Answer:
The computations are shown below:
Explanation:
(a) Depletion cost per unit
Depletion cost per unit
= $717,963 ÷ 806,700 tons
= $0.89 per ton
(b) The Journal entry to record depletion expense is
Depletion Expense A/c Dr $ 92,293
(103,700 tons × $0.89)
To To Accumulated Depletion A/c $ 92,293
(Being the depletion expense is recorded)
(c) The cost applicable is
= 16,700 unsold units × $0.89
= $14,863
Answer:
As in her worthless note,Sandy has a zero adjusted basis. Her bad debt deduction is Nil according to Section 166 (b).
Section 166(g)(1) states that her capital loss realized on the deemed sale of this stoke is also nil because of zero adjusted basis in her worthless stock.
According to Reg. Sec.1.1366-2(a)(5) if all of her stock is disposed by an S corporation shareholder and loss carryforward attributable to the Section 1366 (d) basis. Limitaitons are permanently disaalowed.
Hence, her $7,400 ordinary loss carryforward can never be deducted by Sandy.
Sandy has no 2012 tax consequences from worthlessness of her Lindlee investments
Answer:
.D.complementary products
Explanation:
A complementary good is a product whose usage is dependent on the availability of another. Complementary goods are, therefore, goods that are used together. For example, A and B will be complimentary goods if the use of A will require the use of B.
Yachts and docks are complementary products because a yacht will require a dock as the base of its operation. Without a dock, yacht operations will be almost impossible. Bill is not making good sales on big yachts because potential customers cannot find sufficient docking space. Other examples of complementary goods are car and petrol, printers and ink cartridges, guns and bullets, and DVD players and DVD disks.
Answer:
(b) purchase contract with no contingencies.
Answer:
The correct answer is letter "C": it yields a larger variety of solutions than generally available using an LP method.
Explanation:
In Goal Programming (GP), the MINIMAX objective aims to minimize the maximum deviation from any type of objective. This approach carries a larger number of solutions compared to the Linear Programming (LP) method which mainly focuses on assigning more weight to each goal in the objective function.