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Decision analysis is one of the most methodology applied in firms and organizations with the efforts to handle uncertainty and risks which may occur in particular group. The various approach is put in place so as to ensure proper decisions that will lead to the realization of maximum profits and substantial progress of the business. Risks in business must occur so as to test various aspects that may arise in a firm. However, it is good to note that once there is an opportunity to avoid undertaking risks in organizations, the management should adhere to the appropriate measures required compared to facing the risks. The application of arithmetic knowledge has provided various methods of studying and evaluating different data to approximate the final outcomes. By so doing, the managerial departments who adhere to such practices are not prone to risks and unexpected results in their fields.
Standard deviation is the measure applied to compute and determine the difference range among a particular set of data provided. After the standard deviation, once a small standard deviation is recorded. Conclusions are that data presented close to the expected value. Likewise, a huge difference between the comparisons will indicate that the data is widely spread and chances of realizing the expected value are very minimal. Formulae to approach standard deviation is produced. With the help of such methodologies, organizations can indicate the various sets of data that they should put forward to realize their targets. Unlike those who will not adhere to this and later experience unexpected outcomes which affect the business negatively.
Expected return is a sum of either profits or loss that any investor expects on any investment or savings done. Expected returns are only evident after a standard deviation program is undertaken. Just like in the standard deviation, a formulae procedure is used.
A prudent manager is likely to fall for asset B
Asset D is likely to be preferred by many financial managers.
Various aspects that a company can apply, the percentage expected returns and standard deviation are also provided. Using the data, the most reliable asset that the firm can invest on and acquire positive results without necessarily taking risk is identified after the calculation. For a prudent potential manager to select efficiently the below calculations will apply.
Financially, the holding period return is the sum of profits that an asset has earned during a given period of duration. The holding period return has of late been the most efficient form of evaluating an investment performance. The waiting period can be towards appreciation or depreciation. Holding period return is the kind of percentage in most of the cases. Considering the data provided in in question c one can acquire the expected holding period returns of Mohammed.
HPR = [(1 + r1) x (1 + r2) x (1 + r3) x (1 + r4)] – 1
The formulae above is to apply.
Hence Mohammed’s expected holding period return is likely to be 11.26%.
Decision making over various assets and investments are commons form of activities that the company will always encounter.
By using the expected returns of asset A we can find that the standard deviation of the same asset is 3.86%
Expected return value on asset B.
Hence the standard deviation of asset B is
For a keen financial manager will apply the necessary formulae to determine the lesser risk asset.
Standard deviation of asset A. 3.87%. 3.87/15%=0.26
Standard deviation asset B. 8.942% 8.942/15%=0.63
Hence a champion is likely to choose asset A which is lesser risky
Various data analysis models will always apply so as a justification of any investment can be concluded. Below are some of the methods with the inclusion of cost and their importance. For instance, production of hamburgers at Burger Kings would lead to a realization of different types of meat cuts bonded together to come up with a more cost saving products. Through this particular method, a linear programming format is to apply. Advantages such as cost savings, reduced fat content of the products, and others will come in place.
In the year 1970s massive losses were common in the US motor car industries, the decline in their markets was also too familiar. However the introduction of the quality management program in the Ford industry, an apparent improvement was noted. Giving the company even chances to compete with other huge companies globally.
The scheduling of crews in American Airlines. The scheduling of airline crews is a tough challenge. It is complex since it involves a lot of statistics application. However, its use in any aircraft company will lead to fruitful results. Since the American Airlines adapted to the scheduling program, notable changes and improvements have been made. Integer linear programming is applied. Chances of flight delays and other occurring issues are rarely experienced.
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