Correlation and Regression Techniques

J. P. Verma ()
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J. P. Verma: Lakshmibai National Institute of Physical Education, Department of Sport Psychology

Chapter Chapter 7 in Statistics and Research Methods in Psychology with Excel, 2019, pp 237-289 from Springer

Abstract: Abstract Correlation measures linear relationship between any two variables. Although correlation does not authentically explain cause-and-effect relationship, it forms the basis of the regression analysis. In order to find the real relationship, the effect of other variables needs to be controlled and this can be done by using partial correlation. In this chapter, correlation and partial correlation have been discussed along with their application by means of solved examples. To know the relationship between the dependent variable and a group of independent variables, multiple correlation is used. It indicates how accurately dependent variable can be estimated on the basis of the independent variables. The multiple correlation along with its characteristics such as concept of suppression variable and law of diminishing returns has been thoroughly explained in this chapter by means of examples. Finally, least squares method of regression analysis has been shown with the help of a solved example.

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-13-3429-0_7

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DOI: 10.1007/978-981-13-3429-0_7

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