Molly, a successful real estate salesperson, took some time off to stay at home with her first child. Days turned into weeks, weeks into months, months into years, until Molly's child was starting school. She decided she needed to head back to her profession and pick up where she left off. During her at-home time, Molly hadn't kept up with any CE requirements, nor had she renewed her license after its expiration almost three years earlier. Can Molly simply pick up where she left off?

The lee family is looking to buy a house in one of two suburban areas just outside of a major city, and air quality is a top priority for them. overall air quality is calculated by taking measures in 100 locations within each suburb and then calculating a measure of central tendency. in one suburb, there is a major bus station that creates very poor air quality at its location but has no impact in the surrounding parts of the suburb. in this situation, which measure of overall suburb air quality would be most useful?

Required prepare the necessary adjusting entries in the general journal as of december 31, assuming the following: on september 1, the company entered into a prepaid equipment maintenance contract. birch company paid $3,400 to cover maintenance service for six months, beginning september 1. the payment was debited to prepaid maintenance. supplies on hand at december 31 are $3,900. unearned commission fees at december 31 are $7,000. commission fees earned but not yet billed at december 31 are $3,500. (note: debit fees receivable.) birch company's lease calls for rent of $1,600 per month payable on the first of each month, plus an annual amount equal to 1% of annual commissions earned. this additional rent is payable on january 10 of the following year. (note: be sure to use the adjusted amount of commissions earned in computing the additional rent.)

You are a manager at asda. you have been given the demand data for the past 10 weeks for swim rings for children. you decide to run multiple types of forecasting methods on the data to see which gives you the best forecast. if you were to use exponential smoothing with alpha =.8, what would be your forecast for week 22? (the forecast for week 21 was 1277.) week demand 12 1317 13 1307 14 1261 15 1258 16 1267 17 1256 18 1268 19 1277 20 1277 21 1297