It is usually noted that correlation does not imply causation, but there are some correlations which are causation as well.
A correlation is when there is a relationship between two variables while causation is when the outcome of one variable affects the outcome of the other variable.
From the first option, though there may be a positive relationship between sales of jeans and sales of slacks, but the purchase of jeans does not mean that you have to purchase a slack, thus, there is no causation.
For the second option, though there may be positive relationship between <span>the number of aisles and the number of products in a supermarket, but a supermarket can have many aisles with few products, i.e. many aisles does not automatically imply many products, thus, there is no causation.
For the third option, though there may be a positive relationship between </span><span>the number of swimmers and the number of sunbathers at a beach, but all swimmers in a beach are not sunbathers and all sunbathers are not swimmers. Thus, a swimmer does not imply a sunbather and a sunbather does not imply a swimmer. Thus, there is no causation.
For the last option, it is generally known that the more you practice an activity, the better you get in that activity. Thus, there exist a relationship between </span><span>the number of hours spent practicing archery and the number of bull's-eyes an archer can hit and there also exist causation because the number of bull's-eye an archer can hit is directly dependent on the number of hours the archer spent practicing.
Therefore, the </span><span>correlation that is most likely a causation is </span><span>the positive correlation between the number of hours spent practicing archery and the number of bull's-eyes the archer can hit.</span>
4x - 12
You can get this by switch the f(x) and the x and then solving for the new f(x)
Yes it’s right for this problem
Answer:
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Step-by-step explanation:
