Six Sigma Black Belt Certified Practice Exam

The best statistical tool for analyzing the relationship between two continuous variables is regression analysis. This technique allows for the modeling of the relationship between a dependent variable and one or more independent variables, providing insight into how changes in one variable affect another. Regression analysis not only quantifies the strength and direction of the relationship but also allows for predictions based on that relationship. While correlation analysis also evaluates the relationship between two continuous variables, it focuses primarily on the strength and direction of the linear relationship without specifying a cause-and-effect dynamic. In contrast, regression analysis does provide a framework for understanding how one variable influences another, which is often more informative in practical applications. ANOVA (Analysis of Variance) is used to compare the means of different groups rather than directly assessing the relationship between two continuous variables, making it less suitable for this purpose. The chi-square test is primarily used for categorical data to assess how expectations compare to actual observed data and is not applicable to continuous variables. Therefore, regression analysis stands out as the most comprehensive method for examining and predicting relationships between continuous variables.