A number between -6 and 14 will be chosen at random. What is the pr.pdf

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A number between -6 and 14 will be chosen at random. What is the probability that the point selected will be within 2 units of the point with coordinate 8? Solution Total number of possibilities = 19 ( -5 to 13) Favourable outcomes = 5 (6 to 10) Probability = Favourable outcomes/Total number of possibilities = 5/19.

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Bayes Solution Bayes\' theorem deals with the role of new information in revising probability estimates. The theorem assumes that the probability of a hypothesis (the posterior probability) is a function of new evidence (the likelihood) and previous knowledge (prior probability). The theorem is named after Thomas Bayes (1702–1761), a nonconformist minister who had an interest in mathematics. The basis of the theorem is contained in as essay published in the Philosophical Transactions of the Royal Society of London in 1763. Bayes\' theorem is a logical consequence of the product rule of probability, which is the probability (P) of two events (A and B) happening— P(A,B)—is equal to the conditional probability of one event occurring given that the other has already occurred—P(A|B)—multiplied by the probability of the other event happening—P(B). The derivation of the theorem is as follows: P(A,B) = P(A|B)×P(B) = P(B|A)×P(A) Thus: P(A|B) = P(B|A)×P(A)/P(B). Bayes\' theorem has been frequently used in the areas of diagnostic testing and in the determination of genetic predisposition. For example, if one wants to know the probability that a person with a particular genetic profile (B) will develop a particular tumour type (A)—that is, P(A|B). Previous knowledge leads to the assumption that the probability that any individual will develop the specific tumour (P(A)) is 0.1 and the probability that an individual has the particular genetic profile (P(B)) is 0.2. New evidence establishes that the probability that an individual with the tumor—P(B|A)—has the genetic profile of interest is 0.5. Thus: P(A|B) = 0.1×0.5/0.2 = 0.25 The adoption of Bayes\' theorem has led to the development of Bayesian methods for data analysis. Bayesian methods have been defined as \"the explicit use of external evidence in the design, monitoring, analysis, interpretation and reporting\" of studies (Spiegelhalter, 1999). The Bayesian approach to data analysis allows consideration of all possible sources of evidence in the determination of the posterior probability of an event. It is argued that this approach has more relevance to decision making than classical statistical inference, as it focuses on the transformation from initial knowledge to final opinion rather than on providing the \"correct\" inference. In addition to its practical use in probability analysis, Bayes\' theorem can be used as a normative model to assess how well people use empirical information to update the probability that a hypothesis is true. Oxford Dictionary of Philosophy: Theorem in probability theory. Thomas Bayes (1702-61) was an English clergyman, whose An Essay towards Solving a Problem in the Doctrine of Chances occurs in two memoirs presented by Price (Bayes having died), in Philosophical Transactions of 1763 and 1764. Bayes gave a result for the probability that the chance of an event on a single trial is within a certain interval, given the number of times the event has occurred and the number.

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Baxter & Baxter have total assets of 710,000. There are 45,000 shares of stock outstanding with a market value of 28 a share. The firm has a profit margin of 7.1 percent and a total asset turnover of 1.29. What is hte price-earning ratio? 16.38 17.99 19.38 20.12 22.41 Solution total asset turnover=revenue/average total assets revenue=$915900 Net Income=Profit=0.071*revenue=$65028.9 EPS=Net Income/Total shareholding=$1.445 P/E=Price/EPS=19.38.

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Based on value line and number below i have too determine the time period of the detailed forcast for which good estimates are possible , and of the simplified forcast for the more distant future. NIKE (NKE)corporation 2010-20141) Historical(2010-2014) 2)Near future(2015-2019) and TRansition stage(2020-2024) It has to work on1) ROE- 2b(ploback)3) g(growth rate) Historicla Year 2010 2011 2012 2013 2014 ROE 0.196 0.217 0.214 0.222 0.249 b 0.144 0.160 0.155 0.158 0.175 g 2.82% 3.47% 3.32% 3.50% 4.35% Year 2010 2011 2012 2013 2014 ROE 0.196 0.217 0.214 0.222 0.249 b 0.144 0.160 0.155 0.158 0.175 g 2.82% 3.47% 3.32% 3.50% 4.35% Near Future Year 2015 2016 2017 2018 2019 ROE 0.258 0.255 0.305 0.355 0.310 b 0.220 0.220 0.220 0.220 0.220 g 5.68% 5.61% 6.71% 7.81% 6.82% Transition Stage Year 2020 2021 2022 2023 2024 ROE 0.291 0.272 0.253 0.234 0.215 b 0.216 0.211 0.207 0.202 0.198 g 6.27% 5.74% 5.22% 4.73% 4.25% Year 2010 2011 2012 2013 2014 ROE 0.196 0.217 0.214 0.222 0.249 b 0.144 0.160 0.155 0.158 0.175 g 2.82% 3.47% 3.32% 3.50% 4.35% Solution 1. ROE is the Return On Equity, ie it is the return on the investents made by the business, Given the informaton and the concern that which year would give NKE corporation the best ROE. is the year 2018. Since it has the highest ROE of .355 % 2.Ploughback Period: It is the peroid taken by business to break even, period from which it would start generating profit. Thus based on the data above, 2010 has the best plouback period , best here is the least in numerical terms, that means it would only take .144 yrs to start generating profit. 3.Best growth rate is in the year 2018..

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Based on the point above that is about the difference between cohesive soil and cohesionless soil.Can you write an essay of 300 words about the difference between cohesive soil and cohesionless soil based on the point above and any relevent point to the subject of the essay.Can you write your answer neatly so that I can see and understand it easily. sive soil Fine silt Cla( exhibit platicity -high poros low permeabili Date Cohesionless 8Sil No. Course d O .06 mm) Sand ravel not exhibit pla hcity Low Orosi high bi li Solution Soil can be classified on the basis of their property to hold or not to hold together. The soil in which the particles stick together is called cohesive soil such as clay and the soil where the particles do not adhere to each other are called cohesion less soil such as sand. There are many factors which can differentiate cohesive soil from cohesion less soil. They are: 1.Particle size- While the particle size of cohesive soil range from 0.06 mm to less than 0.002 mm, the particle size of cohesion less soil range from 0.0 6mm to 200mm. Thus, cohesive soil is called fine-grained and cohesion less soil is called coarse-grained. 2.Porosity- Cohesive soils tend to hold moisture and show high porosity. This is because their low sized microscopic particles compact together to create micro pores where water can fill in and stay as clay particles have affinity towards water molecules. On the other hand, cohesion less soil show lower porosity as water cannot retain in larger sized pores and flows away through connected pores. 3.Permeability- Cohesive soils exhibit lower permeability compared to cohesion less soil because their pores are not interconnected unlike the pores of cohesion less soil; and are too small to allow the retained water to flow quickly under gravity. 4.Erodibility- Cohesive soils are less erodible compared to cohesion less soil because of the high cohesive forces acting between the soil particles. 5.Plasticity- Cohesive soils show high plasticity (at a particular moisture content called Plastic Limit), i.e. they retain the shape change without cracking after removal of the force applied. This occurs due to the molecular plate-like structure in cohesive soil which slide over each other in presence of water. Absence of such molecular structure in cohesion less soils make them less plastic. 6.Examples- Cohesive soil- Clay, silt Cohesionless soil- Sand, gravel..

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Based on the income and the statements of cash flows from 2011 through 2015, did Mr. Martin have positive net income an cash flow? Please show all work. Background MartinCo is a small company that has been in the Martin family for several generations. In 2010, Mr. Martin added a new business line selling an exclusive and unique image processing sensor that he had developed. For the last years, the business unit had done quite well, exceeding Mr. Martin’ and the Board of Director’s expectations. Given that MartinCo had never worked in the image processing industry, the project had originally been viewed as extremely risky with several of the board members recommending against it. Even so, the project had prevailed and the business unit had done well. Recently, Mr. Martin had received inquiries from a major Photography and Imaging firm (Canikon, Inc.) to exclusively use his image processing sensor or to purchase the rights to the sensor outright with the intent of getting a larger manufacturer to produce the product. Mr. Martin is faced with a dilemma. Should he choose to keep the rights to his product, he will have to ramp up production to meet the demands of Canikon. Alternatively, should Mr. Martin chooses not to expand his image processing business unit to meet Canikon\'s propositions, Canikon could independently develop a similar sensor and cut him out of the market altogether. Mr. Martin is loath to give up the rights to his designs and brand and realizes that he might have to do so if the numbers don’t fall out well for his product. Mr. Martin wants to compile a report for the business unit that will give him some insight into its present operation and potentially a better understanding of whether an expansion would be a feasible undertaking. A big concern that Mr. Martin has is that Canikon intends to, and would be able to significantly underprice his present product and cost structure. Canikon is currently a leading distributor in the Photography and Imaging industry. Hence, the company has the ability to source a larger manufacturer to produce a similar type of sensor and would able to bring economies of scale to bear that Mr. Martin would have difficulty achieving. ------------------------------------------ Product Development and Initial investments Mr. Martin invested significant time and expense in the development of his unique Image Processing Sensor. He went through extensive development, testing, consumer feedback, promotional giveaways and effort before proposing the product and business line to the board members. All in all he had produced one hundred and fifty units before even having a fully functional production line. Mr. Martin presented his ideas to the board at the 2nd quarter Board of Directors meeting of 2010. Although there was some hesitation, the Board of Directors approved the project and expected the purchase of equipment to be finalized with plans to have the sensors to run off the lines and delivered to the dis.

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