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AveGali [126]
3 years ago
9

ABC will purchase a machine that will cost $2,575,000. Required modifications will cost $375,000. ABC will need to invest $75,00

0 for additional inventory. The machine has an IRS approved useful life of 7 years; it is presumed to have no salvage value. ABC plans to depreciate the machine by using the straight-line method. The machine is expected to increase ABC's sales revenues by $1,890,000 per year; operating costs excluding depreciation are estimated at $454,600 per year. Assume that the firm's tax rate is 40%. What is the annual operating cash flow?
Business
1 answer:
3241004551 [841]3 years ago
6 0

Answer:

The Annual Operating Cash Flow is $1,029,811.43

Explanation:

Initial Investment = Cost of Machine + Modification Cost

Initial Investment = $2,575,000 + $375,000

Initial Investment = $2,950,000

Salvage Value = $0

Useful Life = 7 years

Depreciation per year = (Initial Investment - Salvage Value) / Useful Life

Depreciation per year = ($2,950,000 - $0) / 7

Depreciation per year = $421,428.57

Annual Operating Cash Flow = (Sales – Operating Costs) * (1 – Tax Rate) + Tax Rate * Depreciation

Annual Operating Cash Flow = ($1,890,000 - $454,600) * (1 - 0.40) + 0.40 * $421,428.571

Annual Operating Cash Flow = $1,435,400 * 0.60 + 0.40 * $421,428.571

Annual Operating Cash Flow = $1,029,811.4284

Annual Operating Cash Flow = $1,029,811.43

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The percentage of variation esplained by the model is given by the determination coefficient, on this case:

R^2 = 0.934^2 =0.872

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Explanation:

Assuming the following dataset:

x                 y

8.6           9.6

9.3           18.5

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Assuming this question: "The data has a correlation coefficient of r = 0.934. Calculate the regression line for this  data. What percentage ofvariation is explained by the regression line? Predict the number of doctors per 10,000 residents in a town with a per capita income of $8500."

We want a linear model like this:

y = mx +b

Where m represent the slope and b the intercept for the linear model. And we cna find the slope and b with the following formulas:

m = \frac{n \sum xy - \sum x \sum y}{n \sum x^2 -(\sum x)^2}

b = \frac{\sum y}{n} -m \frac{\sum x}{n}

And from the dataset we have the following values:

n= 6, \sum x =53, \sum y = 83.7 , \sum xy = 755.89, \sum x^2 = 471.04

And replacing into the equation for m we got:

m =\frac{6(755.89) - (53)(83.7)}{6(471.04) -(53)^2}=5.756

And the intercept:

b = \frac{83.7}{6}-36.895 5.756 \frac{53}{6}=-36.895

And then the linear model is given by:

\hat y = 5.756 x -36.895

We can find the estimation replacing x = 8.5 into the linear model and we got:

\hat y = 5.756(8.5) -36.895=12.031

And we have 12.031 doctors per 10000 residents.

The percentage of variation esplained by the model is given by the determination coefficient, on this case:

R^2 = 0.934^2 =0.872

And we have 87.2% of the variation explained by the linear model given.

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C. I, II, III

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