An adjustable-rate mortgage is one can change. stays the same. only goes up. only goes down.

Classifying inflows and outflows of cash classify each of the following items as an inflow (i) or an outflow (o) of cash, or as neither (n). lg 2 lg 2 item change ($) item change ($) cash +100 accounts receivable −700 accounts payable −1,000 net profits +600 notes payable +500 depreciation +100 long-term debt −2,000 repurchase of stock +600 inventory +200 cash dividends +800 fixed assets +400 sale of stock +1,000

The monthly sales for yazici​ batteries, inc., were as​ follows: month jan feb mar apr may jun jul aug sept oct nov dec sales 19 20 17 12 11 18 16 17 19 22 21 24 this exercise contains only parts b and c. ​b) the forecast for the next month​ (jan) using the naive method​ = nothing sales ​(round your response to a whole​ number). the forecast for the next period​ (jan) using a​ 3-month moving average approach​ = nothing sales ​(round your response to two decimal​ places). the forecast for the next period​ (jan) using a​ 6-month weighted average with weights of 0.10​, 0.10​, 0.10​, 0.20​, 0.20​, and 0.30​, where the heaviest weights are applied to the most recent month​ = nothing sales ​(round your response to one decimal​ place). using exponential smoothing with alpha ​= 0.40 and a september forecast of 21.00​, the forecast for the next period​ (jan) = nothing sales ​(round your response to two decimal​ places). using a method of trend​ projection, the forecast for the next month​ (jan) = nothing sales ​(round your response to two decimal​ places). ​c) the method that can be used for making a forecast for the month of march is ▾ a 3-month moving average a 6-month weighted moving average exponential smoothing the naive method a trend projection .

An important application of regression analysis in accounting is in the estimation of cost. by collecting data on volume and cost and using the least squares method to develop an estimated regression equation relating volume and cost, an accountant can estimate the cost associated with a particular manufacturing volume. consider the following sample of production volumes and total cost data for a manufacturing operation. production volume (units) total cost ($) 400 4000 450 5000 550 5400 600 5900 700 6400 750 7000 compute b 1 and b 0 (to 2 decimals if necessary). b 1 b 0 complete the estimated regression equation (to 2 decimals if necessary). = + x what is the variable cost per unit produced (to 1 decimal)? $ compute the coefficient of determination (to 4 decimals). note: report r 2 between 0 and 1. r 2 = what percentage of the variation in total cost can be explained by the production volume (to 2 decimals)? % the company's production schedule shows 500 units must be produced next month. what is the estimated total cost for this operation (to 2 decimals)? $