Proposal Argument I Essay Example | Topics and Well Written Essays - 1000 words

Proposal Argument I - Essay Example Meet the Parents† was made on this topic in which a male nurse fell in love with a girl and when they go to visit the parents of that girl everything become a nightmare just because the profession owned by that guy was nursing. The movie represents a true picture of our society because today, millions of people have a perception that nursing is only a field for females and they believe a man cannot fit in a feminine field. I believe this is totally wrong and unfair because the issue of inequality of male nurses is exactly the same to the issues of discrimination in other professions. To understand the reasons for inequality facing men in nursing, it is crucial to have an insight into the past of this profession. In the 3rd century, nursing was founded as an attractive profession in ancient rime and at that time it was dominated by men. In the 20th century, women dominated nursing and had kicked out men from this profession by creating a perception that nursing is a â€Å"feminine† profession. The biggest support with women was the foundation of the American Nurse Association in 1913, which banned the entry of men. Later, somewhere in 1930’s men were welcomed to nursing, but just in papers and documents because they were discriminated by teachers in school and later on by peers, patients and society in their workplace. I have been interviewing many registered male nurses and most of them complained about unequal treatment by teachers in school. Johnson is a registered male nurse and he told me that the course contents, class environment and teaching style were women centered, which compelled me to feel uncomfortable during classes (Johnson). Many authors also participated in making the issue of inequality in the field of nursing for male nurse by referring nurses as women in their books and text books which further discouraged males from choosing nursing as a profession. This is not the limit, as patients usually demand to have female nurses to take care of

Effect of Advertising in Brand Promotion Dissertation

Effect of Advertising in Brand Promotion - Dissertation Example with Established Businesses 34 4.3 Analysis and Discussion 37 5.CONCLUSIONS, IMPLICATIONS & RECOMMENDATIONS 43 5.1 Conclusions 43 5.2 Recommendations and Implications for Businesses 45 5.3Revisiting Aims and Objectives 47 5.4 Research Limitations 48 5.5 Areas of Future Study 48 5.6 Concluding Remarks 49 References 50 Appendix-I 55 1. INTRODUCTION In today’s competitive world, businesses can only survive if they communicate well to their customers. In the time when every other company is bombarding messages to the customers, one must not stay behind in the race of communication. There are several ways to communicate with the customers and where the product itself, the price and the place too communicates with the customers there are some specific communication tools available for companies to reach the target audiences. Promotion mix elaborates different ways via which a company can target its current and potential customers. These specific communication tools include advertisi ng, sales promotion, publicity / public relations and personal selling – the promotion mix. This paper focuses on advertising as a way to reach audiences where the major focus is on brand building and how it may help in promoting a business. The distinction between new and established businesses and the impact of advertising and branding on both a new and an established business is presented. 1.1 Background and Context Businesses focus on advertising and branding more than ever before; this is partly because of the increased competition. It has become important to stay visible in the time when every other business is advertising and promoting itself. Advertising and branding is the most beneficial and extremely vital for businesses. It is true that advertisements affect businesses; several authors and researchers have concluded that advertisement has the power to have an effect on businesses. Though not same, there is a close link between advertisement and brand promotion. Br ands are created over a period of time and advertising plays a crucial role in brand promotion; a common marketing strategy used for creating awareness of products, increase in sales and ensuring customer loyalty is brand promotion. Many businesses instead of promoting individual products focus on promoting the brands as a part of their corporate strategy; this is called corporate branding. Grime (2012, p. 146) defined corporate branding as â€Å"a consistent effort centered on the company as a whole†. The prime motive of brand promotion is to create customer awareness (Trehan & Trehan 2010); once established, the customer tends to purchase that product again and again which leads to customer loyalty. Brand promotion also

Introduction To Cricket In The 21st Century History Essay

Introduction To Cricket In The 21st Century History Essay When considering the extensive amount of research that has been directed toward the sporting world from a mathematical, statistical and operational research perspective, the Duckworth/Lewis method (Duckworth and Lewis, 1998, 2004) perhaps stands alone as the most significant contribution to sport. The common practice in dealing with interrupted one-day cricket matches until 1992 was to compare the run rates (the total number of runs scored divided by the number of completed overs) of the competing teams; the team with the higher run rate was declared the winner. However, this rule tended to benefit the team batting second (Team 2) at the expense of the team batting first (Team 1), leading to the common practice of inviting the other team to bat first if rain was expected. The difficulty with run rates is that targets are determined by taking the remaining overs into account, while ignoring the number of lost wickets. As is well known, batsmen tend to bat less aggressively and score fewer runs when more wickets have been taken. The first team does not have the same strategic options as the second team and, in that sense, the rule does not provide both teams with equal opportunities. Realising that this rule is biased towards the side batting second, the Australian Cricket Board introduced its most productive overs rule during the 1992/93 season. This rule calculates the target for Team 2 by taking the n highest scoring overs of Team 1 where n is the number of played overs (for example, 40 if 10 overs are lost due to rain). Ironically, this rule was now considered as tending to favour the side batting first and transparently unfair to the team batting second. To illustrate, Suppose that Team 2 requires 20 off 19 balls to win, when a short shower takes three overs away. The reset target would now be 20 off 1 ball since the three least productive overs are deduced from the original target (which we may believe were three maiden overs in this case). However, this seems to be unfair and even ironic: the second teams excellent bowling (three maiden overs) in the first innings is now turning against them; it would have been better for Team 2 in this case if Team 1 had reached the same total score without any maidens. The Duckworth/Lewis method was utilised and gained prominence during the 1999 World Cup, and since that time, it has been adopted by every major cricketing board and competition. In one-day cricket, the Duckworth/Lewis method is based on the recognition that at the beginning of a match, each side has resources available (typically 50 overs and 10 wickets). When the match is shortened, the resources of one or both teams are reduced and the two teams usually have different resources for their innings. In this case, in an attempt to be fair, a revised target for the team batting second is set. The determination of the target using resources is known as the Duckworth/Lewis method. What makes the adoption of the Duckworth/Lewis method remarkable is that the method is widely perceived by the public as a black box procedure. Generally, people do not understand how the targets are set but they do agree that the targets are sensible or at least preferable to the approach based on run rates. Although the Duckworth/Lewis (D/L) method was designed for one-day cricket, it has also been applied to Twenty20 cricket. Twenty20 is a relatively new version of limited overs cricket with only 20 overs per side. In contrast to the one-day game and first-class cricket (which can take up to five days to complete), Twenty20 matches have completion times that are comparable to other popular team sports. With the introduction of the biennial World Twenty20 tournament in 2007 and the Indian Premier League in 2008, Twenty20 cricket has gained widespread popularity. Although Twenty20 (t20) cricket is similar to one-day cricket, there exist subtle variations in the rules (e.g. fielding restrictions, limits on bowling, etc) between the two versions of cricket. The variations in the rules, and most importantly, the reduction of overs from 50 to 20 suggest that scoring patterns in t20 may differ from the one-day game. In particular, t20 is seen as a more explosive game where the ability to score 4s and 6s is more highly valued than in one-day cricket. Since the D/L method (and its associated resource table) is based on the scoring patterns in one-day cricket, it is therefore reasonable to ask whether the D-L method is appropriate for t20. With the rise of Twenty20, an investigation of the D/L method applied to t20 is timely. Up until this point in time, such an investigation might not have been possible due to the dearth of t20 match results. Now analysts have at their disposal nearly 200 international matches, and through the use of efficient estimation procedures, the question may be at least partially addressed. Also, since t20 matches have a shorter duration, to date, few matches have been interrupted and resumed according to D/L. Consequently, if there is a problem with D/L applied to t20, it may not have yet manifested itself. This was true before the third editon of the World t20 in May 2010 when a controversial outcome occurred in a game between England and the West Indies. The criticism directed at the usage and appropriateness of the method by players, commentators and fans provide sufficient motivation to adjust the table in this project. In Section 2, the construction of the Duckworth/Lewis resource table is reviewed as well as its effective inception relative to past rain rules. Some comments are provided on aspects of the table and the limitations of the method. In Section 3, an alternative Twenty20 resource table is obtained using a non-parametric approach based on Gibbs sampling. The data used in the construction of the new table consist of all international Twenty20 matches to date involving Test-playing nations as recognised by the International Cricket Council (ICC). The project concludes with a short discussion in Section 4. A heat map is provided to facilitate comparisons between the two tables. 2. For their eyes only: Evaluation of the current method and its appropriateness A condensed version of the Duckworth/Lewis resource table (Standard Edition) is shown in Table 1 (taken from the ICC Playing Handbook 2008-09). In an uninterrupted innings of one-day cricket, a team starts batting with maximum resources available, equivalent to 50 overs and zero wickets taken. Reflect now on a one-day match where Team 1 scores 276 runs at the end of its 50 overs, as a simple example of the use of the Duckworth/Lewis resource table. Before Team 2 has a chance to start their chase of Team 1s total, it rains and they only receive 30 overs for their innings. A look at the resource table shows that Team 2 has only 75.1% of their resources in hand and, consequently, their target for winning the match is set at 276(0.751)=208 runs. Contrast the Duckworth/Lewis target with the unreasonably low target of 276(30/50)=166 runs based on run rates. Table 1. Abbreviated version of the Duckworth-Lewis resource table (Standard Edition) Overs available Wickets lost 0 1 2 3 4 5 6 7 8 50 100.0 93.4 85.1 74.9 62.7 49.0 34.9 22.0 11.9 40 89.3 84.2 77.8 69.6 59.5 47.6 34.6 22.0 11.9 30 75.1 71.8 67.3 61.6 54.1 44.7 33.6 21.8 11.9 25 66.5 63.9 60.5 56.0 50.0 42.2 32.6 21.6 11.9 20 56.6 54.8 52.4 49.1 44.6 38.6 30.8 21.2 11.9 10 32.1 31.6 30.8 29.8 28.3 26.1 22.8 17.9 11.4 5 17.2 17.0 16.8 16.5 16.1 15.4 14.3 12.5 9.4 1 3.6 3.6 3.6 3.6 3.6 3.5 3.5 3.4 3.2 0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 The table entries indicate the percentage of resources remaining in a match with the specified number of wickets lost and overs available. The D/L method has several advantages, which make it undoubtedly preferable to all previously used retargeting rules: completeness (it is able to handle all kinds of interruptions, even multiple interruptions and other unusual situations); the underlying mathematical model is internally consistent; tables are easily accessible/the computer programme is user-friendly; and the method compared to previous rules preserves the chance of winning by providing a relatively realistic reset target. Duckworth and Lewis (1998) only make available incomplete information relating to the creation of the resource table. Nevertheless, they do reveal that the table entries are based on the estimation of the 20 parameters Z0(w) and b(w), w=0, †¦, 9 corresponding to the function where Z(u,w) is the average total score obtained in u overs in an unlimited overs match where w wickets have been taken. While the utility of the Duckworth/Lewis table in one-day cricket cannot be questioned, a number of questions arise based on (1) and the estimates found in Table 1: Is (1) the best curve when considering that there are several parametric curves that could be fit? Is there any benefit in using a non-parametric fit to derive the table entries? The function (1) refers to unlimited overs cricket but is formed from a basis of one-day rules. Since one-day cricket is limited overs cricket, is there an advantage in taking the structure of the one-day game into account? How are the parameters estimated? If the 10 curves corresponding to w=0, †¦, 9 are fit separately, there are little data available beyond u=30 for fitting the curve with w=9. Also, the asymptotes for the curves with w=0,1,2 (see Figure 1 of Duckworth and Lewis (1998)) fall beyond the range of the data. In Table 1, the last two columns have many identical entries going down the columns. Although very few matches occur under these conditions, is it really sensible for resources to remain constant as the available overs decrease? This is a consequence of the asymptote imposed by (1). Although the D/L method maintains the margin of victory, it does not preserve the probability of victory. The resource table employed by the D/L method, and throughout its several updates, is based on detailed information from a large number of first innings scoring patterns. Therefore, the method assumes that the expected proportion of overall scoring for a particular over when a given number of wickets have been lost is the same in both innings. The validity of this assumption (that scoring patterns are the same in both innings) can be questioned. It has been found that there are a greater relative proportion of runs scored in the early and late overs of second innings, than in the first innings. The rule assumes that run-scoring accelerates right from the beginning of the innings so that runs come at a faster rate for every over completed; an exponential relationship between runs and overs is assumed. Although this captures the fact that run-scoring accelerates at the end of an innings, the moment of stabilisation somewhere after the relaxing of fielding restrictions is overlooked. 50 overs has been the standard format for a One-day International (ODI) for so long (over 20 years) that there is a period between the end of the fifteenth over and the start of the 41st where the batting side keep the scorecard ticking over through nudged and nurdled singles whilst the fielding side are perfectly happy to concede. Furthermore, no consideration is given to powerplay overs in which fielding restrictions are in place. Losing two overs during a period of fielding restrictions reduces a teams resources more than when a team loses the same couple of overs somewhere between, say, overs 25 and 30. The D/L method does not reflect the fact that the first period has a much higher run-scoring capacity than the second. The asymmetry between the equations for resetting targets impairs the quality of impartiality and may even lead to strategic options which are not equally open to both teams. When the target is large and Team 2 forsees a substantial reduction of its innings, Team 2 could take the strategic option to keep as many wickets as possible in hand, even if the scoring rate is less than required: a score of 99/1 (or 110/2, 123/3†¦) after 25 overs in the second innings against a target of 286 for 50 overs would win if no further play is possible. This distorted result is not merely due to the scaling of limited early data but also stems from an idealised assumption of how batting sides deploy their resources during an innings. The D/L method, like other (target) prediction algorithms, tries to fit historical data into a function curve, and uses this to predict future match states. Although this approach is generic and scales well, the specificity of the match is lost. For example, say in two instances a match is interrupted in the first innings with the score at 100/3 after 25 overs. The prediction (extrapolation) for both the matches will be the same. However, if one of the teams were 90/0 after 15 overs and the other team were 40/3 at the same stage, it is highly probable that the second team would have gone on to score more than the first. 3. Turn the tables: A new model for Twenty20 matches For ease of discussion, it is convenient to convert the Duckworth/Lewis resource table to the context of Twenty20; the resource table is shortened to 20 overs and the entries scaled so that an innings beginning with 20 overs and zero wickets corresponds to 100% resources. Table 2 gives the full Duckworth/Lewis resource table (Standard Edition) for Twenty20 where the entries are obtained by dividing the corresponding entry in Table 1 by 0.566 (the resources remaining in a 1-day match where 20 overs are available and zero wickets taken). Table 2. The Duckworth/Lewis resource table (Standard Edition) scaled for Twenty20 Overs available Wickets lost 0 1 2 3 4 5 6 7 8 20 100.0 96.8 92.6 86.7 78.8 68.2 54.4 37.5 21.3 19 96.1 93.3 89.2 83.9 76.7 66.6 53.5 37.3 21.0 18 92.2 89.6 85.9 81.1 74.2 65.0 52.7 36.9 21.0 17 88.2 85.7 82.5 77.9 71.7 63.3 51.6 36.6 21.0 16 84.1 81.8 79.0 74.7 69.1 61.3 50.4 36.2 20.8 15 79.9 77.9 75.3 71.6 66.4 59.2 49.1 35.7 20.8 14 75.4 73.7 71.4 68.0 63.4 56.9 47.7 35.2 20.8 13 71.0 69.4 67.3 64.5 60.4 54.4 46.1 34.5 20.7 12 66.4 65.0 63.3 60.6 57.1 51.9 44.3 33.6 20.5 11 61.7 60.4 59.0 56.7 53.7 49.1 42.4 32.7 20.3 10 56.7 55.8 54.4 52.7 50.0 46.1 40.3 31.6 20.1 9 51.8 51.1 49.8 48.4 46.1 42.8 37.8 30.2 19.8 8 46.6 45.9 45.1 43.8 42.0 39.4 35.2 28.6 19.3 7 41.3 40.8 40.1 39.2 37.8 35.5 32.2 26.9 18.6 6 35.9 35.5 35.0 34.3 33.2 31.4 29.0 24.6 17.8 5 30.4 30.0 29.7 29.2 28.4 27.2 25.3 22.1 16.6 4 24.6 24.4 24.2 23.9 23.3 22.4 21.2 18.9 14.8 3 18.7 18.6 18.4 18.2 18.0 17.5 16.8 15.4 12.7 2 12.7 12.5 12.5 12.4 12.4 12.0 11.7 11.0 9.7 1 6.4 6.4 6.4 6.4 6.4 6.2 6.2 6.0 5.7 The table entries indicate the percentage of resources remaining in a match with the specified number of wickets lost and overs available. To build a resource table for Twenty20 (t20), it is imperative to consider the scoring patterns specific to the shortest version of the game. Hence, consider the 141 international t20 matches involving ICC full member teams that have taken place from the first in 17 February 2005 through to 14 January 2011 (details of these matches can be accessed from ESPN Cricinfo). The shortened matches where the Duckworth/Lewis method was present have been excluded along with the t20 matches involving non-test playing nations (ICC Associates); the latter disqualification is in place to ensure matches are of a consistently high standard. Since scoring patterns in the second innings show a level of dependency to the number of runs scored by Team 1, consider first innings data only in the examination of t20 scoring patterns. Note that in their development of a simulator for one-day cricket match results, Swartz et al (2009) consider batting behaviour in the second innings. Match summary results are obtainable from ESPN Cricinfos statistics website but this study calls for ball-by-ball data. For this, Stephen Lynch (statistician) took pains to compose the associated commentary log for each match and store the data in a tabular form for easy access. For each match, define z(u,w(u)) as the runs scored from the point in the first innings where u overs remain and w(u) wickets have been taken until the conclusion of Team 1s innings. Calculate z(u,w(u)) for all values of u that occur in the first innings for each match beginning with u=20 and w(u)=w(20)=0. Next calculate the matrix T=(tuw) where tuw is the estimated percentage of resources remaining when u overs are available and w wickets have been taken. Calculate (100%) tuw by averaging z(u,w(u)) over all matches where w(u)=w and dividing by the average of z(20, 0) over all matches; the denominator is the average score by a side batting first in a t20 match. In the case of u=0, set tuw=t0w=0.0%. Table 3 displays the matrix T, an initial attempt at a resource table for t20. Note that t20,0=100% as desired. Although T is a non-parametric estimate of resources and makes no assumptions concerning the scoring patterns in t20, it is less than ideal. First, there are many table entries where there are missing data for the given situation. In addition, Table 3 does not exhibit the monotonicity expected. Logically, there is a requirement for a resource table that is non-decreasing from left to right along rows and a requirement for a resource table that is non-decreasing down columns. Also o bserve some conspicuous entries in Table 3, particularly the entry of 110.2% resources corresponding to 19 overs available and two wickets taken. This entry is clearly misleading and should be less than 100%. It arises due to the small sample size (three matches) corresponding to the given situation. For this non-parametric resource table (upcoming), the estimation procedure is robust to observations based on small sample sizes as the surrounding observations based on larger sample sizes have greater influence in the determination of the table. Therefore, there is retention of conspicuous observations such as 110.2%. This investigation of Duckworth/Lewis in Twenty20 should be viewed as one of discovery rather than an attempt to replace the Duckworth/Lewis table. Table 3. The matrix R=(r ow) of estimated resources for Twenty20 Overs available Wickets lost 0 1 2 3 4 5 6 7 8 20 100.0 19 93.6 83.0 110.2 18 90.4 85.8 78.3 17 86.7 80.5 82.8 53.7 16 81.7 74.5 81.9 70.7 32.8 15 76.5 71.4 71.5 65.9 59.9 14 68.3 69.1 67.6 66.2 58.4 13 63.8 68.2 62.4 62.9 59.0 24.3 12 62.1 62.3 60.6 57.3 58.8 44.1 11 60.5 56.3 57.0 53.6 61.0 39.7 10 57.6 49.6 52.1 52.8 48.1 38.6 41.0 35.2 9 54.9 52.1 43.6 49.0 44.1 33.8 35.0 29.7 8 51.0 46.4 41.7 42.2 41.2 36.7 27.5 28.7 7 48.6 45.8 38.9 35.9 39.1 34.8 24.1 25.5 6 54.0 37.9 36.6 30.3 36.2 31.3 20.9 21.4 26.7 5 44.0 32.5 25.4 28.7 29.4 23.9 17.1 14.9 4 28.2 23.4 22.5 22.2 20.9 14.3 10.6 3 20.6 19.9 16.9 17.8 15.8 12.4 7.6 2 21.2 17.6 11.9 13.4 10.6 11.0 7.2 1 8.7 5.2 7.3 6.0 5.5 6.0   The table entries indicate the percentage of resources remaining in a match with the specified number of wickets lost and overs available. Note: Missing entries correspond to match situations where data are unavailable. To impose the monotonicity constraints in the rows and columns, refer to the general problem of isotonic regression. For these purposes, consider the minimisation of with respect to the matrix Y=(yuw) where the double summation corresponds to u=1, †¦, 20 and w=0, †¦, 9, the quw are weights and the minimisation is subject to the constraints yuwgreater than or equal toyu,w+1 and yu,wgreater than or equal toyu−1,w. In addition, impose y20,0=100, y0,w=0 for w=0, †¦, 9 and yu,10=0 for u=1, †¦, 20. Although the fitting of Y is completely non-parametric, there are some arbitrary choices that have been made in the minimisation of (2). First, not only was the choice of squared error discrepancy in (2) convenient for computation, minimisation of the function F with squared error discrepancy corresponds to the method of constrained maximum likelihood estimation where the data ruw are independently normally distributed with means yuw and variances 1/quw. Second, a matrix Y: 20 10 based on overs is chosen. Alternatively, a larger matrix Y: 120 10 based on balls could have been considered. The overs formulation is preferred as it involves less missing data and leads to a less computationally intensive optimization. With a matrix Y based on overs, it is possible to interpolate on a ball-by-ball basis if required. Third, a simple choice has been made with respect to the weights quw. 1/quw is set equal to the sample variance used in the calculation of ruw divided by the sample size. The rationale is that when ruw is less variable, there is stronger belief that yuw should be close to ruw. Table 4 gives a non-parametric resource table based on the minimisation of (2). An algorithm for isotonic regression in two variables was first introduced by Dykstra and Robertson (1982). Fortran code was subsequently developed by Bril et al (1984). An R code implementation has been used that is available from the Iso package on the Cran website (www.cran.r-project.org). The programme requires 27 iterations to achieve convergence. What is unsatisfactory about Table 4 is that it suffers from the same criticism that was directed at the Duckworth-Lewis resource table. There is a considerable number of adjacent entries in Table 4 that have the same value. Again, it is not sensible for resources to remain constant as available overs decrease or wickets increase. The problem is that in the minimization of (2), various fitted ys occur on the boundaries imposed by the monotonicity constraints. Table 4 is also unsatisfactory from the point of view that it is incomplete; missing values corresp ond to match situations where data are unavailable. To address the above criticisms, it is necessary take a slightly different approach to estimation. As previously mentioned, it can been seen that (2) arises from the normal likelihood Therefore, consider a Bayesian model where the unknown parameters in (3) are the ys. A flat default prior is assigned to the ys subject to the monotonicity constraints. It follows that the posterior density takes the form (3) and that Gibbs sampling can be carried out via sampling from the full conditional distributions subject to the local constraints on yuw in the given iteration of the algorithm. Sampling from (4) is easily carried out using a normal generator and rejection sampling according to the constraints. Although in statistical terminology, (3) takes a parametric form, the approach is referred to as non-parametric since no functional relationship is imposed on the ys. Table 4. A non-parametric resource table for Twenty20 based on isotonic regression Overs available Wicket lost 0 1 2 3 4 5 6 7 8 20 100.0 19 93.6 85.5 85.5 18 90.4 85.5 80.8 17 86.7 80.8 80.8 64.7 16 81.7 77.4 77.4 64.7 55.9 15 76.5 71.5 71.5 64.7 55.9 14 68.8 68.8 67.6 64.7 55.9 13 66.6 66.6 62.6 62.6 55.9 38.4 12 62.2 62.2 60.6 57.3 55.9 38.4 11 60.5 56.8 56.8 54.8 54.8 38.4 10 57.6 52.1 52.1 52.1 48.1 38.4 34.1 29.3 9 54.9 52.1 46.5 46.5 44.1 36.3 34.1 29.3 8 51.0 46.4 42.0 42.0 41.2 36.3 28.6 28.6 7 48.6 45.8 38.9 37.3 37.3 34.8 25.3 25.3 6 39.7 39.7 36.6 32.8 32.8 31.3 23.0 21.4 21.4 5 39.7 32.5 28.0 28.0 28.0 23.0 17.1 15.5 4 27.9 23.4 22.5 22.2 20.9 14.3 10.7 3 20.7 19.9 17.4 17.4 15.8 12.4 7.7 2 20.7 17.6 12.5 12.5 10.8 10.8 7.2 1 8.7 6.6 6.6 6.0 5.7 5.7 The table entries indicate the percentage of resources remaining in a match with the specified number of wickets lost and overs available. Missing entries correspond to match situations where data are unavailable. In Table 5, the estimated posterior means of the ys obtained through Gibbs sampling are given, and these provide an alternative resource table for t20. The computations pose no difficulties and the estimates stabilize after 50,000 iterations. For cases of missing data, the Duckworth/Lewis table entries are used to impute the missing rs. The imputation is in the spirit of a Bayesian approach where prior information is utilised. Unlike Table 4, Table 5 is a complete table. Also, there are no longer adjacent table entries with identical values and this is due to the sampling approach. Finally, it can be stated that the methodology allows the input of expert opinion. For example, suppose that there is expert consensus that a table entry yij ought to be tied down to a particular value a. To force this table entry, all that is required is to set rij=a and assign a sufficiently small standard deviation Unfortunately we are unable to provide accessible alternative text for this. If you requi re assistance to access this image, please contact [emailprotected] or the author Table 5. A non-parametric resource table for Twenty20 based on Gibbs sampling Overs available Wickets lost 0 1 2 3 4 5 6 7 8 20 100.0 96.9 93.0 87.9 81.3 72.2 59.9 44.8 29.7 19 95.6 90.9 87.7 83.0 76.9 68.3 56.5 42.0 27.2 18 91.7

Maria Mitchell Essay -- Essays Papers

This paper will discuss the life of Maria Mitchell and how she became the first woman astronomer in the United States. It will tell of where she grew up. How she climbed the ranks to achieve her goals and how she came into discovering her true passion of astronomy. By describing the events that made this courageous woman, we can see clearly how she set an example for her gender in the Nineteenth century. Women have always been at the forefronts of science, even though they have not always taken the credit for it. One of the defining marks of humanity is our ability to affect and predict our environment. Science - the creation of structure for our world - technology - the use of structure in our world - and mathematics - the common language of structure - all have been part of our human progress, through every step of our path to the present. Women and men together have researched and solved each emerging need. But in beginning of this paper, we will begin at the beginning and reveal the location of her birthplace to tell of her origins to seek the woman who broke many gender stereotypes. Maria Mitchell, an American astronomer, â€Å"was born August 1, 1818 in Nantucket, Massachusetts, USA.† (McPherson p.12) Her father, a member of the Quaker religion felt strongly that girls should receive education equal to that of boys. When Maria was sixteen she was already a teaching assistant to a schoolmaster. â€Å"It was this strict schoolmaster that gave Maria the advantage over the others,† (Weatherford p.144) in that she could quickly find problems and solve them. He was Cyrus Peirce, the founder of the first normal school in America, nowadays called a teacher's college. When she was seventeen she decided to open a school of her own. She rented a room and put an advertisement in the newspaper. The school closed after a year when Maria was offered a job as a librarian of Nantucket's Atheneum Library. This job was perfect for her, because she was earning a good salary and had time to study and read books. Her father also was â€Å"hired as cashier of the Pacif ic Bank.† (p.54) With his new job came the living quarters attached to the bank. Mr. Mitchell built an observatory on the roof and installed a brand-new four-inch telescope. He used it to do star observations for the United States Coast Guard and Maria helped her father with the measurements. One night in the Au... ...ollege. A crater on the moon was named for her. Posthumously, a tablet with her name was put in the New York University Hall of Fame, her name was carved in a frieze at the Boston Public Library, and she was inducted into the National Women's Hall of Fame. With all of these accomplishments in her career, it is not a wonder that she became the first woman astronomer in the United States of America. By proving herself worthy of what a man could do, she excelled beyond the call of duty and met all of the criteria that a man was supposedly only capable of doing. By having the courage and faith to do what she loved, she set the example for many women in the future to rise through the ranks of men and become just as successful. Bibliography: Gormley, Beatrice, Maria Mitchell: The Soul of an Astronomer, Eerdmans, William B. Publishing Company, December 1995. McPherson, Stephanie, Hetty Mitchell (Illustrator), Rooftop Astronomer: A Story about Maria Mitchell Lerner Publishing Group, The, June 1990. Mitchell Kendall, Phebe, Lee and Shepard, Maria Mitchell: Life, Letters and Journals, 1896. Weatherford, Doris, American Women's History, Prentice Hall General Reference, 1994.

High School Student

Karina Canas English 2323 2/15/12 Supernatural vs. Natural Ever been watching television and out of nowhere a picture frame or some other object fall without anyone moving it? Was it some supernatural power that caused it to fall like a ghost that is haunting a house or was the picture frame just placed wrong? The Castle of Otranto has many mysterious events that happen all throughout the novel, but not all of them are said to be supernatural. Some of the events can actually be explained, but others can’t therefore are said to be supernatural.The very first thing that happens in the novel is the giant helmet â€Å"larger than any casque ever made for human beings† that had fallen randomly out of the sky and crushed Conrad. There is no reasonable explanation to how anyone could have dropped it on Conrad because it was that huge that no one could have lifted it. One of the events that can be explained is when Manfred is trying to chase after Isabella but stops when the â €Å"moon presented to his sight the plumes of the fatal helmet, which rose to the height of the windows, waving backwards and forwards in a tempestuous manner, and accompanied with a hollow and rustling sound†.The reflection of the moon casted a shadow of the helmet and the wind caused the shadow to appear to be waving. The rustling sound was most likely made by the animals or the guards walking. This event appears to be natural though it does give the setting a scary atmosphere. Falling photograph frames are somewhat normal, but Horace Walpole took it a little farther and mentioned the portrait of Manfred’s â€Å"grandfather uttered a deep sigh, and heaved its breast†. Not only did his grandfather in the portrait sighed, but â€Å"it also quit its panel, and descended on the floor with a grave and melancholy air and then motion for Manfred to follow him†.Just like in Harry Potter moving portraits that talk are fictions, but it is a very effective way to raise the climax and give the reader a feeling of mystery and raise the climax. Especially when he finally gets to the door of the chamber and it is â€Å"clapped to with violence by an invisible hand†. The door is not actually held by an invisible hand. It is most likely locked up that’s why Manfred has a hard time opening the door. Later while Manfred is searching for Isabella, his guards Diego and Jaquez manage to get the door open and find what they believe to be a â€Å"giant lying down, for the foot and leg were stretched at length on the floor†.This giant could possibly be the owner of the giant helmet at the beginning of the novel, but there is still no explanation of how the giant got to the chamber without anyone noticing it. Even the guards mention how the giant is supernatural for they suggest for Manfred to â€Å"send for the chaplain, and have the castle exorcised because it appears to be enchanted†. Towards the end of the novel Frederic men tions that while he was in the forest he found a hermit who â€Å"St. Nicholas had appeared to and revealed a secret that he was to disclose to mortal man only on the day of his death-bed†.The apparition of a dead saint is supernatural because the dead don’t come back to life. When Manfred offers Frederic to marry his daughter Matilda â€Å"three drops of blood fell from the nose of Alfonso’s statue meaning that the blood of Alfonso will never mix with that of Manfred†. There has been many cases where it is said that statues bleed or cry, and even though there are proofs there is no logically explanation to this events other than the fact that they are supernatural.As mention there are many mysterious events which cannot be explained, but give a sense of scariness in the novel. The most effective in mystery are the giant helmet which gives intrigues the reader to keep on reading to try and solve the mystery of it and the grandfather coming out of his port rait and leading Manfred to the giant who could possibly the owner of the mysterious helmet. Supernatural and natural events are both great to create mystery that sometimes it is hard to tell them apart.

Political Philosophy and Machiavelli Essay

Nicolo Machiavelli is a well known philosopher of the Italian Renaissance from the sixteenth century. The return of the Medici family in Florence in 1512 forced Machiavelli out of office, and he wrote The Prince after retiring from the public. The Prince is one of his most famous works, it describes the means by which a new leader may gain and maintain power. His ideas can be applied to new rulers ranging from a new principal to a new president of a new country. While discussing his ideas for new rulers, Machiavelli says â€Å"Upon this a question arises: whether it be better to be loved than feared or feared than loved? † (Machiavelli 98). If a ruler is not able to do both, it is better to be loved than feared. Machiavelli answers his own question through his ideas of what makes a successful ruler. He argues that a prince is much safer being feared than loved. Machiavelli says â€Å"†¦ for love is preserved by the link of obligation which, owing to the baseness of men, is broken at every opportunity for their advantage; but fear preserves you by a dread of punishment which never fails. † (Machiavelli 99). He says that being loved creates opportunity for being taken advantage of and being feared doesn’t fail. Bringing fear to his people with cruelty would make them united and loyal. Most people who are fearful of any authority fear punishment, so they are more inclined to not cross the line of disrespect. Without a doubt, being loved is more desired from the people and has a greater value compared to being feared, even though the perks of being feared can make a leader successful. Since it’s better to be loved than feared, there are three important characteristics to have to ensure that the new people you’re ruling love you; these characteristics are being honest, having respect, and being protective. Honesty is an important characteristic to have because the body of people you’re ruling and the way they act is a reflection of yourself. If you make honest and good behavior a key value, your people will do the same. If you don’t make honest and good behavior a key value, your people won’t trust that you are always doing the right thing and telling the truth. Machiavelli says, â€Å"Everyone sees what you appear to be, few experience what you really are. † (Machiavelli 106). His quote shouldn’t be true if you’re an honest and truthful leader. Machiavelli says in his quote that a leader does not show his complete self to everyone, that he displays an act of goodness to his people and only reveals what he really is to those who ask for it. Being an honest leader inside and out will only help gain your people’s trust and true love. This quote also ties into the one that reads â€Å"†¦ it is unnecessary for a prince to have all the good qualities I have enumerated, but it is very necessary to appear to have them. † (Machiavelli 250). Machiavelli says that a leader must put on a false face to his people and pretend to have qualities that he does not actually have. It’s not acceptable to hide yourself from your people because if you say you’re going to protect them no matter what and you back out when something bad happens, your people will be disappointed and won’t have trust in you. A successful leader who wishes to be loved should be honest to his people for who he really is because it will give him respect. You can’t gain respect without giving respect. Respect is one of the most important characteristics to have when being a leader because people always want to be in an environment where they feel valued. A leader isn’t going to be successful if their people aren’t happy and feel as if they aren’t important. If a leader is genuine with respect, his people will be more willing to give back respect and do as he says. Though, the truth is that it is important to give respect whether they feel the leader deserves it or not. As Machiavelli says, â€Å"A prince is also respected when he is either a true friend or a downright enemy. † (Machiavelli 250). It doesn’t matter the relation you have with your leader, whether they’re a true friend or a downright enemy, you’re going to respect them just because they’re your leader. Your people may not like what you do, but you will be respected. It’s obvious that being respected out of actual love is the better than being being respected out of fear, and that good respect should lead to good confidence within the leader. The feeling of being protected is desired from a lot of people. If you’re a new principal, your students and staff want locks on doors and an officer nearby. If you’re the new president of a country, your nation wants to know that they have a reliable and strong army fighting for and protecting the country. A successful leader should always be ready for whatever situations may come. Machiavelli says, â€Å"He who does otherwise, either from timidity or evil advice, is always compelled to keep the knife in his hand. † (Machiavelli 61). A leader should always be ready for quick action if some situation should arise. Your people will love and admire you if they know you’re protecting them and is always cautious for quick problems. It takes great courage and confidence to take full responsibility for your people’s safety and well being. Being honest, having respect, and being protective are characteristics of being a successful but loved leader that have applied to people from before Machiavelli’s time all the way up to present day. It’s easy to spot feared leaders such as Hitler apart from loved leaders like Martin Luther King Jr. Being loved not feared is better to be if you cannot be both because the people you’re leading actually like you for who you are and are willing to do what you say, they aren’t scared into doing it. Martin Luther King Jr. led his people with the same respect they gave him, he was honest and true with his feelings, and he went above and beyond to change the world’s way of how they treated colored people to protect them from getting hurt and discriminated any longer. His people loved and admired him for who he really was, he didn’t hide anything. Martin Luther King Jr. was a successful leader because he was loved and possessed honesty, respect and protectiveness.