Curtis Inc. uses a job order costing system. Manufacturing overhead is applied on the basis of direct labor cost. Total manufacturing overhead was estimated to be $67,995 for the year; direct labor was estimated to total $151,100. (1/1) (12/31)
Raw Materials Inventory $ 11,900 $ 13,500
Work in Process Inventory $ 22,200 $ 18,200
Finished Goods Inventory $ 35,300 $ 39,800
The following transactions have occurred during the year.
Raw materials purchases $ 118,000
Direct materials used $ 109,500
Direct labor $ 147,200
Indirect materials used $ 6,900
Indirect labor $ 15,100
Factory equipment
depreciation $ 24,200
Factory rent $ 19,200
Factory utilities $ 9,400
Other factory costs $ 8,100
(a) Calculate the predetermined overhead rate.(b) Calculate cost of goods manufactured.(c) Calculate the over- or underapplied overhead. (Input all amounts as positive values.)(d) Calculate adjusted cost of goods sold.

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 .

At a student café, there are equal numbers of two types of customers with the following values. the café owner cannot distinguish between the two types of students because many students without early classes arrive early anyway (i. e., she cannot price-discriminate). students with early classes students without early classes coffee 70 60 banana 51 101 the marginal cost of coffee is 10 and the marginal cost of a banana is 40. the café owner is considering three pricing strategies: 1. mixed bundling: price bundle of coffee and a banana for 161, or just a coffee for 70. 2. price separately: offer coffee at 60, price a banana at 101. 3. bundle only: coffee and a banana for 121. do not offer goods separately. assume that if the price of an item or bundle is no more than exactly equal to a student's willingness to pay, then the student will purchase the item or bundle. for simplicity, assume there is just one student with an early class, and one student without an early class. price strategy revenue from pricing strategy cost from pricing strategy profit from pricing strategy 1. mixed bundling $ $ $ 2. price separately $ $ $ 3. bundle only $ $ $ pricing strategy yields the highest profit for the café owner.

David consumes two things: gasoline (g) and bread (b). david's utility function is u(g, b) = 10g^0.25 b^0.75. use the lagrange technique to solve for david's optimal choices of gasoline and bread as a function of the price of gasoline, p_g, the price of bread, p_b, and his income m. with recent decrease in the price of gasoline (maybe due to external shock such as shale gas production) does david increase his consumption of gasoline? for david, how does partial differential g/partial differential p_g depend on his income m? that is, how does david's change in gasoline consumption due to an increase in the price of gasoline depend on his income level? to answer these questions, find the cross-partial derivative, |partial differential^2 g/partial differential m partial differential p_g.