A piece of equipment has a first cost of $145,000, a maximum useful life of 7 years, and a market (salvage) value described by the relation S-120,000 -25,000k, where k is the number of years since it was purchased. The salvage value cannot go below zero. The AOC series is estimated using AOC = 60,000+ 13,000k. The interest rate is 13% per year. Determine the economic service life and the respective AW. The economic service life is year(s) and the AW value is $[

Furniture Forecasting Futura Furniture Products manufactures upscale office furniture for the Office of the Future. The sales division comprises regionally based sales offices made up of sales representatives and regional managers. Sales representativeswho report to the regional managersconduct direct sales efforts with customers in their regions. As part of the sales process, representatives gather information about likely future orders and convey that information back to the regional managers. Regional managers use that information to create sales forecasts, which are then used as the basis for manufacturing schedules. Sales representatives and regional managers are both compensated on a salary plus commission (percentage of revenue as pricing is centrally controlled). However, a regional managers commission is adjusted based on regional sales that exceed the forecasted budget. Corporate managers are concerned with one of Futuras key products, the DeskPod. They worry that DeskPod forecasts are inaccurate, causing extreme havoc in the manufacturing process. How are the forecasts likely to be inaccurate? What do you think is driving this inaccuracy? How might this problem be solved?

Logarithms are especially useful for comparing series with two divergent scales since 10 percent growth always looks the same, regardless of the starting level. When absolute levels matter, the raw data are more appropriate, but when growth rates are whats important, log scales are better.

Why has coal dominated as a fuel source for 24/7/365 electricity generation for so many decades?

Estimate the double-log (log linear) time trend model for log cruise ship arrivals against log time. Estimate a linear time trend model of cruise ship arrivals against time. Calculate the root mean square error between the predicted and actual value of cruise ship arrivals. Is the root mean square error greater for the double log non-linear time trend model or for the linear time trend model?