IDEAS home Printed from https://ideas.repec.org/a/arp/ajoams/2020p145-152.html
   My bibliography  Save this article

Statistical Measures of Location: Mathematical Formula Versus Geometric Approach

Author

Listed:
  • ADENIRAN Adefemi Tajudeen*

    (Department of Statistics, Faculty of Science, University of Ibadan, Ibadan, Oyo State, Nigeria)

  • OJO Johnson Funminiyi

    (Department of Statistics, Faculty of Science, University of Ibadan, Ibadan, Oyo State, Nigeria)

  • FAWEYA Olanrewaju

    (Department of Statistics, Faculty of Science, Ekiti State University, Ado-Ekiti, Ekiti State, Nigeria)

  • BALOGUN Kayode

    (Department of Statistics, Federal Scool of Statistics Ibadan, Oyo State, Nigeria)

Abstract

Graphical method and mathematical formula are the two approaches for estimating measures of location. Understanding of many instructors of introductory statistics classes are: mean cannot be graphically determined and numerical (formula) approach is more precise than geometrical technique. Contrary to their understanding, this study estimate mean of a dataset geometrically (from histogram) by determining the centroid of histogram drawn from such data set. In addition, we also make known that mathematical formulas for mean, median and mode were derived geometrically (either from ogive or histogram). Finally, the research illustrated the two techniques with a survey data and established that the two approaches produce same results.

Suggested Citation

  • ADENIRAN Adefemi Tajudeen* & OJO Johnson Funminiyi & FAWEYA Olanrewaju & BALOGUN Kayode, 2020. "Statistical Measures of Location: Mathematical Formula Versus Geometric Approach," Academic Journal of Applied Mathematical Sciences, Academic Research Publishing Group, vol. 6(7), pages 145-152, 07-2020.
  • Handle: RePEc:arp:ajoams:2020:p:145-152
    DOI: 10.32861/ajams.67.145.152
    as

    Download full text from publisher

    File URL: https://www.arpgweb.com/pdf-files/ajams6(7)145-152.pdf
    Download Restriction: no

    File URL: https://www.arpgweb.com/journal/17/archive/07-2020/7/6
    Download Restriction: no

    File URL: https://libkey.io/10.32861/ajams.67.145.152?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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:arp:ajoams:2020:p:145-152. 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: Managing Editor (email available below). General contact details of provider: http://arpgweb.com/index.php?ic=journal&journal=17&info=aims .

    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.