Every valid argument with true premises has a true conclusion. Rewrite the above statement in the form V[x] x, if [y] then [z] (
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Answer:
(a) he total realized gain is $1,123,200.
(b) § 1250 gain realized in 2019 is, $276,480.
(c) The § 1231 gain realized in 2019 is, $77040.
Step-by-step explanation:
(a)
Compute Skylar's total realized gain under the installment sales method as follows:
Cash Received = $144,000
Note Receivable = $1,440,000
Total Selling Price = Cash Received + Note Receivable
= $144,000 + $1,440,000
= $1,584,000
Cost of Property = $1,152,000
Deducted Depreciation = $691,200
Adjusted Bias = Cost of Property - Deducted Depreciation
= $1,152,000 - $691,200
= $460,800
Total Realized Gain = Total Selling Price - Adjusted Bias
= $1,584,000 - $460,800
= $1,123,200
Thus, the total realized gain is $1,123,200.
(b)
§ 1250 gain will be same as the amount of depreciation that was in excess of the straight-line amount.
Thus, § 1250 gain realized in 2019 is, $276,480.
(c)
Total Realized Gain = $1,123,200
§ 1250 gain realized in 2019 = $276,480
§ 1231 gain = Total Realized Gain - § 1250 gain realized in 2019
= $1,123,200 - $276,480
= $846,720
The total selling price was, $1,584,000.
Compute the percentage of § 1231 gain of the selling price as follows:
§
Thus, 53.5% of the cash received will be the § 1231 gain.
§ 1231 gain realized in 2019 = $144,000 × 53.5% = $77,040.
Thus, the § 1231 gain realized in 2019 is, $77040.
Answer:
(a) The joint PMF of W, L and T is:
(b) The marginal PMF of W is:
Step-by-step explanation:
Let <em>X</em> = number of soccer games played.
The outcome of the random variable <em>X</em> are:
<em>W</em> = if a game won
<em>L</em> = if a game is lost
<em>T</em> = if there is a tie
The probability of winning a game is, P (<em>W</em>) = 0.60.
The probability of losing a game is, P (<em>L</em>) = 0.30.
The probability of a tie is, P (<em>T</em>) = 0.10.
The sum of the probabilities of the outcomes of <em>X</em> are:
P (W) + P (L) + P (T) = 0.60 + 0.30 + 0.10 = 1.00
Thus, the distribution of W, L and T is a appropriate probability distribution.
(a)
Now, the outcomes W, L and T are one experiment.
The distribution of <em>n</em> independent and repeated trials, each having a discrete number of outcomes, each outcome occurring with a distinct constant probability is known as a Multinomial distribution.
The outcomes of <em>X</em> follows a Multinomial distribution.
The joint probability mass function of <em>W</em>, <em>L</em> and <em>T</em> is:
The soccer tournament consists of <em>n</em> = 5 games.
Then the joint PMF of W, L and T is:
(b)
The random variable <em>W</em> is defined as the number games won in the soccer tournament.
The probability of winning a game is, P (W) = <em>p</em> = 0.60.
Total number of games in the tournament is, <em>n</em> = 5.
A game is won independently of the others.
The random variable <em>W</em> follows a Binomial distribution.
The probability mass function of <em>W</em> is:
Thus, the marginal PMF of W is: