Narrative vs expository

Saturday, December 14, 2019

Chemistry Study Guide Free Essays

Friday, December 6, 2019

Interest Rates Essay Example For Students

Interest Rates Essay Interest rate essay Causes ofcan be explained as -deferred consumption. When money is loaned the lender delays spending the money on consumption goods. Since according to time preference theory people prefer goods now to goods later, in a free market there will be a positive interest rate. Inflationary expectations. Most economies generally exhibit inflation, meaning a given amount of money buys fewer goods in the future than it will now. The borrower needs to compensate the lender for this. Alternative investments. The lender has a choice between using his money in different investments. If he chooses one, he forgoes the returns from all the others. Different investments effectively compete for funds. Risks of investment. There is always a risk that the borrower will default on the loan. This means that a lender generally charges a risk premium to ensure that, across his investments, he is compensated for those that fail. Liquidity preference. People prefer to have their resources available in a form that can immediately be exchanged, rather than a form that takes time or money to realize. Taxes. Because some of the gains from interest may be subject to taxes, the lender may insist on a higher rate to make up for this loss. The nominal interest rate is the amount, in money terms, of interest payable. The real interest rate, which measures the purchasing power of interest receipts, is calculated by adjusting the nominal rate charged to take inflation into account. There is a market for investments which ultimately includes the money market, bond market, and stock market and currency market as well as retail financial institutions. The CAPM returns the asset-appropriate required return or discount rate i.e. the rate at which future cash flows produced by the asset should be discounted given that assets relative riskiness. Betas exceeding one signify more than average riskiness; betas below one indicate lower than average. Thus a more risky stock will have a hi gher beta and will be discounted at a higher rate; less sensitive stocks will have lower betas and be discounted at a lower rate. The CAPM is consistent with intuition investors (should) require a higher return for holding a more risky asset. Since beta reflects asset-specific sensitivity to non-diversifiable, i.e. market risk, the market as a whole, by definition, has a beta of one. Stock market indices are frequently used as local proxies for the market and in that case (by definition) have a beta of one. An investor in a large, diversified portfolio (such as a mutual fund) therefore expects performance in line with the market. The risk of a portfolio is comprised of systematic risk and specific risk. Systematic risk refers to the risk common to all securities i.e. market risk. Specific risk is the risk associated with individual assets. Specific risk can be diversified away (specific risks average out); systematic risk (within one market) cannot. Depending on the market, a portfolio of approximately 15 (or more) well selected shares might be sufficiently diversified to leave the portfolio exposed to systematic risk only. A rational investor should not take on any diversifiable risk, as only non-diversifiable risks are rewarded. Therefore, the required return on an asset, that is, the return that compensates for risk taken, must be linked to its riskiness in a portfolio context i.e. its contribution to overall portfolio riskiness as opposed to its stand alone riskiness. In the CAPM context, portfolio risk is represented by higher variance i.e. less predictability. Exactly how these markets function is a complex question. However, economists generally agree that the interest rates yielded by any investment take into account:?The risk-free cost of capital ?Inflationary expectations ?The level of risk in the investment ?The costs of the transaction The risk-free cost of capital is the real interest on a risk-free loan. While no loan is ever entirely risk-free, bills issued by major nations like the United States are generally regarded as risk-free benchmarks. The Accident That Changed My Life EssayIt is a common misconception that EMH requires that investors behave rationally. This is not in fact the case. EMH allows that when faced with new information, some investors may overreact and some may under-react. All that is required by the EMH is that investors reactions be random enough that the net effect on market prices cannot be reliably exploited to make an abnormal profit. Under EMH, the market may, in fact, behave irrationally for a long period of time. Crashes, bubbles and depressions are all consistent with efficient market hypothesis, so long as this irrational behavior is not predictable or exploitable. Or in other terms, an efficient market is defined as a market where there are large numbers of rational, profit-maximizers actively competing, with each trying to predict future market values of individual securities, and where important current information is almost freely available to all participants. In an efficient market, competition among the many intelligent participants leads to a situation where, at any point in time, actual prices of individual securities already reflect the effects of information based both on events that have already occurred and on events which, as of now, the market expects to take place in the future. In other words, in an efficient market at any point in time the actual price of a security will be a good estimate of its fundamental value. There are three forms of the efficient market hypothesis 1.The Weak form asserts that all past market prices and data are fully reflected in securities prices. In other words, technical analysis is of no use. 2.The Semi-strong form asserts that all publicly available information is fully reflected in securities prices. In other words, fundamental analysis is of no use. 3.The Strong form asserts that all information is fully reflected in securities prices. In other words, even insider information is of no use. Securities markets are flooded with thousands of intelligent, well-paid, and well-educated investors seeking under and over-valued securities to buy and sell. The more participants and the faster the dissemination of information, the more efficient a market should be.

Friday, November 29, 2019

Business Intelligence and Data Warehousing System

Introduction The name business intelligence (BI) is a name that was formed in the mid 1950s to describe the act of changing un-grouped data from a companyÃ¢â‚¬â„¢s or an organizationÃ¢â‚¬â„¢s contrasting functional data into a common data warehouse that could help the organization to come up with or in reporting and presenting information.Advertising We will write a custom assessment sample on Business Intelligence and Data Warehousing System specifically for you for only $16.05 $11/page Learn More The person uses this collected data network through an easy-to-use interface which functions to display the outcome of the extraction, transformation and loading procedure. This is commonly known as the ETL procedure and it is used to expand the data warehouse. This particular network also acts as an ordered reporting environment that distributes the completed and available functional reports and business decisions all over the various departments of the organ izations. It is noted that in the recent times, service oriented architecture (SOA) has decided to start supplanting and augmenting data warehousing and business intelligence implementations (Biere, 2003). This action of merging data warehousing and business intelligence has a business advantage in that the reporting and making of decisions are carried out or are dependent on a common functional view or better still on one model of the truth. Access to business intelligence information has become timely and it is also known that graphic dashboards have been developed with the main aim of keeping tracks of major business operations. As a result, this has made business intelligence more graphic intensive. Practically, charts and business graphics now form a common part of reports. The graphic dashboards were named so because of their resemblance to the usual automobile or car dashboards. They work by giving operational information at a glance (Moss Atre, 2003). Business intelligence is made up of various techniques of analyzing data and conveying the information that the would-be customers or users will need. The categories include: Geographic Information Systems (GIS) used in collecting spatial data; Standard statistical method used for collecting quantitative data for the purpose of forecasting, predictive models, and decision trees; and Semantic analysis method which is usually used for textual data (Biere, 2003). The Geographic Information System and Business Intelligence Geographic information system is an old but well developed and very informed technology that sprung up in the universityÃ¢â‚¬â„¢s computer science development in the later years of the 1960s. The main reason for coming up with geographic information system was to relate the available collected data with geographic referenced map graphics and pictures so as to help people understand the impact and effects of geography on factors such as behaviour and outcomes of results.Advertising Loo king for assessment on business economics? Let's see if we can help you! Get your first paper with 15% OFF Learn More Geographic information system and business intelligence have been known throughout history to follow different growth and implementation ways. However, these two technologies have been merged due to the overwhelming request by customers to use a more complete technology and also for practical reasons. Within different organizations it is known that the visibility of these two technologies has improved to meet regulatory needs. To meet the needs and requirements of business intelligence and geographic information system beneficiaries, leading business intelligence providers have continually used the two technologies and have provided innovative answers to their rapidly increasing number of end users (Weber, Grothe Schaffer, 1999). The outcome is that the new users have answered to this with new applications that influence the synergy of the merged technolog ies. Geographic information system can be merged with other data technique analysis and business intelligence. There are various factors that have made their integrations very easy as will be discussed in the paper. The merger of geographic information systems with other data technique analysis provides numerous benefits to the whole organization without interfering with or interrupting the already available information technology data. In todayÃ¢â‚¬â„¢s world, geographic information system recognizes the location component of data and relates the data to geographic feature found in a GIS. These features are geographic representations of real features like roads, river, forests, lakes oceans, mountains, buildings, game parks and game reserves, deserts and many more. They also include conceptual features like political boundaries and service areas. When one relates information to these features, she or he enables users to arrange data depending on the geographic area of each record i n the data. For example, they get to know data on mountains, water sources, can easily locate roads, homes and schools while conducting a survey. This type of geographic data operations is shown as a map and clearly shows spatial relationship and influence that cannot be pointed out in traditional tabular views of data (Hall Jordan, 2010). A geographically sorted data gives a chance for the usage of new data that might not have anything in common with the already existing data apart from location, for example, schools and other governmental organizations that engage in data collection such as insurance companies.Advertising We will write a custom assessment sample on Business Intelligence and Data Warehousing System specifically for you for only $16.05 $11/page Learn More GIS analysts can map the addresses they will need or those of insured facilities and overlay flood plain boundaries so as to identify all the facilities within the flood prone areas. This information enables them to compute the logistics on reserves from potential catastrophic floods and can help schools to come up with a budget. Similarly, private and public organizations can also carry out the same investigation to find out the potential impact on facilities, supply chains and employees (Hall Jordan, 2010). Geographic information system and business intelligence came into use or were implemented at a time when the general information technology was developing to embrace common ways of compiling, distributing, storing and using data. Most business environments, both public and private organizations, had an increasing demand to operate effectively so as to be able to meet the requirements of their increasing number of clients. As a result, they found a propriety system a major hindrance to their daily business operations. To solve this problem, various IT providers and different organizations proposed that they should try to adapt a method that had concepts of using standard and common ways of integrating data. From the time these standards were adopted by the providers of IT, it became very easy for different applications to interact as they shared the same foundations of technology. It is also noted that internet technology also improved tremendously and became a major communication protocol that enabled the exchange of information between the various functional departments of an organization. As the standards were being put to use, business intelligence and GIS concentrated more on dealing with and giving information they considered very important to their major users (Prabhu, 2004). The BI providers made connectors for most common file formats used by businesses while on the other hand the GIS experts worked hard to create connections of geographic features formats that were in worldwide use then. The increased use of internet and the adoption of standards as a data and information medium partly contributed to mission of enterprise im plementations of applications. BI application operators had technology grounds and applications that could help in meeting the requirements of enterprise implementations. However as discussed earlier, both BI and GIS operations work differently. It was therefore thought that merging these two applications would give opportunities for proliferations of the technologies and the benefits of these two technologies would be realized through using operational units that are recently not using similar technologies. Consequently, this would lead to the expansion of integrated applications in the entire enterprise. These same sentiments were shared by innovators in governmental organizations that needed to obtain actionable information from the existing data (Prabhu, 2004).Advertising Looking for assessment on business economics? Let's see if we can help you! Get your first paper with 15% OFF Learn More BI experts also found out that the already adopted standard technology architectures would make the merging of GIS and BI very easy. If anything, every technology gave solutions and answers to issues that were seen as major obstacles to enterprise implementations of respective applications. GIS experts saw that using tabulated data obtained from numerous databases and file systems would have been hard and expensive, while on the other hand the BI experts solved this problem by using the ETL method or using connectors that enabled BI applications to use native language. However BI providers found it most difficult to work with geographic data format, CAD data and imagery. To add to this problem, they also had difficulties with the projections used in GIS maps. But then again the GIS providers solved this issue by using standards of the interoperability of their data (Prabhu, 2004). Data Warehousing and Business Intelligence Data warehousing is an important aspect to talk about when d iscussing business intelligence. Data warehousing has different definitions a few of which are listed below: Data warehouse is a recent development in database management in which copies of all the databases in an organization or a company are kept or arranged in one single location and can easily be accessed by employees from any locality. It is also the method of designing, building and maintaining a data warehouse system (SCN Education, 2001). Data warehouse can also be defined as a collection of an organizationÃ¢â‚¬â„¢s data that has been compiled and kept electronically. They are made in such a way that they make easy the reporting and analysis of information (Thierauf, 2001). Data warehousing is related to business intelligence (BI). It tells us that the major thing that the project personnel should do is to collect information from final consumers because they are usually not well conversant with the data warehouse matters and as a result they need the guidance of a business sponsor. It is very important to do a proper choice of data warehouse personnel and tools and also business intelligence software. The personnel can either be external consultants who are normally more experienced and have elaborate knowledge in the field, or they can be permanent employees. Permanent employees are found to be much more economical as opposed to consultants who are very expensive (Hall Jordan, 2010). The next step involves executing data warehouse design which involves several steps such as quality assurance, incremental enhancement, the physical environmental set up and many more. The design of the data warehousing must be done taking into consideration various issues such as what is supposed to be done to successfully finish the phase, the approximate amount of time that is needed to finish it, and the documents that will be needed at the end of the task to show every single step taken during the data warehouse task. The documents help consultants to relay their o utcomes to clients. Models of Data Warehousing The models of data warehousing are divided into dimensional model, conceptual model and logical model. Dimensional model is normally used in data warehousing systems that are used for translational type systems. It deals with aspects such as category of information for instance time and attributes. It also contains a fact table which is a table that gives information on the measure of interest such as amount of sales in a business. On the other hand a conceptual data model shows the level of relationship between various areas. A logical data model gives a much detailed description of data without taking into account how they will be implemented in the database. Business Intelligence is made up of various techniques for analyzing data and conveying information to the would-be decision makers. Standard Statistical Methods and Business Intelligence This is a method that uses statistical surveys to compile quantitative information involving attributes of a population. This analysis may centralise on opinions or factual information based on its use and it mostly involves asking questions directly to individuals. Ã¢â‚¬Å"These questions can be given by a researcher whereby this type of examination is called a structured interview or researcher administered survey,Ã¢â‚¬ (Thierauf, 2001, p. 67). It can also be in the form questionnaires. In this technique, the questions are usually ordered and standardized in such a way that the question does not have any effect on the answers to the questions. This is done to ensure validity, reliability and generalizability of the research. All the other people taking the survey test should be given the same questions in the same order as it was done to the others. This ensures accuracy and reliability of the collected data. In organization development (OD), keenly structured examination tools are usually used on the basis of data collection, organizational diagnosis and other expected outcomes of the business (Weber et al., 1999). This technique can be used to study concepts such as curriculum development. It becomes more useful when the researcher wants to have a one-on-one encounter with the respondents. Here the survey questions are given in the form of questionnaires. The people involved go from door to door or home to home asking questions and collecting their data at the same time. The data collected is then quantified for later use. For example, if a given country needs to change its curriculum, first it will have to come up with the design of how it wants the new syllabus to look like, the subjects that are supposed to be taught and those that should be left out, the stages at which the subjects are supposed to be taught, the resources they would expect the teachers to use and the methods of teaching, as well as the form of behaviour reinforcement to be used to mention but a few. The response to these questions during the piloting stage will give the dev elopers the green light to go ahead and implement the new structured curriculum or they will have to go back to the drawing board. For instance, if majority of the people find the newly proposed curriculum to meet the countryÃ¢â‚¬â„¢s educational and workforce needs then it can be implemented. On the other hand, if majority of respondents are not satisfied with the proposed curriculum then the developers will use their responses and opinions to come up with a syllabus that is suitable to their citizens and one that meets their countryÃ¢â‚¬â„¢s needs. Usually the outcome of this technique is very reliable and effective and can also be merged with geographic information system to help the people involved to get to various regions of the country (Thierauf, 2001). The standard statistical methods can also be used by a country to find out how its citizens have advanced technologically. For example surveyors can set out to find out the number of people using electronics such as computers, televisions, microwaves, electric cookers, refrigerators among other electronics at home. In such a case, the surveyors move from home to home both in the rural and urban areas collecting data about each of the equipment named above. Businesses can also make use of this technique to find out about their customersÃ¢â‚¬â„¢ feelings towards their products and services. The results from the survey can help the organization to make decisions that would increase their customer base by developing products and services that meet their customersÃ¢â‚¬â„¢ needs. The advantage of this method is that it does not require users to be highly educated so as to be able to interpret the data. On the negative side, it is time consuming since it is done manually and not electronically. This technique becomes much more effective when merged with GIS because whereas the technique itself does not give maps and pictorials, it can use maps and pictorials from the GIS (Prabhu, 2004). Semantic text mining and BI too go hand in hand as this helps in retrieving data from large amounts of data that is mainly collected in text form. Text mining helps BI experts by equipping them with skills on how to get textual data organised and ordered so that it can be easy to use. Most companies such as call centres, emails and many more collect their data in text form. This information is noted to be increasing on a daily basis and at a high rate. By using text mining BI experts apply the knowledge of text mining examining numbered and short hand data information in the business organization. They then organize this information into manageable form that can be used by others. They do this without omitting the most important part of information that would have been otherwise lost if text mining was not used (Gao, Chang Han, 2005). Reference List Biere, M. (2003). Business intelligence for the enterprise. Upper Saddle River: Pearson Education. Gao, L., Chang, E., Han, S. (2005). Powerful tool to expan d business intelligence: text mining. World Academy of Science, Engineering and Technology, 8, 110-115. Hall, D., Jordan, J. (2010). Human-centred information fusion. Chicago: Artech House. Moss, L., Atre, S. (2003). Business intelligence roadmap: the complete project lifecycle for decision-support applications. New York: Addison-Wesley. Prabhu, C. (2004). Data warehousing: concepts, techniques, products and applications. New Delhi: Prentice-Hall of India. SCN Education. (2001). Data warehousing: the ultimate guide to building corporate business intelligence. Berlin: Wiley-VCH. Thierauf, R. (2001). Effective business intelligence systems. London: Greenwood Publishing Group. Weber, J., Grothe, M., Schaffer, U. (1999). Business intelligence. Berlin: Wiley-VCH. This assessment on Business Intelligence and Data Warehousing System was written and submitted by user Kenny Hartman to help you with your own studies. You are free to use it for research and reference purposes in order to write your own paper; however, you must cite it accordingly. You can donate your paper here.

Monday, November 25, 2019

Acids and Bases essays

Acids and Bases essays What substances turned into Acids? Pour about three milliliters of your sample in each of three test tubes. Pour the same amount on a watch glass. In the first test tube put in two drops of methyl orange and record the color. In the second test tube, put in two drops of bromothymol blue and record the color. In the third test tube, add two drops of phenothalein and record the color. Using the watch glass sample, touch the tips of a red and a blue litmus paper and record the colors. Then touch the tip of a piece of pH Paper and record the color and match the color to the chart and record the pH. Methyl O Bromothymol B Phenothalein R Litmus B Litmus pH Paper Color Congo R AA- orange/red yellow clear red red pink(1) purple OJ- red/orange yellow yellow red pink Orange(4) purple HA- red yellow clear red red red(2) purple Bleach-orange yellow clear red red orange(4) purple Vinegar-red yellow clear red red red(1) purple SH-orange blue red blue blue brown(12) orange Mouth wash-red yellow/green sky blue red red red(1) purple Lemon J-red yellow clear red red red(2) purple Windex-Orange blue clear red blue orange(6) red Plax-orange blue lilac red ...

Thursday, November 21, 2019

Abstract Essay Example | Topics and Well Written Essays - 250 words - 20

Abstract - Essay Example Vikings colonist in Iceland and Greenland farmed and filled storehouse with luxuries for trade in the Europeans. The Canadian archeologist discovered iron ship rivets and many artifacts belonging to the Vikings in the coast of Ellesmere Island. Hence, the discovery of the yarn in 1999 made Sutherland to scrutinize other archeologist artifacts originating from the domain of Arctic hunter. Surprisingly, the spun yarns found spread from Nunguvik, Tanfield Valley, Willows Island, to Avayalik Island located between Northern Baffin Island and Northern Labrador. Moreover, the fragments of tally sticks discovered resembled Vikings items used to record trade transaction and to spin fibers. Consequently, many artifacts from the Arctic found in the Museum pointed out the good relation in trade between the Dorset hunters and Vikings. The Viking always moved in search of new traders hence exploring the North American Coast. Therefore, the small nomad of Dorset hunters welcomed hunted walruses and fur-bearing animals whose fur could be spun to luxurious yarn. Therefore, the Vikings camping at the Tanfield Valley open an opportunity to trade with the Dorset hunters for

Wednesday, November 20, 2019

IBM's workforce management initiative(WMI) Essay

IBM's workforce management initiative(WMI) - Essay Example ) is basically an approach to the human capital management which would make the company a global integrated enterprise whose operations cut across wide geographical areas and which placed various value creation processes in a worldwide arena that optimized their productivity and efficiency (Boudreau 2010). The idea of WMI actually was developed by the then IBMÃ¢â‚¬â„¢s chief human resource officer, Randy MacDonald in 2003 and was later supported by other members of the work force. This idea required a lot of changes to be done in the management. According to the IBMÃ¢â‚¬â„¢s management, one of the important moves towards the achievement of its goal was to start a business metaphor for the IBM which would be a basis for what was referred as Ã¢â‚¬Ëœdecision ScienceÃ¢â‚¬â„¢ for talents. The Ã¢â‚¬Ëœdecision scienceÃ¢â‚¬â„¢ is what actually the IBM envisioned. The idea here was to consider the existing employees, applicants, vendor supply and learning as alternative sources of talents supply which were actually based in different geographical areas and within different individuals (Boudreau 2010). It had also to consider some other factors as the language used in such areas as job description; competencies and knowledge, skills and abilities. This is used in describing the resources and also defining and organizing decisions and views towards the resources. There was also need for an expertise taxonomy which would help classify the jobs by identifying things like job roles(JR) and job role skill sets (JRSS) and also identifying coming upon with common descriptors around the tasks executed by different people. By the year 2003, IBM had hundred thousands of full-time employees, over 90,000 contactors and above 40,000 applicants. These were grouped into roles such that by the year 2008, there were around 331 roles needed to define the companyÃ¢â‚¬â„¢s work force. Each role here represented hundreds of both applicants and contractors and over 1000 employees. There are several impacts associated with the

Monday, November 18, 2019

Journal # 1 Essay Example | Topics and Well Written Essays - 250 words

Journal # 1 - Essay Example Internship is an elemental component of nursing leadership where nursing students get to experience various professional scenarios first hand. The first day of Masters in Nursing Leadership internship at The Lake County Community Health Center involved meeting Damaris, M. She is the director of the family case management, nurse family, pregnancy prevention and health-works program. The meeting acted as introduction to what the internship entailed including the number of times such meetings were going to take place in a week. A notable engagement during the internship period was taking part in preparing for an upcoming performance review for the department (Clark 72). This created an opportunity for one to learn what is required in the operations of such a department. The internship also offered invaluable pointers onto the viability of my intended project. This was in the sense that it provided for a chance to remedy all the shortcomings of the project. The internship experience worked towards improving the content and context of the nursing leadership