ABSTRACT
This chapter shows that multiple correlation coefficient (R) involves correlation between a combination of variables to increase predictability of the outcome variable. It explores that multiple correlation coefficient has the same basic characteristics as r. The chapter explains that computationally the coefficient of determine is R squared. It examines that the coefficient of determination (R) in percent shows the variance in the outcome variable explained by a combination of variables. The chapter discusses the correlation between the combination of two variables and a third variable. Specifically, the closer the value of R is to zero, the weaker the relationship. For an inverse relationship, the closer R is to –1.00, the stronger the relationship. R multiplied by 100% indicates the percentage of variance in one variable accounted for by the combination of predictors.
