IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-981-95-4318-2_8.html

Quantitative Method Design and Data Analysis

In: Social Science Methodologies for Management Research

Author

Listed:
  • Vissanu Zumitzavan

    (Khon Kaen University, College of Local Administration)

Abstract

This chapter offers an overview of quantitative method design and data analysis within management research. It details key analytical stages—from data cleaning to multivariate techniques and interpretation—whilst addressing the advantages (objectivity, generalisability, replicability) and disadvantages (lack of detail, rigidity) of quantitative methods, further noting how AI augments these methods. The core deliberates widely utilised parametric inferential statistics, including t-tests, ANOVA variants (One-Way, ANCOVA, Two-Way, Repeated Measures), MANOVA, MANCOVA, Pearson Correlation, Multiple Regression Analysis, Logistic Regression Analysis, and Discriminant Analysis, outlining their assumptions, applications, and interpretations. Subsequently, it covers crucial non-parametric tests—Chi-square, Fisher’s Exact, McNemar’s, Sign, Wilcoxon Rank Sum, Cochran Q, Kruskal-Wallis H, and Friedman’s and Spearman’s Rank Correlation—each enlightened with its purpose and fundamental requirements. Overall, the chapter acts as a practical guide to selecting and utilising appropriate statistical techniques for testing varied research hypotheses in management discipline.

Suggested Citation

  • Vissanu Zumitzavan, 2025. "Quantitative Method Design and Data Analysis," Springer Books, in: Social Science Methodologies for Management Research, chapter 0, pages 109-202, Springer.
    • Handle: RePEc:spr:sprchp:978-981-95-4318-2_8
    DOI: 10.1007/978-981-95-4318-2_8
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:sprchp:978-981-95-4318-2_8. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.