The
invention and rapid diffusion of more productive agricultural
techniques during the 1970s and 1980s is called the Green Revolution. The Green Revolution involves introduction <span>of new higher-yield seeds and the expanded use of fertilizers. These are the two main practices of the Green revolution.
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Answer:
$1, 727.68
Explanation:
Cheryl wants to have $2000 three years from now in an account that pays 5%
The $2000 is equivalent to the Future value when applying the compound interest formula. The present value is the amount she needs to invest now.
Fv= PV (1+5/100)^3
$2000 = PV(1+0.05)^3
$2000 =Pv 1.157625
Pv = $2000/1.157625
Pv= 1,727.68
Cheryl has to invest $1, 727.68
Answer:
The company must sell $300,000 to earn a target profit of $90,000.
Explanation:
Contribution margin per unit = Sales price per unit - Variable costs per unit. = $60.00 - $15.00 = $45
Contribution margin ratio = Contribution margin per unit / Selling price per unit = $45 / $65 = 0.75, or 75%
Total Fixed Costs = $135,000
Target profit = $90,000
Sales in dollars to earn the target profit = (Fixed cost + Targeted profit) / Contribution margin ratio = ($135,000 + $90,000) / 75% = $300,000
Therefore, the company must sell $300,000 to earn a target profit of $90,000.
Answer:
a. 8.30 %
b. $918.65
c. 16,60%
Explanation:
a. What is the bond's yield to maturity
Using a Financial Calculator Enter the following respective values and find i.
N = 10×2 = 20
Pmt = $1,000 × 8.6 % / 2 = $43
P/yr = 2
Pv = $ 1,035.77
Fv = $1,000
YTM / i = ?
i = 8.30%
Therefore yield to maturity is 8.30 %
b. What will be the bond's price
Using a Financial Calculator Enter the following respective values and find Pv .
N = 10×2 = 20
Pmt = $1,000 × 8.6 % / 2 = $43
P/yr = 2
Fv = $1,000
YTM / i = 9.90%
Pv = ?
Pv = $ 918.65
Therefore the bond's price is $918.65
c. What is the bond's yield to maturity
bond's yield to maturity - expressed as an APR = 8.30 % × 2
= 16,60%
Answer:
The options for this question are the following:
a. 1
b. 2
c. 0.5
d. 1.5
The correct answer is a. 1
.
Explanation:
Group analysis or grouping is the task of grouping a set of objects in such a way that the members of the same group (called a cluster) are more similar, in some sense or another. It is the main task of exploratory data mining and is a common technique in the analysis of statistical data. It is also used in multiple fields such as machine learning, pattern recognition, image analysis, information search and retrieval, bioinformatics, data compression and graphic computing.
Group analysis is not in itself a specific algorithm, but the task pending solution. Clustering can be done using several algorithms that differ significantly in your idea of what constitutes a group and how to find them efficiently. Classical group ideas include small distances between members of the group, dense areas of the data space, intervals or particular statistical distributions. Clustering, therefore, can be formulated as a multi-objective optimization problem. The appropriate algorithm and the values of the parameters (including values such as the distance function to use, a density threshold or the number of expected groups) depend on the set of data analyzed and the use that will be given to the results. Grouping as such is not an automatic task, but an iterative process of data mining or interactive multi-objective optimization that involves trial and failure. It will often be necessary to pre-process the data and adjust the model parameters until the result has the desired properties.