The Monkeys Paw :: essays research papers

The Monkey's Paw By (author) W.W.Jacobs   Ã‚  Ã‚  Ã‚  Ã‚  The mystery of the Monkey's Paw is a cleverly thought out short story. This story had three main parts. These parts were the first wish, the second wish, and the third wish.   Ã‚  Ã‚  Ã‚  Ã‚  The first wish was the only tragic wish that was granted. Mr.White, his son Herbert, and an old man were sitting around playing chess. There was a knock at the door and Mr. White answered it to let the man in. His name was Sergeant-Major Morris. He sat down in the seat nearest the fire, and after several glasses of whiskey he began to talk. He talked about some of his war experiences, and then of India.   Ã‚  Ã‚  Ã‚  Ã‚  His last story was about a magical mummified monkey's paw. The sergeant-major tells the family that the old dried out monkey's paw has a spell put on it by an old fakir. The story continues and then Mr.White and the sergeant-major trade. Later Mr. White wishes for 200 pounds. A man comes and visits the Whites telling them that their son Herbert had been killed, and then he gibes them 200 pounds. The consequence of Mr. Whites first wish is the main reason he uses a second and third wish.   Ã‚  Ã‚  Ã‚  Ã‚  Mr. White did not want to use a second wish but his wife insisted that they wish their son back to life. Mr. White wishes his son back to life, but nothing happens so they go to sleep. They are sleeping when they hear a knocking sound at their front door. Mrs. White goes downstairs to answer the door even though Mr. White told her not to answer the door. Mrs. White approached the door while Mr. White looked for the monkey's paw.   Ã‚  Ã‚  Ã‚  Ã‚  At the very moment Mr. White unlocked the door Mr. White found the monkey's paw and made his third and final wish. Just as he made his wish the knocking stopped, and his wife opened the door. What was the last wish? The author never really says, but one can assume that he wished he had never made

The Relationship of Freedom to the Acquisition, Possession, and Exercise of Virtue :: Philosophy Philosophical Essays

ABSTRACT: There are three common objections that any broadly Aristotelian virtue theorist must face, insofar as he or she holds that acts must be performed from a firm and stable disposition in order to express virtue, and that virtue is in some way a praiseworthy fulfillment of human potential. Each of these objections accuses the virtuous person of not fully exercising his or her rationality and freedom, and thus of being somehow less than fully human. There are three common objections that any broadly Aristotelian virtue theorist must face, insofar as he or she holds that acts must be performed from a firm and stable disposition in order to be called acts expressing virtue, and that virtue is in some way a praiseworthy fulfillment of human potential. Each of these objections accuse the virtuous person of not fully exercising his or her rationality and freedom, and thus of being somehow less than fully human. The first objection is that acts flowing from the firm and stable disposition of virtue need not be expressions of rationality and freedom, since they may be performed by rote. The second objection, related to the first, has to do with the voluntariness of the possession of virtue. Those who hold that the virtues must be firm and stable dispositions generally hold that a good upbringing from childhood is of utmost importance in the acquisition of such dispositions. The second objection is thus as follows: if a person’s virtue depends upon her upbringing, then she is not responsible for her virtue; it was not up to her and she deserves no praise. The first objection, then, is that particular acts from a firm disposition of virtue are not fully rational or free; the second objection is that the acquisition of the dispositions themselves is not fully rational or free, since it depends upon upbringing. If neither the possession nor the exercise of virtue need be rational and free, then it seems that the activity of virtue is less than fully human, and thus cannot be the praiseworthy fulfillment of our human potential. The third objection, like the second, also has to do with the importance of one’s upbringing to the virtuous life, but is a bit more pointed. Those who present the third objection argue that the acquisition of virtue, inasmuch as it requires such a directive upbringing, itself constitutes a limitation of one’s freedom.

Coroperate Social Responsibility

Corporate Social responsibility Introduction A few years ago firms only goal was to gain economic profit from their businesses. In recent times it has been discussions if economic profit are the only reason for businesses to exist (Kilotons 1991) In modern society the belief that businesses have responsibilities against the society they operate in have grown bigger, but there are still people and organizations who believe that gaining economic profit from their business are the only thing they have to be concerned about (Chant 2013).The purpose of this essay is to discuss and compare the different viewpoints of corporate social responsibility (hereafter referred to as CARS) and the key issue is to see why corporations and their management should be concerned with CARS. The paper will start by explaining what CARS is and how businesses can gain profit from applying CARS. Thereafter the counterargument, that business doesn't have any other responsibilities then gaining profit, will be presented. An example of good CARS-work will thereafter be demonstrated.The relationship between ethics in business will also be discussed. Different views of CARS There are many different definitions of what corporate social responsibility is but one ay to look at it is that corporate responsibility is used to describe the work that companies do voluntarily that has a positive impact on society, the environment or the economy (Shill, Apothecary ; Kansas 2010). CARS is supposed to help businesses to behave ethically and gain economic profit and at the same time helping to solve social issues (Chant 2013).Not only are CARS good for the society and the people in it but also for the stakeholders of the company. CARS can change stakeholders purchase behavior, employment seeking and also investment. Over mime CARS can also help the company to build a stronger brand and in that way also gain an economic profit (Shill, Apothecary ; Kansas 2010). In recent times a lot of critiques have been pointed to CARS. The counterargument meaner that business only responsibility against the society is to gain economic profit and only do what the business was created to do (Chant 2013).Many opponents against CARS say that businesses only should use their resources and engage in activities that are designed to increase profits so long as it stays within the law (Kilotons, 1991). Why corporate social responsibility? The question is if businesses and corporations have a social nature and responsibility or not? My own answer to this question is that businesses, in the modern society, is of social nature and have responsibilities against the society. Corporations and businesses are a big part of our society and what they do make a big impact on people, environment and also how other business act.I would like to compare it with people walking on the street and don't put their rubbish in the garbage bins. I believe that almost everyone thinks that it would be ethically wrong not to put t heir rubbish in the bins. If everyone throws their rubbish on the street the society and community would not have looked nice and people would care less about, in this case, the environment because no one else does. My point of view is that it reflection of the people in it and so are the corporations and business (Chant 2013).It's understandable that some corporations think it is unnecessary to implement CARS and that it only will cost them money that they won't get back. To demonstrate how businesses can gain economic advantages from CARS I will use a Swedish company ‘KEA. KEA is a big home decoration company that operates all over the world and ton is one of their most important raw materials. The company want all cotton used in their products to come from sustainable productions. By using the better cotton initiative they can help reduce environmental and social impacts.They have also proved that this initiative can help KEA to offer competitive priced products that satisf y customers' needs and also helps the company to reach one of their ambitions to provide responsibly sourced products (CARS: Sweden leads by example in corporate responsibility 2013) With that said, my point is that many companies have to look ore on the output they can gain from CARS and not so much on the input. Conclusion There are many ways of looking at and understand CARS and my point of view in this paper is that CARS is a good thing and that corporations and businesses can gain both social and economic profits from it.On the other hand it can be difficult to measure performance of CARS and to compare business with each other (Chant 2013). But maybe comparing and competitiveness is not necessary as in economical ways. Maybe CARS can be Just a question of good ethics, something as obvious as throwing rubbish in the garbage bin or pay your employees' salary in time. Is that a realistic goal? Probably not, because it takes that CARS belong to some sort of common sense if that's going to happen.The important thing for businesses to understand is that CARS should be a part of their business strategy and goal. The modern world is growing and businesses have to keep up with the changes in the environment around them. People are getting more knowledge about ethics and culture and that's why it's getting more important for businesses and their management to apply it in to their strategy. Maybe people are going to choose one supermarket in front of the other cause the first one didn't care about the ethical issues with food production.

Game Theory and Life Insurance

Astln Bulletin 11 (198o) 1-16 A GAME T H E O R E T I C LOOK AT L I F E I N S U R A N C E UNDERWRITING* JEAN LEMAIRE Universit6 Libre de Bruxelles Tim decision problem o[ acceptance or rejection of life insurance proposals is formulated as a ~vo-person non cooperattve game between the insurer and the set of the proposers Using the mmtmax criterion or the Bayes criterion, ~t ~s shown how the value and the optunal stxateg~es can be computed, and how an optimal s e t of medina! , mformatmns can be selected and utlhzed 1. FORMULATIONOF THE GAME The purpose of this paper, whose m a t h e m a t i c a l level is elementary, is to d e m o n s t r a t e how g a m e t h e o r y can help the insurers to formulate a n d solve some of their underwriting problems. The f r a m e w o r k a d o p t e d here is life insurance acceptance, but the concepts developed could be a p p h e d to a n y other branch. The decision problem of acceptance or rejection of life insurance proposals can be f o r m u l a t e d as a two-person non cooperative g a m e the following w a y : player 1, P~, is the insurer, while player 2, P2, is the set of all the potential pohcy-hotders. The g a m e is p l a y e d m a n y times, m fact each time a m e m b e r of P. – fills m a proposal. Ve suppose t h a t tlfis person is either perfectly h e a l t h y (and should be accepted) or affected b y a disease which should be detected and cause rejection. We shall assume for the m o m e n t t h a t the players possess only two strategies each. acceptance a n d rejection for P~, health or disease for P2. To be more realistic we should introduce a third pure s t r a t e g y for P~: a c c e p t a n c e of the proposer with a surcharge. To keep the analysis as simple as possible we shall delay the introduction of surcharges until sectmn 4. Consequently we can define a 2 x 2 p a y o f f m a t r i x for the insurer. .P~ †¢ P2 healthy proposer A B ill proposer C D acceptance rejection I t iS evident t h a t the worst o u t c o m e for the insurer is to accept a b a d risk. I n t e r p r e t i n g the payoffs as utilities for P1, C should be the lowest figure. Clearly D > B : it is better for the insurer to reject a b a d risk than a good risk. Also A must be greater t h a n B. One anight argue a b o u t the relative * Presented at the 14th ASTIN Colloqumm, Taornuna, October x978. 2 JEAN LEMAIRE values, A and D, of the good outcomes. We shall suppose in the examples and the figures that D > A, but the analysis does not rely on this assumptmn. In order to find the value of the game and the optimal strategy for P~, we can apply – – the minimax criterion, or – – the Bayes criterion. 2. THE MINIMAX CRITERION To apply the minimax criterion assimilates P2 to a malevolent opponent whose unique goal is to deceive the insurer and to reduce his payoff. This is of course an extremely conservative approach, to be used by a pessimistic insurer, concerned only by its security level. 2. 1. Value and Optimal Strategies without information Since P2's objective is to harm P~, the game becomes a 2 x 2 zero-sum twoperson game, which can be represented graphicaUy. The vertical axis of fig. 1 is the payoff to P1. His possible choices are represented by the two straight lines. The horizontal axis is P2's choice: he can always present an healthy proposer, or a non healthy, or pick any probability mix in between. The use of mixed strategies is fully justified here since the game is to be played m any times. Since P2's payoff is the negative of Pl's', his objective is to minimize the insurer's maximum gain, the heavy broken line. The ordinate of point M Payoff Io p~ D A B healthy i'x~n hi'Klllh Fig. i LIFE INSURANCE UNDERWRITING 3 is then the value of the game. The abscissa of M provides the optimal mixed strategy of P2 P~'s optimal strategy can be obtained similarly (for more details see for instance OWLN (1968, p. 29) ) Thus, by adopting a mixed strategy (to accept any risk with a probability D-B PA = A + D – B – c ‘ and t  ° reject w i t h a p r o b a b i l i t y p n = I AD-BC ? ‘A),. P~ can guarantee himself a payoff of v~ = A + D – B – C ‘ D-C PH = A + D – B – C whatever the strategy adopted by his opponent. P2's optmml strategy is to present a proportion of good risks. 2. 2. Introduction of Medical Information The preceding model is extremely naive (and vv1Lt only be used as reference for comparisons) since it does not take into account P,'s possibility to gather some information about the proposer's health, by asking him to fill in an health questmnnaire, or by requiring him to undertake a medical examination. This information is of course only partially reliable. But, however imperfect, it can be used to improve P~'s guaranteed payoff. How can the insurer make optimal use of the information lie does have ? It is sufficient for our purposes to characterize tile medical information by two parameters : Ps, tile probability of successfully noticing a bad risk, and PF, tile false alarm probability of detecting a non-existant illness. Let us introduce a third pure strategy for P , : to follow the indications of tile medical information. If tile proposer is not healthy, his illness is detected with a probabihty Ps, and remains undetected with a probability 1 – – P S . . P i ‘ S expected payoff thus equals E = Dps + C(1-ps). Smailarly, his payoff m case the proposer is healthy is F = (1–pF)A + t~FB. Fig. 2 represents a â€Å"detector† with a . 7 success probability and a . 4 false alarm probability. We notice that, m this case, P1 can guarantee himself a payoff v2 > vl by mixing the strategies â€Å"to accept† and â€Å"to follow the detector's indication†. Of course, for other values of Ps and PF, tile optimal mixed strategy varies and can mix a different set of pnre strategies. The detector can even be so imperfect that the line . FE passes below the intersection of B D and AC; then the medical information is so weak that it is useless. 4 Payoff to Pl JEAN LEMAIRE JD1 J E~ ao % 7o % 4o % 6o % I A. healthy f~n heall hy Fig. 2 2. 3. Optimal Deteclwn System A detector is characterized by a pair (Ps, PFF) of probabilities. The underwriters can decide to render the standards of acceptation more severe, by rejecting more people, thereby incrcasing the success probabihty Ps. Unfortunately, the false alarm probability PF will then increase too. Can gaine theory help us to select an optimal detection system ? Must the company choose a â€Å"nervous† detector, with a high success probability, but also a high false alarm rate, or a â€Å"pldegmatic† or â€Å"slow† system with low probabilities Ps and PF ? Let us assume for sunplicity that all the medical information has been aggregated mto a single discriminating variable (for instance by using discrlminant- or regression analysis). The distribution of the discriminatmg variable for the healthy population will usually overlap the dastribution for the non healthy group. The choice of a particular detector can consist of selecting a critical value, any higher observed value leading to rejection, any lower value to acceptance (this procedure is optimal if the distributions are normal with equal variances Otherwise, tile decision rule can be obtained by a hkelilaood ratio method (see appendix or LEE (1971, pp. 2oi-2o3)). The shaded zone represents the false alarm probability, the dotted region the success probability. Each critical value determines those two probabilities. If the critical value is moved to the right, the detector becomes slower. If it is moved to the left, it become~ more nervous. The set of all the critical values LIFE INSURANCE UNDERWRITING healthy [ non healthy value acceptance t | of the t n g variable dlSCrlmlnat relectlon Fig. 3 Y Ps Fig 4 defines the efficiency curve of the d i s c n m i n a n t variable. The weaker the dlscriminant power of this variable, the nearest to the bissectmg line its efficiency line. A perfect discrimmant variable has a triangular efhciency x y z . The set of all the detectors determines a set of values for the game. The highest value v* for the insurer is reached when the p a y o f f line is horizontal. This can be roughly seen as follows (for a more rigorous proof see LUCE and RAIFFA (1957, pp. 394-396)): the critical value, m o v i n g from left to right, generates a family of hnes with decreasing slope. If . Pat chooses a d e t e c t o r with 6 JEAN LEMAIRE a pos~ttve slope, P= can reduce his payoff below v* b y always presenting h e a l t h y proposers. Similarly, ~f the slope is negative, a continuous flow of non h e a l t h y proposers will keep P~'s payoff below v*. yotl to Pt I D A C h , a i r h~ rmn heulth, Fig 5 The optimal detector can be easdy obtained b y equating the payoffs E and F : Dps + C ( 1 – p s ) = A ( l – p y ) Then (1) + BpF. D-C C-A PF – B – A PS + B – A defines a straight line in fig. 4, whose intersection with the efficiency line determines the o p t i m u m . N o t e t h a t the optimal s t r a t e g y of P~ is a pure s t r a t e g y : to follow the advace of the d e t e c t o r , the insurer does not have to t h r o w a coin after the mecidal examination m order to decide if tile proposer is accepted. W h a t happens is t h a t the â€Å"noise† in the observation system, however small, provides the necessary r a n d o m i z a t i o n in order to p r e v e n t P2 from outguessing the insurer. 2. 4. The Value of Improving the Detectton System A medmal e x a m i n a t i o n can always be improved† one can introduce an electrocardmgram, a blood test . . . . for each proposer. B u t ~s it w o r t h the cost ~ An i m p r o v e d discrimination ability means t h a t tile distributions of fig. 3 are more LIFE INSURANCE UNDERWRITING 7 Fig. 6 Payoff to p, D A im rn i ir~f r m i n B C healthy on hl, olt h Fig. 7 separated and present less overlap. The characterizing probabilities ibs and PF are maproved, and the efficiency line moves away from the bisecting line. The intersection of the improved efficiency line with (1) (which is determined only by the payoffs and therefore does not change with increased discrimina- 8 JEAN LEMAIRE tion) provides the new optimal detector; the ass ociated value is higher for the insurer. If the cost of implementing the new system is less (in utilities) than the difference between the two values, it is worthwhile to introduce it. The insurer should be willing to pay any amount inferior to the difference of the values for the increase in lus discrimination ability. 2. 5. A n Example 1 All the proposers above 55 years of age willing to sign a contract of over 3 million Belgian Francs in a given company have to pass a complete medical examination with electrocardiogram. We have selected 200 male proposers, loo rejected because of the electrocardiogram, and loo accepted. This focuses the attention on one category of rejection causes: the heart diseases, and implicitly supposes that the electrocardiogram is a perfect discriminator. This (not unrealistic) hypothesis being made, we can consider the rejected persons to be non healthy. Correspondingly the accepted proposers will form the healthy group. We have then noted the following characteristics of each proposer: x~: overweight or underweight (number of kilograms minus number of centimeters minus loo) ; x2: number of cigarettes (average daily number); m: the presence of sugar x4: or albumine in the urine; x s : the familial antecedents, for the mother, xs† and the father of the proposer. We then define a variable x0 = l o if the proposer is healthy 1 otherwise nd apply a standard selection technique of discriminant analysis in order to sort out the variables that slgnihcantly affect Xo The procedure only retains three variables xj, x2 and m, and combines them hnearly into a discriminating variable. The value of this variable ~s computed for all the observatmns, and tile observed distributions are presented in fig. 8. As was expected, the discrimination i s quite poor, the distributions strongly overlap. The multiple correlation between Xo and the set of the explaining variables equals . 26. The group centroids are respectively . 4657 and . 343We then estmaate for each possible crltmal value Ps and PF and plot them on fig. lo. t This e x a m p l e p r e s e n t s v e r y w e a k d e t e c t o r s a n d is o n l y i n t r o d u c e d m o r d e r to illus t r a t e t h e p r e c e d m g theory. LIFE INSURANCE UNDERWRITING 9 Fig 8 S Fig 9 We must now assign uNhtlcs to the various outcomes. We shall select A = 8, B = 4, C = o and D = lo. Then the value of the g a m e w i t h o u t medical information is 5. 714, P2 presenting 2/7 of bad usks and P i accepting 3/7 of the proposals. Let us now introduce the medmal reformation nd for instance evaluate the s t r a t e g y t h a t corresponds to a . 5 critical value. On fig. lO, we can read ~s = . 51 a n d PF = 33. Then E = . 5] ? ]o + . 4 9 x o = 5-], a n d F = 3 3 x 4 + . 67 x 8 = 6. 68. The value of this game is 6 121, P2 presenting more bad risks (34. 1%), P I mixing the strategies † r e j e c t † and â€Å"follow d e t e c t o r † with respect- 10 JEAN LE/vIAIRE F i g . 1o Fig. 11 LIFE INSURANCE UNDERWRITING 11 lye probabilities . 208 and . 792 Fig. 11 shows t h a t this s t r a t e g y is too â€Å"slow†, t h a t too m a n y risks are accepted. On the other hand, a detector w~th a . 4 critical value is too nervous: too m a n y risks are rejected T h e value is 5. 975, P2's optimal s t r a t e g y is to present 74. 7% of good risks, while Pa should accept 29. 7% of the tmle and trust the d e t e c t o r otherwise. To find the o p t i m u m , we read the intersection of the efficiency line with equation (1), in this case 5 ~F = 2 – 2 Ps We find PF = . 425 Ps = . 63 with a critical value of . 475. T h e n E = lOX. 63 + ox. 37 = . 425Ãâ€"4 + – 5 7 5 x 8 = 6. 3. f the insurer adopts the ptu'e s t r a t e g y of always accepting the a d w c e of the medical information, he can g u a r a n t e e himself a value of 6. 3 irrespective of his o p p o n e n t ‘ s strategy. L e t us now a t t e m p t to improve the me examination b y a d & n g a new variable xT, the blood pressure of the proposer Because of the high positive correlation between xt and xv, the selection procedure only retains as significant the varia bles x. % xe and x7 Fig. 9 shows t h a t the distributions are more separated. In fact, the group centroids are now . 4172 and . 828 and the multiple correlation between xo and the selected variables rises to . 407. T h e efficiency hne (fig IO) is uniformly to the right of the f o r m e r one. The intersection with (1) is PF = 37 P,s = . 652 with a critical value of approxunatxvely . 45. The value of the game rises to 6. 52, an i m p r o v e m e n t of 22 for the insurer at the cost of controlling the blood pressure of each proposer (see fig. 1~). 3' THE BAYES CRITERION I n s t e a d of playing as if the proposer's sole objective were to o u t s m a r t him, the insurer can a p p l y the B a r e s crlter~on, i. . assume t h a t P2 has a d o p t e d a fixed a priori s t r a t e g y H e can suppose (from past experience o1†³ from the results of a sample s u r v e y p e r f o r m e d with a m a x n n a i me&cal examination) t h a t a p r o p o r t i o n Pn of the proposers is hea lthy. The analysis is easier m this 12 JEAN LEMAIRE case, since P2's m i x e d strategy is now assumed to be known P t only faces a one-dimensional p r o b l e m ‘ he must maximize his utility on the d o t t e d vertical line of fig. 12. Pc/Of f p~ to JD A t B, N C ol eall hy 1 – PH PH non heoll hy Fig 12 One notices from fig. 12 t h a t a medical examination is sometimes useless, especially if PH is near 1. In this case, P t ‘ s optimal s t r a t e g y is to accept all the proposers. In the general case, P t should m a x m n z e the linear function of PF a n d PH [~5FB + (1 – – pF)A]~SH + [paD + (I – ps)c] (1 – PH), under the condition t h a t PF and Ps are linked b y the efficiency curve of fig. 4. As far as the example is concerned, this economic function (represented in fig lo) becomes 1. Ps – 3 4PF if one supposes that p2's mixed s t r a t e g y is to present 15% of bad risks. 6. 8 + F o r the first set of medical informatio n (xl, x2, x6), tile m a x i m u m is reached at the point Ps = . 28, PF = . 09. Since PH is r a t h e r tngh, this is a v e r y slow detector, yielding a fmal u t d l t y of 6. 914. Comparing to the optimal n n x e d strategy, this represents an increase in utility of . 614, due to tlie exploitation of . P2's poor play. Of course, tliis d e t e c t o r is only good as long as P2 sticks to LIFE INSURANCE UNDERWRITING 3 his mixed strategy. It is uneffective against a change in the proposers' behaviour: if for instance PH suddenly drops below . 725, P~'s utlhty decreases under 6. 3, the guaranteed payoff with the mlmmax strategy In this aspect, the Bayes criterion implies a more optimistic attitute of P1. For the second set of medical information (x2, m, xT), the opblnal detector (Ps = . 45, ~bF = o9) grants a utility of 7. t69 if PH = . 85, an improvement of . 649 colnparing to the ininimax strategy (see fig. 11). 4. T O W A R D S MORE R E A L I S M 4. 1. Surcharges Conceptually, the introduction of the possibility of accepting a proposer with a surcharge presents little difficulty: it amounts to introduce one more pure strategy for the insurer. Payoll to ID A G B heollhy non heoil hy F , g . 13 A detector could then be defined by two critical values C1 and C2 enveloping an m c e m t u d e or surcharge zone. The two critical limits would detelmme 4 probabihtles fl~ f12 p8 p4 = = = = probability probabihty probability probability of of of of accepting a bad risk surcharging a bad risk rejecting a good risk surcharging a good risk 14 JEAN LEMAIRE ealthy non healthy V Surchar~le I C1 C2 Fig. 14 and two efficiency curves. A necessary condition for a detector to be optimal is that the corresponding payoff hne is horizontal, i. e. that (2) (1–[email  protected] + 7b,G + p3B = ( 1 – p ~ – p 2 ) D + P2H + P~C. The two efficiency curves and (2) determine 3 relations between the probabilities. One more degree of freedom is thus avai lable to maximize the payoff. 4. 2. Increaszng the Number of Strategies of P2 In order to practically implement the preceding theory one should subdivide P2's strategy â€Å"present a non healthy proposer† according to the arious classes of diseases. P1 should then have as pure strategaes: reject, accept, a set of surcharges, and follow detector's advice, and P2 as m a n y pure strategms as the number of health classes. The graphical interpretation of the game is lost, but linear programming fan be used in order to determine its value and optimal strategies. Appendix: The Likehhood Ratio Method Let — x be the value of tlle discriminant variable, healthy, – – p(H) and p(NH) the a priori probabihties of being healthy or non – – f(x I H) and f(x ] NH) the conditional distributions of x. We can then compute the a posterior1 probability of being non healthy, given the value of the discriminant variable (1) p = p ( N g ix) = f(x l g H ) p ( N H ) f(x l N H ) p ( g g ) + f ( x l H)p(H)† LIFE INSURANCE UNDERWRITING 15 Similarly p ( H I x) = l – p. T h e e x p e c t e d payoffs for the two decisions are EPA = ( 1 – p ) A EPR = (1-p)B Define D* to be D* = EPA — + pC + po. EPn = [(A-B)+(D-C)]p – (A-B). Consequently, D* is a linear function of p, with a positive slope. There exists a critical ~b, ~b,, for which D* = o' (A – B ) Pc = ( A – B ) + ( D – C ) nd the optimal decision rule is to reject if p > Pc ( t h e n D * > o ) a n d t o – – accept if p < Pc (then D * < o ) . — If f ( x [ H) and f(x I N H ) are normal densities with equal variances, there is a one-to-one m o n o t o n i c relationship between p and x, and thus the crttmal p r o b a b l h t y Pc induces a critical value xe. In general, h owever, the cutoff point is not unique. T h e r e m a y be two or more critical values. In t h a t case, we define the likelihood ratio of x for hypothesis N H over hypothesis H as f(x [ N H ) L(x) Of f(x I H) c o u r s e o _-< L(x) =< oo. S u b s t i t u t i n g L(x) in (1) gives 1 P = or 1 L(x) p ( N H ) + p(H) p 1 (2) L(x) – p ( N H ) l – p † F o r constant a priori probabilities, there is a m o n o t o n e relationship between p and L(x); L(x) goes from o to oo as p goes from o to 1. Therefore, a unique critical likelihood ratio Lc(x) exists and can be obtained b y replacing Pc for p in (2) (3) p(H) A – B Lc(x) – p ( N H ) D – C† ] 6 JEAN LEMAIRE p 1. 0 ~-Pc = 0 5 0. 5 I I I NH H I_-~ X? I J_ X? 2 H — Fig. 15 The optimal decision rule reads if L(x) > L c ( x ) , reject; if L ( x ) < L c ( x ) , accept. Notice that, i f A – B = D – C , pc = 1/2 The decision rule is equivalent to maximizing the e x p e c t e d n u m b e r of correct classifications. F r o m (3) p(H) L e(x) #(NH)† If, furthermore, the prior probabii]ties are equal, Lc(x) = 1. REFERENCES AXELROD, 1~ (1978) Copzng wzth deception, International conference on applied game theory, Vmnna LEE, V,r. (1971) Dec~szon theory and human behaviour, J. Wiley, New York LuCE, R and H ]{AIFFA (1957). Games and deczszons, J Wiley, New York. OWEN, G. (1968) Game theory, ~V. Saunders, Philadelphia.

A Day of Happy Moments

Pleasure is something which satisfies our senses but happiness is something deep seated. It is something which is much nearer to our soul. A hot cup of coffee on a chilly day would surely bring pleasure and not happiness. Now I shall say when I was very happy. Even from my early days, I used to take interest in games. My elder brothers used to take me to the sports and matches. Whenever I saw the victors receiving trophies, I eagerly wished that I must be on the victory stand one day. As I came to the secondary school, I took interest in long distance running. With some boys of my class, I used to take to the track and run. In one of the inter-school competitions I came first in the one kilometer race. This gave me not only satisfaction but also encouraged me to put in more and more effort. I was regularly on the track practicing. I learnt the techniques from my physical instructor. From one kilometer I Learnt slowly to run two kilometers within three minutes. The day when I can do it, is still far-off. Still unceasingly I practice long distance running. The Inter-district Sports Meet of the schools came and I was selected for 1000 meter race. It was a red letter day in my life. The event was announced and along with five others, I was standing on the track. Hundreds of people were looking at us. We were set on the mark and the gun went off. I started steadily and knew that I must have spare energy for the last lap. It was a three round business. In the first two rounds, I kept myself the second or third. In the third round, Picked up speed and was running like a colt, left others far behind and breasted the tape in the record time. The excitement was so much that I was almost unconscious for a few minutes. Then I ran to the victory stand. My joy knew no bounds when my name was announced first and I took the salute. It was the glorious day and I enjoyed boundless happiness.

Discrimination in Employment Act Essay

Legislative requirements are defined by law, The health and safety act 1974 ensures a safe working environment. The electricity at work regulations 1989, The COSHH 2002 regulations protects people against any chemical/substances hazardous to health, the MHOR 1999 how to move equipment safely without injury. The data protection act 1998, The equality act 2010 involves race relations and disability, age, Each has their own act , sex discrimination act 1975 and age discrimination act 2006. RIDDOR 1995 for the reporting of injuries,disease and dangerous occurrences. Regulatory requirements include IFL code of practice for teachers to ensure responsibilities towards safe guarding vulnerable adults in learning, public liability insurance , a waiver for clients to sign to say they are happy to be treated by trainees under supervision, risk assessments. Hygiene standards, registered personnel, terms and conditions of employment, codes of professional practice LLLS 2008 IFL, and your duty of care. 1. 2 To value and celebrate everyone, as each learner will each have a different range of abilities, you must treat everyone equally and with dignity and respect, no matter their age, race, culture or disability. Everyone is entitled to education and adapt your teaching methods to include everyone. Have a look at Reisenberger & Dadzie 2002, Equality and diversity in adult and community learning- a guide for managers, Niace, which you can access at http://www. excellencegareway. org. uk/pdf/A1181. pdf Accessed 20th October 2012. 1. 3 Think about what you will be teaching prepare and organize a plan. Make the lesson interesting but informative. To adapt your lesson if something goes wrong, are the learners benefiting from the lesson and how to tell if they are. Assess your methods if you notice they are not picking up on the topic, track progress and look back on paperwork/ evidence try another method. Be positive, knowledgeable in your profession, confident, enthusiastic and encourage, keep up to date with the beauty industry. Good practical experience and keeping up to date records show organisation. 1. 4 Identify the needs of the learner, then look at the type of methods available. Then we can assess if the learner is getting what they need out of that teaching method, deliver current and relevant information, the learner may have a preference of how they would like this to be done. You will need to try all methods and adapt them, use different resources while your lesson is in progress, reflect on your own experiences in order to motivate the learner. As a teacher you may need to mentor, support, plan, design and deliver to the best of your ability, reflect, adapt and communicate effectively, observe and listen, to self assess yourself, justify your decisions, keep records and make referrals as necessary in order to do this I use the table below called the smart guide and I follow this to involve an objective setting. S | Specific, know what need to be achieved | |M |Measurable, ways of measuring completion | |A |Achievable, is an event that is achievable | |R |Realistic, factors such as resources and time | |T |Time scaled, deadlines, stops people postponing tasks. They relate to a | | |guide for objective setting. | 2. 1 A relationship between the learner and the teacher should be of a professional manner, listen to them when they are talking, do not involve yourself or others with any personal issues, confidentiality is important , but we need to know when to refer the learner . No contact by phone or outside the premises, if you know the learner you must inform your line manager. When you are with a student in a one to one situation leave the door open or have someone else in the room with you. 2. 2 You need to know when to refer a learner for internal or external support services, be prepared to be the first point of call and you need to know what services are available for them, then you can refer them to another trained professional and concentrate on supporting them. There are many services available for learners such as the Samaritans helpline, drugs, dyslexia, citizens advice bureau, victim support and NHS direct, as well as assistance with funding. 2. You can clarify your own responsibilities with your line manager, be a team player, register with organisations within your field such as HABIA (Hair and Beauty industry authority), LAPS ( Lead authority partnership scheme). Health and safety in Hairdressing and beauty therapy( online) ( updated 27th Ju ne 2012) ( Accessed on 20th October 2012) available at http://www. hse. gov. uk/hairdessing. 3. 1 The environment that you work in should be safe and clean with adequate lighting and space, good maintenance of equipment with appropriate records to hand. You should provide facilities so the learner can research their material, have access to books or the website, show videos, outings to a salon with a good reputation, ensure the layout of your class room is meeting the requirements of the learner this may change. Do a lesson plan, identify all needs, Assess if your methods have been productive, encourage and support all learners, motivate them to build their portfolio of evidences, give them feedback after practicals, share your experiences , discuss the positives with the negatives. 3. 2 Do not interrupt a learner when they are talking, listen to them and express an option. Encourage them to make their own ground rules to show respect to others, there may be other professionals or clients watching. Think of your colleagues as a client, maintain their dignity, wear full uniform this reflects your professionalism, hair tied back, no nail polish, nails short and clean, wash hands, wear appropriate footwear, set standards for the learner to follow. Mobile phones on silent, equipment to be cleaned and put away safely. Give the learner responsibilities such as a stock check. Conduct yourself in a professional manner at all times this will reflect on the running of the salon and the sales of the bu siness. Bibliography: London underground trainers code of practice.

Froogle Inc. Strategy Essay

Mary, a small business owner in Vermont whose company specializes in the manufacture and sale of ski equipment to Vermont ski resorts, signs a contract with Froogle, Inc. an internet corporation with principal place of business in California, which allows Mary to advertise her business on Froogle’s internet search engine. All of Mary’s business dealings with Froogle are done either by telephone or via internet; she has never been to California. Two months into the business relationship Froogle states that Mary has violated their agreement which prompts Froogle to file a lawsuit against Mary in the California court system. Does the State of California County of Monterey in Salinas have personal jurisdiction over Mary? In order for a state (California) to have personal jurisdiction over a non resident defendant (Mary) the defendant must have established minimum contacts: (1) purposeful direction of activities towards the forum: Boschetto v. Hansing, 539 F.3d 1011 (9th Cir. 2008) – â€Å"minimum contacts†. Without greater interactivity between Mary’s advertisement for her Vermont based business dealings and the residents of California, personal jurisdiction would not be appropriate: Mink v AAAA Development L.L.C., 190 F.3d 333 (5th Cir. 199) In order to establish if a plaintiff’s state forum has personal jurisdiction over a non resident defendant they must prove that the nonresident defendant (whom has never traveled to California and does not target there business advertising at California residents) had sufficient amount of contact with the state. A passive website advertising that is not directed at the residents of California is not enough to establish personal jurisdiction. Therefore, the state of California would not have personal jurisdiction over Mary.