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University researchers examining the behavior of local bank teller lines have developed a stochastic model that integrates pattern analysis of most popular services by hour, and general customer traffic averages. When implemented, despite the significant and random fluctuations in actual line length, including even longer lines at moments, the model was able to better process peak crowds with the same number of tellers by shortening average time at the window. Accordingly, the stochastic model is likely to provide a higher quality of service for the customer.
Which of the following, if true, most strengthens the argument?
A. The model can also predict local traffic patterns during rush hour as well as quieter hours.
B. A similar study by a local bank also improve line flow by adding a 'flex' employee to supply additional teller capacity at peak times.
C. Extreme crowding at bank teller lines remains relatively rare at most local banks.
D. he risk that long teller lines could anger customers is markedly intensified when lines are excessively long.
E. Customer aversion to significant spikes in line length is mitigated if customers perceive the line to move quickly.
OA E
Source: EMPOWERgmat
Which of the following, if true, most strengthens the argument?
A. The model can also predict local traffic patterns during rush hour as well as quieter hours.
B. A similar study by a local bank also improve line flow by adding a 'flex' employee to supply additional teller capacity at peak times.
C. Extreme crowding at bank teller lines remains relatively rare at most local banks.
D. he risk that long teller lines could anger customers is markedly intensified when lines are excessively long.
E. Customer aversion to significant spikes in line length is mitigated if customers perceive the line to move quickly.
OA E
Source: EMPOWERgmat
