Correlation coefficients are the statistical values used to measure the strength or weakness of association between two variables. Furthermore, coefficients can determine the degree and direction of the relationship that exists between different variables provided in a given equation ( Heo et al., 2008) . In most cases, the correlation coefficient is denoted by r and can be any number which can either be positive or negative.
In linear correlation analysis, the coefficient is used to serve different purposes. One use of the coefficient in the linear correlation analysis is to determine the direction of movement between the variables. With this regards, the value of the correlation coefficient can either be positive or negative. The correlation coefficient with a negative value shows that the variables are negatively related and moves in opposite direction. In other words, when one variable is increasing, the other variable will be decreasing. On the other hand, the correlation coefficient with a positive value indicates that there is a positive relationship between the variables ( Johnson & Wichern, 2002) . This means that the variables are moving in the same direction such that when one variable is increasing the other variable is also increasing.
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Another use of the correlation coefficient is to determine the strength of association between the variables under investigation. It is important to note that the value of correlation coefficients often range between -1 and + 1 ( Johnson & Wichern, 2002) . Based on this range, it is possible to determine the strength of the relationship between the variables. A correlation coefficient with a value that approaches +1 demonstrates a strong positive association between the variables whiles the coefficient value that is close to -1 show a strong negative relationship between the variables. On the other hand, the value of the correlation coefficient that is close to zero and negative indicates that there is a weak negative relationship between the variable while the coefficient value that is close to zero and positive shows a weak positive correlation.
References
Heo, J. H., Kho, Y. W., Shin, H., Kim, S., & Kim, T. (2008). Regression equations of probability plot correlation coefficient test statistics from several probability distributions. Journal of Hydrology , 355 (1), 1-15.
Johnson, R. A., & Wichern, D. W. (2002). Applied multivariate statistical analysis (Vol. 5, No. 8). Upper Saddle River, NJ: Prentice hall.
