IDEAS home Printed from https://ideas.repec.org/a/vra/journl/v11y2022i1p185-192.html
   My bibliography  Save this article

Statistical Significance, Power of the Test, and Effect Size Measures in Two-independent-samples t-test case

Author

Listed:
  • Svetlana Todorova

    (University of Economics - Varna, Varna, Bulgaria)

Abstract

Quantitative research is focused on determining the occurrence of certain population phenomena by analyzing data from a sample. Statistics is a tool that is used to check hypotheses and make decisions to reject or fail to reject such hypotheses. In this paper, the various statistical tools are reviewed: the limitations of null hypothesis significance testing and the advantages of using effect size as two measurements, which can provide important information about the results of a study. These measurements also can help interpretation of data results and easily detect trivial effects. Further, it is recommended to establish an appropriate sample size by using the optimum statistical power of the test that the research is designed. We discuss statistical significance, sample size, power of the test, and effect size, all of which have an enormous impact on how we interpret the results.

Suggested Citation

  • Svetlana Todorova, 2022. "Statistical Significance, Power of the Test, and Effect Size Measures in Two-independent-samples t-test case," Izvestia Journal of the Union of Scientists - Varna. Economic Sciences Series, Union of Scientists - Varna, Economic Sciences Section, vol. 11(1), pages 185-192, April.
    • Handle: RePEc:vra:journl:v:11:y:2022:i:1:p:185-192
    as

    Download full text from publisher

    File URL: http://su-varna.org/journal/IJUSV-ESS/2022.11.1/185-192.pdf
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    statistical significance; power of the test; effect size; sample size; independent samples t-test;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software

    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:vra:journl:v:11:y:2022:i:1:p:185-192. 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: Pavel Petrov (email available below). General contact details of provider: https://edirc.repec.org/data/uevecea.html .

    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.