Question

A grocery store cashier tracked the payment methods used by his customers during each hour of the

cashier's six-hour shift. A portion of his data is shown below.
Hour
Customers Paying with Cash
Customers Paying with Credit
1
9
0
25
6
***
***
***
6
4
10
The cashier made a scatter plot of his data and graphed a line of best fit. He then used his line to
predict how many customers will pay with cash in an hour when 9 customers pay with credit. To best
determine if the cashier's prediction is likely to be accurate, what question should you ask?
O
Does the number of customers paying with cash affect the number of customers paying with credit?
O
Does the number of customers paying with credit affect the number of customers paying with cash?
O
is the correlation positive or negative?

Are the data sets strongly correlated?
B

Answer 1

To best determine if the cashier's prediction is likely to be accurate, the question you should ask is: "Are the data sets strongly correlated?"

By knowing the strength of the correlation between the number of customers paying with cash and the number of customers paying with credit, you can assess how reliable the prediction will be. A strong positive correlation would indicate that as the number of customers paying with credit increases, the number of customers paying with cash also tends to increase. In this case, the cashier's prediction would likely be more accurate. On the other hand, if there is a weak or negative correlation, the prediction may not be as reliable.