The cruise tourism

The cruise tourism INTRODUCTION Although cruise tourism started in the early 1920s, it became more popular in the last half of the 20th century especially for the middle-aged, affluent demographic mainly in North America. It was a way for them to revel in the sun during winter months while avoiding the crowded tourist spots. The industry has since seen tremendous change in fortunes and is now actually the fastest growing sector within the tourism industry with an annual growth rate averaging 8% since 1980 (Robertsen, 2010). The most popular destinations are as follows with the Caribbean taking the lions share at 50%, the Mediterranean 15%, Alaska 8%, the trans-Panama Canal has 6% of the traffic while west Mexico and northern Europe account for 5% and 4%. The South Pacific sees around 2% of the total cruise tourists. Around 80% of all cruise tourists come from North America although that figure is expected to decline as other markets catch up in the coming years. With estimated global revenue of 27 billion US dollar s and carrying approximately 18 million passengers around the globe, the cruise tourism industry is a major income earner for any economy. CRUISE TOURISM IN CHINA Although China currently sees around 10,000 cruise tourists in its ports in a year, the Chinese government is trying to institute measures to see this number go up to 600,000 passengers by the end of 2010 (Zhao, 2010). Some of the major hurdles that are seen as hampering the Chinese market include strenuous customs procedures, cabotage restrictions (a foreign flag ship is not allowed to call on more than a single Chinese port on one itinerary) and restrictions on Chinese cruise companies (Chinese companies cannot currently curry out cruise operations). Several events have helped to market China in the globe as well as increase the tourist numbers. One of them is the 2008 Beijing Olympics. The world financial crisis has also turned the worlds attention to China due to its improved infrastructure. This has benefited both outbound and inbound business numbers. Chinas growing economy and large middle class population is also seen as a target for large cruise ship companies and many of th em are already beginning to make China a key destination. In 2009 the Costa and Royal Caribbean International Cruises made bold moves by making Shanghai their home ports, increasing the travel options for Chinese cruise tourists. In fact the Cruise Industry News online magazine reports that Hong Kong, Macao and Taiwan all reported double digit growth in the first months of 2010. CRUISE TOURISM IN EUROPE Cruise tourism in Europe in more developed than it is in China mainly because of its established ports and the distribution of income in European economies. G.P Wild report that about 2.5 million European nationals embarked on cruises from European ports (from a total of 2.8 million passengers) in 2005 while 13.1 million passengers visited European ports. They generated about 8.3 billion Euros in revenue, not counting the tremendous effect that the cruise industry has on other industries like ship building, restaurants, hotels and catering, sales and marketing, among others (2007). The cruising industry in Europe has been growing steadily over the years preceding the financial crisis leading to the dropping global share of the cruising traffic held by North America. This is because of the huge potential for cruise tourism in Europe. 3% of the North American population is cruising while it is 1% in Europe. This means that Europe has a greater potential for growth. Also, the new EU cit izens from Eastern Europe are pushing up the demand as their lifestyles continue to change with their changing economic conditions. While cruising was formally the preserve of the middle aged, new products have been introduced that attract children, young adults and even the elderly (Cartwright Baird, 1999). Ultimately, Europe offers the greatest growth potential in the cruise tourism industry. It offers the unique advantage that a large chunk of its population lives relatively near to the sea and so cruise liners see Europe as offering the biggest potential for growth. PERCEPTIONS OF EUROPEAN PASSENGERS In as much as there are many motives for taking a cruise, many traditional European passengers take cruises for reasons that can be summarized as the uniqueness of cruises. The perception of a cruise is that it gives them the opportunity to sample various locations in just one trip. Additionally, there is the common perception that one gets pampered on a cruise, treatment that they would not get anywhere else. Since the vast majority of Europeans have never taken a cruise, it is seen as something new and exciting. There are other opinions on cruising like; one can easily make friends on a cruise, one can shop for a variety of items, it is an opportunity to learn and it is the in thing in tourism right now (Mancini, 2004). Although the opinion of cruise tourism among Europeans is good, there is a problem with its uptake because of some perceptions. Some people view cruising as an activity for the rich. The growth of the industry in China has also been influenced by Chinese consumer behavior. Mr. Qian Yongchan, chairman of China Communications and Transportation Association, summarized the behavior of the Chinese like this: the young and middle aged seek a higher quality of living while large corporations will choose cruise tourism as a means of encouraging their employees or to develop relationships with their clients (2009). The rest of the Chinese population, it seems, is disinterested in this form of tourism. PERCEPTIONS AND BEHAVIOR OF CHINESE TOURISTS CONSUMER PERSEPTIONS Chinas sustained per capita GDP growth which now stands at 3,268 USD has led to the growth of an economically strong, young, middle class who want to enjoy luxury and opulence. Activities that were previously viewed as European are now being demanded. This has seen the growth of the many enterprises including tourism and cruise tourism in particular. Yongchan reports that the number of Chinese cruise tourists reached 93,000 in 2007 (2009). This goes to show that the perception of the Chinese tourist towards cruise tourism is changing. VALUES The modern Chinese tourist has begun to value diversity in their tourist products. Chinese tourists have ventured out of the traditional markets in Taiwan, Europe and North America to go into Africa, the Mediterranean and the Atlantic. Cruise tours offer a good opportunity for them to do so. MOTIVATION The serge in Chinese tourist numbers is being motivated by the new found wealth of the common Chinese people, the growth of the middle class and the opening up of the Chinese market and economy. The Chinese governments increased economic and social obligations in the world are also propelling the Chinese to tour more of the globe. CULTURE EFFECTS The world tourism industry has become more acceptable to the Chinese culture. They now offer products that are not seen as excessive according to Chinese culture. Chinese ingenuity is also having a significant effect on the industry. COMPARISON OF CHINESE AND EUROPEAN CONSUMER BEHAVIOR The modern Chinese tourist does not differ much from the European tourist. Information technology makes certain that both consumers have access to the same information. Popular culture propagated by the media also means that the demands, like and dislikes of both sets of consumers is similar. Nevertheless, the Chinese tourist differs from the European in their experience. Europeans have been at this game for a long time while the market in China is just being opened up. Their expectations also differ in the sense that the Chinese tourist is more conservative than their European counterparts. For example, while casinos may be a big attraction to a European tourist, it may not pull in the crowds in China. POTENTIAL CHINESE MARKET FOR CRUISING The per capita GDP of the main Chinese coastal cities have grown to levels the same as those of medium developed economies. These will provide a strong foundation for passenger liner tourism in the future for Chinas outbound cruise tourism. Its strong economic performance will be another asset (Yongchan, 2009). Chinas diverse and scenic landscape will ensure that tourist numbers keep going up in the future and the plans instituted by the Chinese Transport and Communications Association to improve cruise tourism in the country will also see it rise to one of the top destinations offered by cruise liners (Dervaes, 2003). BENEFITS OF THE DEVELOPMENT OF THE CHINESE MARKET TO THE EUROPEAN MARKET Will the development of the cruise industry in China help Europe sell cruises to Chinese markets? The simple answer is yes. Development of the industry will not only benefit the Chinese market but Europe, North America and the whole cruise industry. Development of Chinese ports and shipbuilding industry will help the global industry by providing alternatives in the sector; the Chinese market will provide a new bracket of tourists while China itself will be a new destination for cruises from around the world. REFERENCES Cartwright, Rodger Carolyn Baird (1999). The Development and Growth of the Cruise Industry. Woburn, MA: Butterworth-Heinemann Dervaes, Claudine (2003). Selling Cruises. New York, USA: Cengage Learning. Dowling, Kingston (2006). Cruise Ship Tourism. Cambridge, MA: CABI Publishing. Golden, Fran W. Jerry Brown (2002). European Cruises Ports of Call. Hungry Minds. Hannafin, Matt Heidi Sarna (2004). Frommers Cruises Ports of Call 2005: From U.S. and Canada Home Ports to the Caribbean, Alaska, Hawaii More. John Wiley Sons. Ludmer, Larry H. (2002). Cruising the Mediterranean: A Guide to the Ports of Call. Montreal, Canada: Hunter Publishing. Mancini, Marc (2004). Cruising: A Guide to the Cruise Line Industry. New York, USA: Cengage Learning. Maxtone-Graham, John (2000). Cruise Savvy: An Invaluable Primer for First Time Passengers. New York, USA: Sheridan House, Inc. Maxtone-Graham, John (2001). Liners to the Sun. New York, USA: Sheridan House, Inc. Stern, Steven B. (1997). Sterns Guide to the Cruise Vacation. 7th ed. Pelican Publishing Co. Robertsen, Graeme (2010). Cruise Ship Tourism Industry. Retrieved 2010-05-05 from http://www.lighthouse-foundation.org/index.php?id=112L=1 China Hospitality News (2009). Marketing MICE Cruises in China. Retrieved 2010-05-05 from http://www.chinahospitalitynews.com/en/2009/01/05/9635-marketing-mice-cruises-in-china/ Yongchang, Qian.(2009). The New Age of China Cruise Industry is Coming. Retrieved 2020-05-05 from http://www.ccyia.com/index.php/industry/viewen/1280 Zhao, Paul (2010).Chinas Cruise Industry is Growing Fast. Retrieved 2010-05-05 from http://prlog.org/10560599 G.P> Wild (International) Limited and Business Research and Economic Advisers (2007). Contribution of Cruise Tourism to the Economies of Europe Cruise Industry News (2010). Upward Trend for International Tourism. Retrieved 2010-05-05 from http://www.cruiseindustrynews.com/cruise-news/3941-42910-upward-trend-for-international-tourism.html

Essay --

T. S. Eliot: Metaphysical Poetry, Prufrock and Hollow Men In the essay â€Å"The Metaphysical Poets,† T. S. Eliot explicates and praises the anti-Romantic and intellectual qualities of metaphysical poetry which Johnson had disapproved. Eliot writes â€Å"the poet must become more and more comprehensive, more allusive, more indirect in order to force, to dislocate if necessary, language into his meaning.† Eliot praised the metaphysical poets’ ability to find the verbal equivalent for states of mind and feeling while using clear, simple, pure language, and unexpected analogies to makes their reader sit up and consider a thought or emotion in a completely nuanced way, such language of metaphysical poetry is evident in Eliot’s poems, The Love Song of J. Alfred Prufrock, and The Hollow Men. Eliot states that the term metaphysical has been used as a term of abuse or as the label of a quaint and pleasant taste. Johnson himself, who employed the term ‘metaphysical poets’ with the poet Donne chiefly in mind, remarks, â€Å"the most heterogeneous ideas are yoked by violence together.† Johnson apprehended the metaphysical style where the â€Å"effects are due to a contrast of ideas, different in degree, but the same in principle.† The force of Johnson’s argument lies in his belief that the metaphysical poets could only correlate dissimilar ideas with violence, and that they could not fuse their analogies into a whole. Eliot remarks that this, however, is not the case and that many of the metaphysical poets have succeeded in combining heterogeneous ideas. Eliot quotes from Bishop King, Herbert and Cowley and other such poets to support his assertion. Thus, Eliot concludes that the fault Johnson references is not valid and the unity of heteroge neous ideas is com... ... as corrosive and cowardly. In the final lines of the poem, the prickly pear rhyme ends in a song about the end of the world. And this is how the world ends in the realm of the hollow men, â€Å"not with a bang, but with a sad and quiet whimper.† Eliot creates a desolate and alienated world where the hollow men dream of a kingdom that could release them from the constant state of nothingness. He focuses on the hollow men’s inability to transcend although it is their only hope. He uses the imagery of disembodied eyes and fading stars to depict the state of the men’s consciousness. Aspects of the form copy the characteristics of the hollow men, as well. The speakers desire to avoid speech and his inability to complete full sentences are shown in the final lines of the poem. Eliot deploys, the hollow men represent all humankind, and their tragic existence concerns everyone. Essay -- T. S. Eliot: Metaphysical Poetry, Prufrock and Hollow Men In the essay â€Å"The Metaphysical Poets,† T. S. Eliot explicates and praises the anti-Romantic and intellectual qualities of metaphysical poetry which Johnson had disapproved. Eliot writes â€Å"the poet must become more and more comprehensive, more allusive, more indirect in order to force, to dislocate if necessary, language into his meaning.† Eliot praised the metaphysical poets’ ability to find the verbal equivalent for states of mind and feeling while using clear, simple, pure language, and unexpected analogies to makes their reader sit up and consider a thought or emotion in a completely nuanced way, such language of metaphysical poetry is evident in Eliot’s poems, The Love Song of J. Alfred Prufrock, and The Hollow Men. Eliot states that the term metaphysical has been used as a term of abuse or as the label of a quaint and pleasant taste. Johnson himself, who employed the term ‘metaphysical poets’ with the poet Donne chiefly in mind, remarks, â€Å"the most heterogeneous ideas are yoked by violence together.† Johnson apprehended the metaphysical style where the â€Å"effects are due to a contrast of ideas, different in degree, but the same in principle.† The force of Johnson’s argument lies in his belief that the metaphysical poets could only correlate dissimilar ideas with violence, and that they could not fuse their analogies into a whole. Eliot remarks that this, however, is not the case and that many of the metaphysical poets have succeeded in combining heterogeneous ideas. Eliot quotes from Bishop King, Herbert and Cowley and other such poets to support his assertion. Thus, Eliot concludes that the fault Johnson references is not valid and the unity of heteroge neous ideas is com... ... as corrosive and cowardly. In the final lines of the poem, the prickly pear rhyme ends in a song about the end of the world. And this is how the world ends in the realm of the hollow men, â€Å"not with a bang, but with a sad and quiet whimper.† Eliot creates a desolate and alienated world where the hollow men dream of a kingdom that could release them from the constant state of nothingness. He focuses on the hollow men’s inability to transcend although it is their only hope. He uses the imagery of disembodied eyes and fading stars to depict the state of the men’s consciousness. Aspects of the form copy the characteristics of the hollow men, as well. The speakers desire to avoid speech and his inability to complete full sentences are shown in the final lines of the poem. Eliot deploys, the hollow men represent all humankind, and their tragic existence concerns everyone.

The Other Nature Essay -- Writing Writer Literature Papers

The Other Nature Early in her exploration of man's soul, Joyce Carol Oates discovers a fundamental truth while writing about the character of Stavrogin in Dostoyevsky's The Possessed-that as part of his inevitable fall, man violates "nature" in so complete a way as to separate himself from the only forces that can save him. This theme dealing with the Fall of man is a constant thread that weaves itself through most of Oates' essays, the corruption by various internal and external forces and the tragedy that results from man's blindness to his own nature and to what would provide him salvation. Oates' power lies in her ability to delve deep within the personalities of the writers, the characters they create, and the powerful themes buried deep in the work's soul. She applies psychological concepts and archetypes in order to explore the implications brought about by the similarities and differences in the characters' thoughts and actions. She reaches her most thought-provoking insights by connecting parallel motifs across a wide spectrum of literature and constantly leaps from one generalization to the next causing the reader to wonder how she has come to the fascinating and brilliant conclusions presented in Contraries. By examining the Fall of man, she discovers how self-awareness and material preoccupations lead to a corruption of the "natural" self. Later, the discussion of tragedy and transcendence in essays about King Lear and Nostromo reveals the fundamental importance of women-as saviors of the natural world and representatives of salvation for men. Women are the und erlying focus of her essays; the archetypes and roles they adhere to and defy as literary characters shape the way she perceives the female. Ultimat... ... subjection is presented as grisly and mean. Perhaps this shift of focus from the sublime to the obscene is necessary to bring more clearly into focus the longstanding female archetype and provide us with the strength to intervene in such deep-running cultural patterns. Oates certainly does not preach at us, and she never tells us exactly what to do. But reading Connie's story, and reading over Oates's shoulder as she sees the archetype that created it, we are pushed, at least, to read the stories we encounter to find and reflect on the conflicts of human nature they reveal. Works Cited Oates, Joyce Carol. Contraries: Essays. New York: Oxford UP, 1981. "Where Are You Going, Where Have You Been?" 1966. Celestial Timepiece: Joyce Carol Oates Archive. Ed. Randy Souther. Dec. 1996. San Francisco. 10 Dec. 2000. <http://storm.usfca.edu/ ~southerr/wgoing.html>

Teaching Helen Keller Essay example -- Learning Education

The Truth About Helen Keller In Learning Dynamics, the authors, Marjorie Ford and Jon Ford, choose to include an excerpt from The Story of My Life by Helen Keller to show learning from experience. The excerpt titled "The Most Important Day of My Life" mainly draws from Helen Keller's early childhood as she begins her education on the third of March in 1887, three months before she became seven years old. Keller recounts her early experiences of being awakened to a world of words and concepts through the brilliant teaching methods of her teacher, Anne Sullivan. Sullivan taught Keller new vocabulary by spelling words into the young girl's hand. At first, she does not understand the meaning of each word, but eventually learn to connect a word with the physical object it represents. Sullivan often left Keller to spend much time in nature as a way to develop her senses. In time, Keller not only discovers the physical world, but also a world of intangible concepts, ideas, images and emotions. Furthermore, she contribu tes much of her learning to Anne Sullivan, which she wrote, "I fell that her being is inseparable from my own, and that the footsteps of my life are in hers. All the best of me belongs to her." Realizing that words could be put together to evoke a mental image, Helen Keller is able to paint many visual images in the readers' minds through her unique and eloquent usage of poetic language. Her writing style captures both her emotion and experiences. She writes, "Have you ever been at sea in a dense fog, when it seemed as if a tangible white darkness shut you in and the great ship, tense and anxious, groped her way toward the shore with plummet and sounding-line and you waited with beating heart for something to happen?" He... ...ucation does not stop at the word "W-A-T-E-R", but she went on to universities and learned many other languages as well. Keller makes a strong argument that her succeed is a result of her teacher, Anne Sullivan, "My teacher is so near to me that I scarcely think of myself apart from her." Even the Fords stated, "Anne Sullivan showed her (Keller) that love and learning are intimately connected." Keller is an extraordinary person not because she overcomes blindness or deafness rather she should be great for her contribution to achieve social changes. Helen Keller should be appreciated for her honesty in realizing that she was privilege to an education, and uses her knowledge and wisdom to help those less fortunate. Works Cited Ford, Marjorie, and Jon Ford. Learning Dynamics (Streamlines : Selected Readings on Single Topics). Belmont: Wadsworth Publishing, 1997.

Data mining

This is an accounting calculation, followed by the application of a threshold. However, predicting the profitability of a new customer would be data mining. Dividing the customers off company according to their profitability. Yes, this is a data mining task because it requires data analysis to determine who the costumers are that brings more business to the company. Computing the total sales of the company. No, this is not a data mining task because there Is not analysis involve, this information can be pull out of any booking program. Sorting a student database based on student ID numbers.No, this Is not a data milling activity because sorting by ID numbers doesn't Involved any data mining task. This is a simple database query Predicting the future stock price of a company using historical records. Yes. We would attempt to create a model that can predict the continuous value of the stock price. This is an example of the area of data mining known as predictive modeling. We could use regression for this modeling, although researchers in many fields have developed a wide variety of techniques for predicting time series. Monitoring the heart rate of a patient for abnormalities. Yes.We would build a model of the normal behavior of heart rate and raise an alarm when an unusual heart behavior occurred. This would involve the area of data mining known as anomaly detection. This could also be considered as a classification problem If we had examples of both normal and abnormal heart behavior. For each of the following, identify the relevant data mining task(s): The Boston Celtic would like to approximate how many points their next opponent will score against them. A military intelligence officer is interested in learning about the captives proportions of Sunnis and Shies in a particular strategic region. A NORA defense computer must decide immediately whether a blip on the radar is a flick of geese or an incoming nuclear missile. A political strategist is seeking the b est groups to canvass for donations in particular county. A homeland security official would like to determine whether a certain sequence of financial and residence moves implies a tendency to terrorist acts. A Wall Street analyst has been asked to find out the expected change in stock price for a set of companies with similar price/earnings ratios.Question 3 For each of the following meetings, explain which phase in the CRISP-DIM process is represented: Managers want to know by next week whether deployment will take place. Therefore, analysts meet to discuss how useful and accurate their model is. This is the Evaluation phase in the CRISP-DIM process. In the evaluation phase the data mining analysts determine if the model and technique used meets business objectives established in the first phase. The data mining project manager meets with data warehousing manager to discuss how the data will be collected. This is theData Understanding phase in the CRISP-DIM process. The data wareh ouse is identified as a resource during the Business Understanding phase; however the actual data collection takes place during the Data Understanding Phase. In this phase data is collected and accessed from the resources listed and identified in the Business Understanding phase. The data mining consultant meets with the vice president for marketing, who says that he would like to move forward with customer relationship management. The main objective of business is to review during the Business Understanding Phase.So, therefore after the meeting it seems the data mining consultant gained success in convincing UP of marketing to provide approval for performing data mining on the customer relationship management system. The data mining project manager meets with the production line supervisor to discuss implementation of changes and improvements. The discussion of implementation of changes and improvements in the project whether specific improvements or process changes are required to ensure that all important aspects of the business are accounted is performed under the Evaluation Phase.The meeting held with business objective to collect and cleanse the data to ensure the quality of data. The analysts meet to discuss whether the neural network or decision tree model should be applied Question 4 [10 points] Describe the possible negative effects of proceeding directly to mine data that has not been preprocessed. Before data mining algorithms can be used, a target data set must be assembled. As data mining can only uncover patterns actually present in the data, the target data set must be large enough to contain these patterns while imagining concise enough to be mined within an acceptable time limit.A common source for data is a data mart or data warehouse. Pre-processing is essential to analyze the multivariate data sets before data mining. The target set is then cleaned. Data. Question 5 [1 5 points] Which of the three methods for handling missing values do you prefer? Which method is the most conservative and probably the safest, meaning that it fabricates the least amount of data? What are some drawbacks to this method? Methods for replacing missing field values with: User defined constants Means or modesRandom draws from the distribution of the variable Question 6 Describe the differences between the training set, test set, and validation set. The training set is used to build the model. This contains a set of data that has fricasseed target and predictor variables. Typically a hold-out dataset or test set is used to evaluate how well the model does with data outside the training set. The test set contains the fricasseed results data but they are not used when the test set data is run through the model until the end, when the fricasseed data are compared against the model results.The model is adjusted to minimize error on the test set. Another hold-out dataset or validation set is used to evaluate the adjusted model in step #2 where, a gain, the validation set data is run against the adjusted model and results compared to the unused fricasseed data. The training set (seen data) to build the model (determine its parameters) and the test set (unseen data) to measure its performance (holding the parameters constant). Sometimes, we also need a validation set to tune the model (e. G. , for pruning a decision tree). The validation set can't be used for testing (as it's not unseen). Data mining This is an accounting calculation, followed by the application of a threshold. However, predicting the profitability of a new customer would be data mining. Dividing the customers off company according to their profitability. Yes, this is a data mining task because it requires data analysis to determine who the costumers are that brings more business to the company. Computing the total sales of the company. No, this is not a data mining task because there Is not analysis involve, this information can be pull out of any booking program. Sorting a student database based on student ID numbers.No, this Is not a data milling activity because sorting by ID numbers doesn't Involved any data mining task. This is a simple database query Predicting the future stock price of a company using historical records. Yes. We would attempt to create a model that can predict the continuous value of the stock price. This is an example of the area of data mining known as predictive modeling. We could use regression for this modeling, although researchers in many fields have developed a wide variety of techniques for predicting time series. Monitoring the heart rate of a patient for abnormalities. Yes.We would build a model of the normal behavior of heart rate and raise an alarm when an unusual heart behavior occurred. This would involve the area of data mining known as anomaly detection. This could also be considered as a classification problem If we had examples of both normal and abnormal heart behavior. For each of the following, identify the relevant data mining task(s): The Boston Celtic would like to approximate how many points their next opponent will score against them. A military intelligence officer is interested in learning about the captives proportions of Sunnis and Shies in a particular strategic region. A NORA defense computer must decide immediately whether a blip on the radar is a flick of geese or an incoming nuclear missile. A political strategist is seeking the b est groups to canvass for donations in particular county. A homeland security official would like to determine whether a certain sequence of financial and residence moves implies a tendency to terrorist acts. A Wall Street analyst has been asked to find out the expected change in stock price for a set of companies with similar price/earnings ratios.Question 3 For each of the following meetings, explain which phase in the CRISP-DIM process is represented: Managers want to know by next week whether deployment will take place. Therefore, analysts meet to discuss how useful and accurate their model is. This is the Evaluation phase in the CRISP-DIM process. In the evaluation phase the data mining analysts determine if the model and technique used meets business objectives established in the first phase. The data mining project manager meets with data warehousing manager to discuss how the data will be collected. This is theData Understanding phase in the CRISP-DIM process. The data wareh ouse is identified as a resource during the Business Understanding phase; however the actual data collection takes place during the Data Understanding Phase. In this phase data is collected and accessed from the resources listed and identified in the Business Understanding phase. The data mining consultant meets with the vice president for marketing, who says that he would like to move forward with customer relationship management. The main objective of business is to review during the Business Understanding Phase.So, therefore after the meeting it seems the data mining consultant gained success in convincing UP of marketing to provide approval for performing data mining on the customer relationship management system. The data mining project manager meets with the production line supervisor to discuss implementation of changes and improvements. The discussion of implementation of changes and improvements in the project whether specific improvements or process changes are required to ensure that all important aspects of the business are accounted is performed under the Evaluation Phase.The meeting held with business objective to collect and cleanse the data to ensure the quality of data. The analysts meet to discuss whether the neural network or decision tree model should be applied Question 4 [10 points] Describe the possible negative effects of proceeding directly to mine data that has not been preprocessed. Before data mining algorithms can be used, a target data set must be assembled. As data mining can only uncover patterns actually present in the data, the target data set must be large enough to contain these patterns while imagining concise enough to be mined within an acceptable time limit.A common source for data is a data mart or data warehouse. Pre-processing is essential to analyze the multivariate data sets before data mining. The target set is then cleaned. Data. Question 5 [1 5 points] Which of the three methods for handling missing values do you prefer? Which method is the most conservative and probably the safest, meaning that it fabricates the least amount of data? What are some drawbacks to this method? Methods for replacing missing field values with: User defined constants Means or modesRandom draws from the distribution of the variable Question 6 Describe the differences between the training set, test set, and validation set. The training set is used to build the model. This contains a set of data that has fricasseed target and predictor variables. Typically a hold-out dataset or test set is used to evaluate how well the model does with data outside the training set. The test set contains the fricasseed results data but they are not used when the test set data is run through the model until the end, when the fricasseed data are compared against the model results.The model is adjusted to minimize error on the test set. Another hold-out dataset or validation set is used to evaluate the adjusted model in step #2 where, a gain, the validation set data is run against the adjusted model and results compared to the unused fricasseed data. The training set (seen data) to build the model (determine its parameters) and the test set (unseen data) to measure its performance (holding the parameters constant). Sometimes, we also need a validation set to tune the model (e. G. , for pruning a decision tree). The validation set can't be used for testing (as it's not unseen). Data Mining Determine the benefits of data mining to the businesses when employing 1. Predictive analytics to understand the behavior of customers Predictive analytics is business intelligence technology that produces a predictive score for each customer or other organizational element. Assigning these predictive scores is the job of a predictive model, which has, in turn been trained over your data, learning from the experience of your organization. Predictive analytics optimizes marketing campaigns and website behavior to increase customer responses, conversions and clicks, and to decrease churn. Each customer's predictive score informs actions to be taken with that customer. 1. Associations discovery in products sold to customers The way in which companies interact with their customers has changed dramatically over the past few years. A customer's continuing business is no longer guaranteed. As a result, companies have found that they need to understand their customers better, and to quickly respond to their wants and needs. In addition, the time frame in which these responses need to be made has been shrinking. It is no longer possible to wait until the signs of customer dissatisfaction are obvious before action must be taken. To succeed, companies must be proactive and anticipate what a customer desires. For an example in the old days, the storekeepers would simply keep track of all of their customers in their heads, and would know what to do when a customer walked into the store. Today’ store associates face a much more complex situation, more customers, more products, more competitors, and less time to react means that understanding your customers is now much harder to do. A number of forces are working together to increase the complexity of customer relationships, such as compressed marketing cycles, increased marketing costs, and a stream of new product offers. There are many kinds of models, such as linear formulas and business rules. And, for each kind of model, there are all the weights or rules or other mechanics that determine precisely how the predictors are combined. In fact, there are so many choices, it is literally impossible for a person to try them all and find the best one. Predictive analytics is data mining technology that uses the company’s customer data to automatically build a predictive model specialized for the business. This process learns from the organization's collective experience by leveraging the existing logs of customer purchases, behavior and demographics. The wisdom gained is encoded as the predictive model itself. Predictive modeling software has computer science at its core, undertaking a mixture of number crunching, trial, and error. 2. Web mining to discover business intelligence from Web customers The fast business growth has made both business community and customers face a new situation. Due to intense competition on the one hand and the customer's option to prefer from a number of alternatives, the business community has realized the essential of intelligent marketing strategies and relationship management. Web servers record and accumulate data about user relations whenever requirements for resources are received. Analy zing the Web access logs can help understand the user behavior and the web structure. From the business and applications point of view, knowledge obtained from the web usage patterns could be directly applied to efficiently manage activities correlated to e-business, e-services and e-education. Accurate web usage information could help to attract new customers, retain current customers, improve cross marketing/sales, effectiveness of promotional campaigns, tracking leaving customers etc. The usage information can be exploited to improve the performance of Web servers by developing proper perfecting and caching strategies so as to decrease the server response time. User profiles could be built by combining users? navigation paths with other data features, such as page viewing time, hyperlink structure, and page content†, according to Sonal Tiwari. 3. Clustering to find related customer information Clustering is a typical unsupervised learning technique for grouping similar data points. A clustering algorithm assigns a large number of data points to a smaller number of groups such that data points in the same group share the same properties while, in different groups, they are dissimilar. Clustering has many applications, including part family formation for group technology, image segmentation, information retrieval, web pages grouping, market segmentation, and scientific and engineering analysis. Many clustering methods have been proposed and they can be broadly classified into four categories such as partitioning methods, hierarchical methods, density-based methods and grid-based methods. Customer clustering is the most important data mining methodologies used in marketing and customer relationship management (CRM). Customer clustering would use customer-purchase transaction data to track buying behavior and create strategic business initiatives. Companies want to keep high-profit, high-value, and low-risk customers. This cluster typically represents the 10 to 20 percent of customers who create 50 to 80 percent of a company's profits. A company would not want to lose these customers, and the strategic initiative for the segment is obviously retention. A low-profit, high-value, and low-risk customer segment is also an attractive one, and the obvious goal here would be to increase profitability for this segment. Cross-selling (selling new products) and up-selling (selling more of what customers currently buy) to this segment are the marketing initiatives of choice. Assess the reliability of the data mining algorithms. Decide if they can be trusted and predict the errors they are likely to produce. Most methods for validating a data-mining model do not answer business questions directly, but provide the metrics that can be used to guide a business or development decision. There is no comprehensive rule that can tell you when a model is good enough, or when you have enough data. Accuracy is a measure of how well the model correlates an outcome with the attributes in the data that has been provided. There are various measures of accuracy, but all measures of accuracy are dependent on the data that is used. In reality, values might be missing or approximate, or the data might have been changed by multiple processes. Particularly in the phase of exploration and development, you might decide to accept a certain amount of error in the data, especially if the data is fairly uniform in its characteristics. For example, a model that predicts sales for a particular store based on past sales can be strongly correlated and very accurate, even if that store consistently used the wrong accounting method. Therefore, measurements of accuracy must be balanced by assessments of reliability. Reliability assesses the way that a data-mining model performs on different data sets. A data-mining model is reliable if it generates the same type of predictions or finds the same general kinds of patterns egardless of the test data that is supplied. For example, the model that you would use to generate for the store that used the wrong accounting method would not generalize well to other stores, and therefore would not be reliable. Analyze privacy concerns raised by the collection of personal data for mining purposes. 1. Choose and describe three (3) concerns raised by consumers. Recent surveys on privacy show a great concern about the use of personal data for purposes other than the one for which data has been collected. The handling of misinformation can cause serious and long-term damage, so individuals should be able challenge the correctness of data about themselves, such as personal records. The last concern is granulated access to personal information, such as personal information about someone’s health when applying for a job. 2. Decide if each of these concerns is valid and explain your decision for each. These concerns are valid, the first concerned mentioned caused an extreme case to occurred in 1989, collecting over $16 million USD by selling the driver-license data from 19. million Californian residents, the Department of Motor Vehicles in California revised its data selling policy after Robert Brado used their services to obtain the address of actress Rebecca Schaeffer and later killed her in her apartment. While it is very unlikely that KDDM tools will reveal directly precise confidential data, the exploratory Knowledge Discovery and Data Mining (KDDM), tools may correlate or dis close confidential, sensitive facts about individuals resulting in a significant reduction of possibilities. The second concern is valid due to incident happening in Washington; Cablevision fired an employee James Russell Wiggings, on the basis of information obtained from Equifax, Atlanta, about Wiggings' conviction for cocaine possession; the information was actually about James Ray Wiggings, and the case ended up in court. This illustrates a serious issue in defining property of the data containing personal records. The third issue is For example, employers are obliged to perform a background check when hiring a worker but it is widely accepted that information about diet and exercise habits should not affect hiring decisions. . Describe how each concern is being allayed. KDDM revitalizes some issues and possess new threats to privacy. Some of these can be directly attributed to the fact that this powerful technique may enable the correlation of separate data sets in other to significantly reduce the possible values of private information. Other can be more attributed to the interpretati on, application and actions taken from the inferences obtain with the tools. While this raises concerns, there is a body of knowledge in the field of statistical databases that could potentially be extended and adapted to develop new techniques to balance the rights to privacy and the needs for knowledge and analysis of large volumes of information. Some of these new privacy protection methods are emerging as the application of KDD tools moves to more controversial datasets. Provide at least three (3) examples where businesses have used predictive analysis to gain a competitive advantage and evaluate the effectiveness of each business’s strategy. The first advantage analysis helps when it comes to validity of a product by making a distinction between the positioning of a product and its ability to satisfy customer requirements. Another important attributes include ease of use, innovation, how well the product integrates with other technologies that customers need. The second advantage is the technology provides to customers. Even if a product is well designed, it must be able to help businesses achieve their business goals. Goals range from gaining insight about customers in order to be more competitive, to using the technology to increase revenue. A key attribute that is measured in this dimension is how well the product supports companies in meeting their objectives. The third advantage is the strength of the company’s strategy. It is not enough to simply have a good vision; a company must also have a well-designed road map that can support this vision. Vision attributes also include more tactical aspects of the company’s strategy such as a technology platform that can scale, well-articulated messaging, and positioning. A key component of this dimension is clarity: it must be clear what business problem the company is solving for which customer.ReferencesAlexander, D. (2012). Data Mining. Retrieved from: http://www.laits.utexas.edu/~anorman/BUS.FOR/course.mat/Alex/#8Josh, K. (2012). Analysis of Data Mining Algorithms. Retrieved from: http://www-users.cs.umn.edu/~desikan/research/dataminingoverview.html Exforsys. (2006). Execution for System: Connection between Data Mining and Customer Interaction. Retrieved from: http://www.exforsys.com/tutorials/data-mining/the-connection-between-data-mining-and-customer-interaction.html Frand, J. (1996). Data Mining: What is Data Mining? Retrieved from: http://www.anderson.ucla.edu/faculty/jason.frand/teacher/technologies/palace/index.htm Pupo, E. (2010). HIMSS News: Privacy and Security Concerns in Data Mining. Retrieved from: http://www.himss.org/ASP/ContentRedirector.asp?type=HIMSSNewsItem&ContentId=73526 Stein, J. (2011). Data Mining: How Companies Now Know Everything About You. Retrieved from: http://www.time.com/time/magazine/article/0,9171,2058205,00.html#ixzz25MwYNhuh

Components of Science Planning Essay

There are five essential components of scientific inquiry teaching that introduce students to many important aspects of science while helping them to develop a clearer and deeper knowledge of some particular science concept and/or process. Research has demonstrated that student involvement in the inquiry process provides a much needed connection and ownership of scientific investigations that will lead to a deeper conceptual knowledge about the content. Inquiry can be labeled as â€Å"partial† or â€Å"full† and refers to the proportion of a sequence of learning experiences that is inquiry-based. For example, when a textbook doesn’t engage students with a question, but begins with an experiment, an essential element of inquiry is missing and the inquiry is said to be partial. Also, inquiry is partial if a teacher chooses to demonstrate how something works rather than have the students explore it on their own and develop questions and explanations. What is important is that at least some of the components of inquiry are present within classroom hands-on experiences and hands-on does not necessarily guarantee inquiry. If all five elements of classroom inquiry are present, the inquiry is said to be full, however each component may vary depending on amount of structure a teacher builds into an activity or the extent to which students initiate and design an investigation. How does a teacher decide how much guidance to provide in an inquiry-based activity? The key element is in the intended outcomes. Whether the teacher wants the students to learn a particular concept, acquire certain inquiry abilities, or develop understandings about scientific inquiry influences the nature of the inquiry. In some instances partial inquiry may be more appropriate than a full inquiry-based experience. Teachers need to make meaningful decisions about how to best deliver the curriculum. The Five Essential Components to Inquiry 1. Learners are engaged by scientifically oriented questions. Scientists may pose two types of questions. They may propose â€Å"why† questions such as â€Å"Why do objects fall toward the Earth?† or â€Å"Why do humans have chambered hearts?† Many of these types of questions can’t be addressed by science. Then there are the â€Å"how† questions such as â€Å"How does sunlight help plant grow?† or â€Å"How are crystals formed?† which can. Students may ask â€Å"why† questions that can be turned into â€Å"how† questions and thus lend themselves to scientific inquiry. The initial question can originate from the learner or the teacher. Purposeful questions can be answered by students’ observations and scientific knowledge they obtain from reliable sources. Skillful teachers help students focus their questions so that they can experience both interesting and productive investigations. Teachers can provide opportunities that invite student questions by demonstrating a phenomenon or having them engage in an open investigation. Sometimes, questions will develop from students’ observations. Other times, the teacher provides the question. Either way, questions must be able to be investigated in a classroom setting. Teachers will likely have to modify student questions into ones that can be answered by students with the resources available, while being mindful of the curriculum. 2. Learners give priority to evidence, allowing them to develop and evaluate explanations that address scientifically-oriented questions. Science uses empirical evidence as the basis for explanations about how the natural world works. Importance is placed on getting accurate data and from observations. To make observations, scientists take measurements in natural settings, or in laboratories. The accuracy of the evidence collected is verified by checking measurements, repeating the observations, or gathering different kinds of data related to the same phenomenon. Evidence collected is then subject to questioning and further investigations. Within the classroom setting, students should follow similar guidelines during their laboratory experiences. 3. Learners formulate explanations form evidence to address scientifically oriented questions. Scientific explanations should be based on reason. They provide causes for effects and establish relationships based on evidence and logical argument and must be consistent with the observations and evidence collected. Explanations are ways to learn what is unfamiliar by relating what is observed to what is already known. For science, this means building upon the existing knowledge base. For students, this means building new ideas upon their current prior knowledge and understandings. 4. Learners evaluate their explanations in light of alternative explanations, particularly those reflecting scientific understanding. Evaluation, and possible elimination or revision of explanations, is one feature that distinguishes scientific from other forms of inquiry and subsequent explanations. Examples of questions one may ask are: â€Å"Does the evidence support the proposed explanations?†, or â€Å"Can other reasonable explanations be derived for the evidence?† An essential component of this characteristic is ensuring that students make the connection between their results and scientific knowledge. 5. Learners communicate and justify their proposed explanations. Scientists communicate their results in such a way that their results can be reproduced. This requires clear articulation of the question, procedures, evidence, proposed explanation, and review of alternative explanations. Having students share their explanations provides others the opportunity to ask questions, examine evidence, identify faulty reasoning, point out statements that go beyond the evidence, and suggest alternative explanations for the same observations. As a result of this communication, students can resolve contradictions and solidify an empirically based argument.

How to Become a Good Parent

In this world, parents consider as torchlight for their children. Parents try to do everything for their children whether it is hard or easy for them. Parents gave them directions how to start their new life by themselves. To become a good parent, a person must have all good qualities which are necessary for their children. There are various steps to become a good parent. The first step is to always take care of your children properly. Parents need to give food to children at proper time in an adequate amount. Never leave them alone till age of maturity. Always keep an eye on their daily activities. Parents also need to take information about their children such as who are their friends in schools and neighborhood. They must find out are they good natured students? The second step is that parents must tell their children what is good for them or what is bad. In this way, children can remain safe without anybody else’s care. If children have already known about bad things, they never do any bad habits. They will always remain far away from bad habits like smoking and gambling. Sometimes, some students start to do bad habits because nobody told them the difference between good and bad. However, parents must tell the disadvantages of bad habits to their children. The third step is to help them in their study. Parents always help their children at the time of any difficulty in their study. Also parents need to decide whether or not children need part-time tutor for their homework. If parents can’t help their children in any difficulties regarding studies, they need to ask the teacher to teach them again on parent’s day. The fourth step is to show your love and also gave them examples of their life experiences. Parents should not shout at their children in front of others. If they will be doing this, children felt their insult and it will lessen their love towards parents. Parents should always teach them in positive way which means with a lot of love. Parents never put so many burdens on their children so that they will become like a burning candle, for example- job along with study, house responsibilities. The fifth step is to teach children, how to survive in this complicated world. Parents teach their children, how to face the difficulties in their life. The guidance and motivation always remains in the mind of children forever because they learned guidance during growing up. Parents must teach their children to think deeply before doing anything, for example- While taking any decision regarding their life goals. In conclusion, by following these steps which are take care, recognizing of bad and good habits, helping them in their study, love, a person can become a good parent. These steps will make a good parent for children who are going to start a new life. The past experiences of parents become lessons for their children in future.