the radius and circumference of several objects were measured.\nradius and circumference of objects\n|radius…

the radius and circumference of several objects were measured.\nradius and circumference of objects\n|radius (in.)|circumference (in.)|\n|----|----|\n|3|18.8|\n|4|25.1|\n|6|37.7|\n|9|56.5|\nwhich best describes the strength of the correlation, and what is true about the causation between the variables?\nit is a weak positive correlation, and it is not likely causal.\nit is a weak positive correlation, and it is likely causal.\nit is a strong positive correlation, and it is not likely causal.\nit is a strong positive correlation, and it is likely causal.
Answer
Explanation:
Step 1: Calculate the expected relationship using the formula for circumference
The formula for the circumference of a circle is ( C = 2\pi r ), which is a perfect linear relationship.
Step 2: Assess correlation strength
Since the relationship is defined by a mathematical formula, the correlation should be extremely strong (close to +1), indicating a strong positive correlation.
Step 3: Determine causation
The radius directly determines the circumference via the formula, so there is a causal relationship where changing the radius causes a change in circumference.
Answer:
It is a strong positive correlation, and it is likely causal.