IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-981-13-0827-7_8.html
   My bibliography  Save this book chapter

Correlation

In: Statistical Methods in Medical Research

Author

Listed:
  • Charan Singh Rayat

    (Postgraduate Institute of Medical Education & Research, Department of Histopathology)

Abstract

So far, we have learned to compute certain mathematical measures, representing the performance or behavior of a set of observations. Instead of studying the performance of two sets separately, it would be of great importance to examine the relationship of one set of observations with the other one. Two variables are said to be “correlated” if an increase or decrease in one variable is associated with an increase or decrease in the other. If higher values of one variable are associated with higher values of the other or when the lower values of one variable are associated with the lower values of the other, then it is said to be “directly correlated” or “positively correlated.” In other words, with an increase/decrease in one variable, the other also increases/decreases, respectively. This is said to be positive or direct correlation. On the other hand, in “negative correlation or inverse correlation” with an increase in one variable, the other variable decreases, or with a decrease in one variable, the other variable increases. Pearson’s coefficient of correlation is a measure of the degree of relationship between the two variables. It is denoted by “r” in the case of sample estimate and by “ρ” in the case of the correlation obtained from the whole population. The applications of various formulae for computing “coefficient of correlation” would be dispensed with solved examples in this chapter.

Suggested Citation

  • Charan Singh Rayat, 2018. "Correlation," Springer Books, in: Statistical Methods in Medical Research, chapter 8, pages 61-68, Springer.
  • Handle: RePEc:spr:sprchp:978-981-13-0827-7_8
    DOI: 10.1007/978-981-13-0827-7_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:978-981-13-0827-7_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.