Relationship between correlation and regression
Correlation and regression are some of the most common and useful methods of statistics used by statisticians. Correlation is used to describe the degree of the relationship between two variables while on the other hand regression is used to describe the relationship between a single dependent and independent variable. It therefore helps to tell us about the linear association that exists between two variables.
There are some similarities between these two approaches. One is that regression is derived from correlation as regression equation is obtained once the correlation value is known (Jon, 2000). Another similarity is that both correlation and regression analysis deal with relationships among variables. Furthermore, both analyses are not interpreted as causing cause-and-effect relationship but rather they indicate how or to what extent variables are associated.
Consequently, correlation and regression have some differences. There is no reference to causation in correlation and there is no variable considered as independent or dependent. The two separate variables have specific relationship and co-relate. On the other hand, in regression one of the variables is considered to be independent and is also called predictor and the other dependent variable also called criterion variable. Therefore, in regression analysis one variable causes certain percentage of change on the other variable (Jon, 2000). These two variables are important in the regression equation because they help to describe the relationship between these two variables. Results of regression are more generalizable compared to those from correlation.
Correlation is applicable in various research work which includes observational research, survey research and archival research such as violence and economic. This is because; it helps to give the degree of relationship or association between variables. Regression analysis is applicable in quantitative researches as it helps to describe the relationship that exists between the independent and dependent variables.
Reference
Jon, R. (2000). Correlation or regression. Retrieved from: http://www.le.ac.uk/bl/gat/virtualfc/Stats/regression/regrcorr.html
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