Answer:
Covariation between the variables due to the fact that non experimental method enables us to observe covariation.
Explanation: covariance helps us to know the degree at which two variables varies from each other. Covariation helps us to know the degree to which two substance vary together like if a change in one leads to a greater changer in the other, no change at all or even a uniform change and if a change in one variable causes an inverse change or behind-me change( tandem or one behind the other change).it seeks to determine the the relationship between two various as per cause and effect.
Answer:
Covariation between variable
Explanation:
The idea that covariation within a set of variables may be organized in a task-specific way to reduce variance of important performance variables led to the development of a few approaches that share some features with the UCM hypothesis but also differ in important ways. One of them is the notion of goal-equivalent manifold.
This approach is based on a body-goal variability mapping derived from goal functions that link body variables, goal variables, and the environment needed for perfect task execution.
Another related approach is based on mapping a redundant set of elemental variables on task-related variables and on considering variability of task performance as a function of three potentially independent contributing factors: tolerance, noise, and covariation.
