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    Data Analysis for the Social Sciences: Integrating Theory and Practice

    £42.29
    £46.99
    Price-Match is available in-store for recommended titles in CCCU module handbooks
    ISBN: 9781446298480
    Products specifications
    Attribute nameAttribute value
    AuthorBors, Douglas
    Pub Date30/01/2018
    BindingPaperback
    Pages664
    Publisher: SAGE PUBLICATIONS LTD
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    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 - all supported by lots of visuals, interactive demonstrations, author videos, and practice datasets.

    '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.