Question

Kathleen McFadden's restaurant in Boston, has recorded the following data for eight recent customers: Customer Number, i No. of Trips to kitchen by Waitress (x;) ovo AWN Minutes from Time Food Ordered Until Food Arrived (y;) 7.25 10.75 11.00 7.00 6.00 6.25 8.00 10.25 a w NNNAAW a) Kathleen wants you to graph the eight points (xi, yi), i = 1, 2, ..., 8. She has been concerned because customers have been waiting too long for their food, and this graph is intended to help her find possible causes of the problem. Choose the correct graph below. a) Kathleen wants you to graph the eight points (xi, yi), i = 1, 2, ..., 8. She has been concerned because customers have been waiting too long for their food, and this graph is intended to help her find possible cause of the problem.

Answer 1

To identify possible causes of delays at Kathleen McFadden's restaurant, the eight customer data points should be graphed on a scatter plot with the number of trips to the kitchen on the x-axis and the wait time for food on the y-axis.

Step-by-step explanation:

Graphing Points to Identify Causes of Delays

Since we do not have a graph to choose from and cannot graph the points directly here, I will guide you on how to create a graph from Kathleen McFadden's restaurant data. To graph the eight points (xi, yi), plot the number of trips to the kitchen by the waitress on the x-axis (which represents the independent variable x) against the minutes from the time food was ordered until food arrived on the y-axis (which represents the dependent variable y). Once plotted, Kathleen could look for trends such as a positive correlation between the number of trips to the kitchen and the waiting time, which might suggest inefficiencies in kitchen procedures or staffing issues. If the points are scattered without any discernible pattern, this might indicate that the cause of delays is inconsistent and may not be related to the number of trips the waitress makes to the kitchen.

For the scenarios given in the question, the data concerning waiting times, standard deviation, and customer arrival rates illustrate the importance of understanding distribution and variation in service times. These examples could be used as additional data points for comparison to identify if similar patterns of variation exist in Kathleen's restaurant.