysis for Social Scientists is designed as a non-technical guide, ignoring the traditional formulaic methods and introducing students to the most widely used computer package for analysing quantitative data. This is the Statistical Package for the Social Sciences (SPSS), whose most recently released versions (for both mainframe computers and IBM-compatible personal computers) are here employed. The authors have assumed no previous familiarity with either statistics or computing, and take the reader step-by-step through each of the techniques for which SPSS can be used.
Author: Carol S. Aneshensel
Release Date: 2013
Genre: Social Science
This book presents a method for bringing data analysis and statistical technique into line with theory. The author begins by describing the elaboration model for analyzing the empirical association between variables. She then introduces a new concept into this model, the focal relationship. Building upon the focal relationship as the cornerstone for all subsequent analysis, two analytic strategies are developed to establish its internal validity: an exclusionary strategy to eliminate alternative explanations, and an inclusive strategy which looks at the interconnected set of relationships predicted by theory. Using real examples of social research, the author demonstrates the use of this approach for two common forms of analysis, multiple linear regression and logistic regression. Whether learning data analysis for the first time or adding new techniques to your repertoire, this book provides an excellent basis for theory-based data analysis.
This Eighth Edition of Social Statistics for a Diverse Society continues to emphasize intuition and common sense, while demonstrating that social science is a constant interplay between methods of inquiry and important social issues. Recognizing that today’s students live in a world of growing diversity and richness of social differences, authors Chava Frankfort-Nachmias and Anna Leon-Guerrero use research examples that show how statistics is a tool for understanding the ways in which race, class, gender, and other categories of experience shape our social world and influence social behavior. In addition, guides for reading and interpreting the research literature help students acquire statistical literacy, while SPSS demonstrations and a rich variety of exercises help them hone their problem-solving skills.
Author: Rachad Antonius
Release Date: 2003-01-22
Genre: Social Science
This is a textbook for introductory courses in quantitative research methods across the social sciences. It offers a detailed explanation of introductory statistical techniques and presents an overview of the contexts in which they should be applied.