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Data Analysis (A Statistical Primer for Psychology Students) - 9780202309002

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9780202309002
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  • Product Details

    Author:
    Edward L. Wike
    Format:
    Paperback
    Pages:
    266
    Publisher:
    Taylor & Francis (November 15, 2006)
    Language:
    English
    ISBN-13:
    9780202309002
    ISBN-10:
    0202309002
    Weight:
    15.25oz
    Dimensions:
    6" x 9"
    File:
    TAYLORFRANCIS-TayFran_260121055302376-20260121.xml
    Folder:
    TAYLORFRANCIS
    List Price:
    $65.99
    Case Pack:
    10
    As low as:
    $62.69
    Publisher Identifier:
    P-CRC
    Discount Code:
    H
    Country of Origin:
    United States
    Pub Discount:
    30
    Imprint:
    Routledge
  • Overview

    This book is intended for psychology majors and graduate students who are conducting experiments for the first time and are faced with the task of making sense out of their data. This much needed "how-to-do-it" text illustrates the application of statistical methods to the data from small samples. It also serves as a handbook, with twenty-two tables presented at the end of the text that will allow the student to carry out virtually every computation necessary in analyzing his data. Almost all of the examples and illustrations are drawn from actual experiments so that the student can see how professional scientists examine their data. The book also shows students the kinds of data that are encountered in psychological research, the kinds of questions investigators seek to answer, and how these questions are approached.

    The author asserts that statistics is not an abstract discipline but a tool in research. However, the book also imparts a philosophy of data analysis and its meaning, a concern for questions of the function of data analysis and the interpretations that legitimately can be drawn from data. In brief, Data Analysis asks: What kinds of data are met in psychological research? What can we do with these data? What can we conclude as a result of this doing?

    The book will be invaluable for students who, even though they may have taken a previous statistics course, are still unsure of what statistical techniques should be used in interpreting their data.