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  • The Philosophy of Quantitative Methods: Understanding Statistics

    The Philosophy of Quantitative Methods by Haig, Brian D.;

    Understanding Statistics

    Series: Understanding Statistics;

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    Product details:

    • Publisher OUP USA
    • Date of Publication 15 March 2018

    • ISBN 9780190222055
    • Binding Paperback
    • No. of pages168 pages
    • Size 137x211x12 mm
    • Weight 277 g
    • Language English
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    Short description:

    The Philosophy of Quantitative Methods undertakes a philosophical examination of a number of important quantitative research methods within the behavioral sciences in order to overcome the non-critical approaches typically provided by textbooks. These research methods are exploratory data analysis, statistical significance testing, Bayesian confirmation theory and statistics, meta-analysis, and exploratory factor analysis. Further readings are provided to extend the reader's overall understanding of these methods.

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    Long description:

    The Philosophy of Quantitative Methods focuses on the conceptual foundations of research methods within the behavioral sciences. In particular, it undertakes a close philosophical examination of a variety of quantitative research methods that are prominent in (or relevant for) the conduct of research in these fields. By doing so, the deep structure of these methods is examined in order to overcome the non-critical approaches typically found in the existing literature today.

    In this book, Brian D. Haig focuses on the more well-known research methods such as exploratory data analysis, statistical significant testing, Bayesian confirmation theory and statistics, meta-analysis, and exploratory factor analysis. These methods are then examined with a philosophy consistent of scientific realism. In addition, each chapter provides a helpful Further Reading section in order to better assist the reader in extending their own thinking and research methods specific to their needs.

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    Table of Contents:

    Chapter 1: Introduction
    Chapter 2: Exploratory Data Analysis
    Chapter 3: Tests of Statistical Significance
    Chapter 4: Bayesianism
    Chapter 5: Meta-Analysis
    Chapter 6: Exploratory Factor Analysis
    Chapter 7: Conclusions

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