Quick Telephone Response (QTR) was started several years ago to provide an outsource telephone service for the growing number of small, specialty catalog mail-order companies that commenced operations in recent years. Since most of the calls are received between 10 a.m. and 2 p.m., QTR began offering a telephone answering service to attempt to fill the remainder of the day for its operators. However, as outsource competition has recently increased, QTR analyzed its operations and concluded that it should focus on its core business of providing service to its mail-order clients only. To bring operating costs into line, QTR concluded that it should shed some of its full-time operators and replace them with part-time operators in order to cover the peak mid-day calling period.

Weldon Miller, director of the Telephone Response Operations Department, engaged a consultant to assist in analyzing the situation and determining the number of full-time and part-time employees that will be required to meet QTR's variable operating schedule. Based on a study of one month's activity they concluded that the number of daily orders received for their specialty clients averaged 3,450 with the mid-day period averaging 2,250 orders. They calculated that there would be a need to retain twenty five (25) full-time employees. They further developed two regression analyses. Regression 1 relates to the average of 3,450 orders per day and Regression 2 relates to the average of 2,250 peak mid-day orders. The data resulting from these analyses are presented below.

Regression Equation: where:

E = a + bN

E = Employees

N = Number of orders

Regression 1

a: 21.938

b: 0.0043

standard error of the estimate: 3.721

t-value: 1.95

r-squared: .624

Regression 2

a: -46.569

b: 0.0051

standard error of the estimate: 1.495

t-value: 2.04

r-squared: 0.755

1)Calculate the number of part-time employees that will be needed each day using the regression results relating to the average number of daily orders handled. Round your response to the nearest whole number.

2)Apply the regression results that relate to the average number of orders handled during the mid- day peak period. Calculate the number of part-time employees that will be needed daily. Round your response to the nearest whole number.

3)Of the two regression analyses used select the regression analysis which appears to be the better one and explain the reason for your conclusion.