Covariance and Correlation are measures of:Group of answer choicesCorrelationDirectionAssociationDispersion

Covariance and correlation are both statistical measures used to assess the relationship between two variables.

1. Covariance indicates the direction of the linear relationship between variables. A positive covariance means that as one variable increases, the other tends to also increase, while a negative covariance indicates that as one variable increases, the other tends to decrease. However, covariance does not provide information about the strength of the relationship.

2. Correlation, on the other hand, not only considers the direction of the association but also standardizes the measure, providing a value between -1 and 1. This allows for a clearer understanding of both the strength and direction of the linear relationship.

Given the answer choices, the best fit for both covariance and correlation is Association since both measures reflect how two variables relate to each other.

So, the correct answer is: Association.