What statistical measure ranges from -1 to +1 and provides insights on the relationship between two variables?

What statistical measure ranges from -1 to +1 and provides insights on the relationship between two variables?

• A. Variance
• B. Standard Deviation
• C. Correlation
• D. Causation

Answer: (C)

The statistical measure that ranges from -1 to +1 and provides insights into the relationship between two variables is correlation. This measure quantifies the degree to which two variables are related. A correlation coefficient closer to +1 indicates a strong positive relationship, meaning that as one variable increases, the other variable tends to increase as well. Conversely, a coefficient closer to -1 implies a strong negative relationship, where an increase in one variable is associated with a decrease in the other. A value around 0 indicates no significant relationship between the variables. Understanding correlation is vital in research and program evaluation because it helps determine how variables interact with one another. This information can guide decision-making and inform further analyses. Other statistical measures mentioned do not provide insights into relationships between variables in the same way; for instance, variance and standard deviation focus on the distribution and variability of a single variable rather than a relationship between two variables, while causation indicates a cause-and-effect relationship rather than merely the strength and direction of a relationship.

The statistical measure that ranges from -1 to +1 and provides insights into the relationship between two variables is correlation. This measure quantifies the degree to which two variables are related. A correlation coefficient closer to +1 indicates a strong positive relationship, meaning that as one variable increases, the other variable tends to increase as well. Conversely, a coefficient closer to -1 implies a strong negative relationship, where an increase in one variable is associated with a decrease in the other. A value around 0 indicates no significant relationship between the variables.

Understanding correlation is vital in research and program evaluation because it helps determine how variables interact with one another. This information can guide decision-making and inform further analyses. Other statistical measures mentioned do not provide insights into relationships between variables in the same way; for instance, variance and standard deviation focus on the distribution and variability of a single variable rather than a relationship between two variables, while causation indicates a cause-and-effect relationship rather than merely the strength and direction of a relationship.