Problem 9-09 (algorithmic) epsilon airlines services predominantly the eastern and southeastern united states. the vast majority of epsilon’s customers make reservations through epsilon’s website, but a small percentage of customers make reservations via phones. epsilon employs call center personnel to handle these reservations and to deal with website reservation system problems and for the rebooking of flights for customers whose plans have changed or whose travel is disrupted. staffing the call center appropriately is a challenge for epsilon’s management team. having too many employees on hand is a waste of money, but having too few results in very poor customer service and the potential loss of customers. epsilon analysts have estimated the minimum number of call center employees needed by day of the week for the upcoming vacation season (june, july, and the first two weeks of august). these estimates are as follows: day minimum number of employees needed monday 50 tuesday 90 wednesday 45 thursday 65 friday 75 saturday 65 sunday 45 the call center employees work for five consecutive days and then have two consecutive days off. an employee may start work on any day of the week. each call center employee receives the same salary. assume that the schedule cycles and ignore start up and stopping of the schedule. develop a model that will minimize the total number of call center employees needed to meet the minimum requirements.

Starting at age 30, you deposit $2000 a year into an ira account for retirement. treat the yearly deposits into the account as a continuous income stream. if money in the account earns 7%, compounded continuously, how much will be in the account 35 years later, when you retire at age 65? how much of the final amount is interest?

Journalize the following transactions that occurred in september 2015 for aquamarines. no explanations are needed. identify each accounts payable and accounts receivable with the vendor or customer name. sep. 3 purchased merchandise inventory on account from shallin wholesalers, $5,000. terms 1/15, n/eom, fob shipping point. 4 paid freight bill of $80 on september 3 purchase. 4 purchased merchandise inventory for cash of $1,700. 6 returned $500 of inventory from september 3 purchase. 8 sold merchandise inventory to hermosa company, $6,000, on account. terms 2/15, n/35. cost of goods, $2,640. 9 purchased merchandise inventory on account from thomas wholesalers, $8,000. terms 2/10, n/30, fob destination. 10 made payment to shallin wholesalers for goods purchased on september 3, less return and discount. 12 received payment from hermosa company, less discount. 13 after negotiations, received a $200 allowance from thomas wholesalers. 15 sold merchandise inventory to jordan company, $2,500, on account. terms 1/10, n/eom. cost of goods, $1,050. 22 made payment, less allowance, to thomas wholesalers for goods purchased on september 9. 23 jordan company returned $400 of the merchandise sold on september 15. cost of goods, $160. 25 sold merchandise inventory to smithsons for $1,100 on account that cost $400. terms of 2/10, n/30 were offered, fob shipping point. as a courtesy to smithsons, $75 of freight was added to the invoice for which cash was paid by aquamarines. 26 after negotiations, granted a $100 allowance to smithsons for merchandise purchased on september 25. 29 received payment from smithsons, less allowance and discount. 30 received payment from jordan company, less return.

One question from a survey was "how many credit cards do you currently have? " the results of the survey are provided. complete parts (a) through (g) below. click the icon to view the survey results. (a) determine the mean number of credit cards based on the raw data. the mean is 3.113.11 credit cards. (type an integer or a decimal. do not round.) (b) determine the standard deviation number of credit cards based on the raw data. the standard deviation is 1.9111.911 credit cards. (round to three decimal places as needed.) (c) determine a probability distribution for the random variable, x, the number of credit cards issued to an individual. x (# of cards) p(x) x (# of cards) p(x) 1 0.280.28 6 nothing 2 nothing 7 nothing 3 nothing 8 nothing 4 nothing 9 nothing 5 nothing 10 nothing (type integers or decimals. do not round.)