Ict analysis Essay Example for Free

Ict analysis Essay It is also very easy to produce the forms as it is just paper and questions that have been printed. This is very easy task for the restaurant but if the customer number increases higher it will be impossible for the system to work in order. Â  This filing system will never break down and have to go in for repairing unlike an application program, which might have to go in for repairing because of technical problems or damage. Â  The data wont get lost due to technical fault however through human error it can be misplaced but not every detail of the every customer will not be lost. But if the datas on the computer and it gets damaged all of Fusions information can be lost. To prevent this they will have to keep back up files. Problem Description This project will aim to solve the data-handling problems of the new restaurant called Fusion. This is a restaurant where a variety of foods are served. To do this work and provide these services customer details (name and address), booking Details and table details are collected and stored in filing cabinets. For the current system the data is collected by asking the customers their details over the phone or in person. This current system has a few disadvantages. These are some of the disadvantages for using the current system: Its very time consuming to use. When the staff wants to find a particular file it takes them an unesccerray long time to go through all the folders and find the file they needed. This is also waste the customers time as they can become very impatient waiting for their file to be taken out. Â  The current system is also a waste of paper because when a new customer comes in they have to fill in a form or if a customers form is misplaced they will have to fill it in again which will cause inconvenience for the customers and the staff at the Fusion Restaurant. Making the restaurant look incompetent. Â  The current system also takes up a lot of storage space, which is eventually going to run out as they are going to get more and more new customers everyday. Â  If a customer wanted to edit their details the staff may find it really difficult to edit it and update information, as it is on paper and will have to be crossed out. This will also be very untidy and not very eye catching. Â  Also, if one member of staff fills up one form and another member of staff has to use it the next day it will be very hard to understand some peoples handwriting. This may cause inconvenience for the customer. Â  The system which is being used now can also be damaged as it is just ordinary paper and can be ruined easily by water, tea or coffee. Â  Another issue is if the original form which was filled previously is misplaced the customer will have to fill another form. This is very frustrating and annoying for the customers. Possible solutions There are a lot of possible solutions for all the problems. These are some of the most sensible and important solutions: They could employ more staff as part of the staff can only organise all the files in the filing cabinet, but this has a disadvantage as it is very expensive to hire more staff and it might cause confusion among the other staff because of so many people working in one restaurant. Â  They can also have different filing cabinets for different customers in alphabetical order. This will make it easier for the staff to find the files as they can just go to the filing cabinet for the people whose name began with an A for example. They can also have a different filing cabinet for bookings and reservations for the day. As this will help the staff, because they can go and check the reservations as they will know which filing cabinet the information is in. Â  They could also have a data handling system made as this will save their time, will be user-friendly, it will also make files a lot easier to locate and there will be no misspellings in this system. This is also saves on the storage space that would have been used previously for storing all the files. Chosen Solutions I have chosen the best chosen solution for solving the problem that Fusion is currently facing. I think the best solution for this problem is to use an application program which might not be specifically made for storing data from restaurants but can be customised to what the restaurant needs in its data handling system. Some of the advantages of this solution are: Â  This application program will be able to save all the data from fusion restaurant, with no misspellings and it will also save a lot of storage space. Also the data cannot be misplaced to anywhere as it is on the computer and as long as the staff press the save button none of the data can be lost. Â  The data saved on the application program can be edited easily and will still be neat unlike the current system that is being used at Fusion. Â  The application program wont be time consuming as data can be found within approximately 45 seconds rather then the current system which might take more then 15 minutes. The application program will also save a lot of paper and ink as the system will be fully digital and wont need to be printed onto paper. The handwriting in the current system is very hard to read as different people fill out different forms, but with an application program everything will be typed in so this will make the writing very easy to read and understandable for all members of staff. Â  This might take some training for people who arent familiar with computers but in the long run it is better for the restaurant itself as it is a very modern restaurant and so should have a modern data handling system like the bigger and more established restaurants. System objectives There are a few system objectives for this application program as these will help improve the service provided by the application program. The system objectives for this application program are: It should allow the staff at the Fusion restaurant to edit customer details as neatly as possible. Allow me to find customer bookings quicker then the current filing system being used at Fusion. Â  Allow the staff at Fusion to find customers easily, so they can attend other customers. Â  The application program should be easy to use. It also allows the staff to get in touch with the customers which is a positive thing for the restaurant. Â  The application program should be able to display information fast so it doesnt cause any inconvenience for the staff or the customer. It should be able to quickly delete customers as when they had filing cabinets they had to find the folder which had to been thrown out. Performance criteria The performance criteria is linked to the system objective as it is just a more detailed explanation about the system objectives. The performance criteria for the application program are: The system should allow the staff to easily change customer details without time constraints. Â  It should also allow me to find customer bookings without any problems in about 45 seconds. Â  The application program should also allow me to find customers easily without showing me other customers and customer details. Â  It should be easy to use so people without any ICT skills can use it easily too. It should also allows the staff to get in touch with the customer as pictures can be added to the application program so this shows a clear picture of how the customer looks like. It should also display information faster, in about 45 seconds for the maximum. It should be able to quickly delete customers as when they had filing cabinets they had to find the folder which had to been thrown out. This is more efficient and environmentally friendly so therefore no paper is being wasted and also increases the speed of data being processed. Current resources Fusion has a PC even though not used for data handling it is used for emailing customers about current offers and information about Fusion. The current resources that are being used now at Fusion restaurant are: A Flat screen which is 15 inches in size and has a Screen Resolution of 1280 x 800. Â  It runs on Windows XP and has the software Microsoft office 2000 right now which is quite old and doesnt have a lot features. Â  It is of the brand Samsung, which is quite popular for PCs. The internet connection is DSL, which is faster than the normal internet connections available. Hardware The hardware in a computer is equipment involved in the function of a computer. Computer hardware consists of parts that can be physically handled. The functions of these components are usually divided into three main categories: input, output, and storage. Software Computer software is a general term used to describe a collection of computer programs, procedures and documentation that perform tasks on a computer system. The term includes application software such as word processors which perform productive tasks for users, system software such as operating systems, which interface with hardware to provide the necessary services for application software, and middleware which controls and co-ordinates distributed systems.

Humorous Wedding Speech †Two Best Men :: Wedding Toasts Roasts Speeches

Humorous Wedding Speech – Two Best Men Good afternoon Ladies and Gentlemen - My name is Steve and this is my partner in crime, Scot. We are the best men today, famed for our double act. Some people may even say we were artists, but I think you'll all realize what kind of artists we are later on this evening. Now, I’d like to think that Gary chose Scott and me to be joint best men so that we could both be by his side on his wedding day. However, Scott reckons Gary only picked us for the wedding photos. Me, so he'd look slimmer, and Scott, so he'd look taller. But in actual fact, it was the bride’s idea to appoint two best men. She thought one person wouldn’t be enough to ensure Gary got to the church on time, smartly dressed and sober. Well, it certainly took more than one person to haul him away from his mini bar last night. Scot It is customary for the best man to retell an embarrassing tale or two from the bridegroom’s past. As Gary’s oldest friend, this part of the speech fell to me. However, I had two problems with this. Firstly, Gary originally insisted on vetting the speech, which would have meant me going to the trouble of preparing two speeches. Luckily, he relented. Secondly, Gary is the original Mr. Nice Guy and it's very difficult to think of anything bad to say about him. So, back to you Steve! Steve I have known Gary a much shorter time than Scot, as you may be able to guess from my youthful good looks and boyish charm. And since I didn't know Gary at school, I've had to rely on his own version of events regarding his education. From this, I gathered that Gary was an exceptionally gifted student and he excelled in almost everything he did, be it sports, academics or the arts, and he left school to the great sadness of his headmaster Scot Well, I did go to school with Gary and I can tell you that’s rubbish. I remember him to be a rather obese, annoying little pupil who excelled at nothing, was constantly picked on, and regularly beaten up – and this was just by the teachers. He most certainly wasn’t gifted at sports either. It didn’t matter what game we played, he was useless in every position.

Error Correction Model

Introduction Exchange rates play a vital role in a county's level of trade, which is critical to every free market economies in the world. Besides, exchange rates are source of profit in forex market. For this reasons they are among the most watched, analyzed and governmentally manipulated economic measures. Therefore, it would be interesting to explore the factors of exchange rate volatility. This paper examines possible relationship between EUR/AMD and GBP/AMD exchange rates. For analyzing relationship between these two currencies we apply to co-integration and error correction model.The first part of this paper consists of literature review of the main concepts. Here we discussed autoregressive time series, covariance stationary series, mean reversion, random walks, Dickey-Fuller statistic for a unit root test. * The second part of the project contains analysis and interpretation of co-integration and error correction model between EUR/AMD and GBP/AMD exchange rates. Considering t he fact, that behavior of these two currencies has been changed during the crisis, we separately discuss three time series periods: * 1999 2013 * 1999 to 2008 * 2008 to 2013. ——————————–Autoregressive time series A key feature of the log-linear model’s depiction of time series and a key feature of the time series in general is that current-period values are related to previous period values. For example current exchange rate of USD/EUR is related to its exchange rate in the previous period. An autoregressive model (AR) is a time series regressed on its own past values, which represents this relationship effectively. When we use this model, we can drop the normal notation of Y as the dependent variable and X as the independent variable, because we no longer have that distinction to make.Here we simply use Xt. For instance, below we use a first order autoregression for the variable Xt. Xt=b0+b1*Xt-1+? t Covariance stationary series To conduct valid statistical inference we must make a key assumption in time series analysis: We must assume that the time series we are modeling is Covariance Stationary. The basic idea is that a time series is covariance stationary, if its mean and variance do not change over time. A covariance stationary series must satisfy three principal requirements. Expected value of the time series must be constant and finite in all periods. * Variance should be constant and finite. * The covariance of the time series with itself for a fixed number of periods in the past or future must be constant and finite. So, we can summarize if the plot shows the same mean and variance through time without any significant seasonality, then the time series is covariance stationary. What happens if a time series is not covariance stationary but we use auto regression model? The estimation results will have no economic meaning.For a non-covariance- stationary time series, est imating the regression with the help of AR model will yield spurious results. Mean Reversion We say that time series shows mean reversion if it tends to fall when its level is above its mean and rise when its level is below its mean. If a time series are currently at its mean reverting level, then the model predicts, that the value of the time series will be the same in the next period Xt+1=Xt. For an auto regressive model, the equality Xt+1 = Xt implies the level Xt = b0 + b1 * Xt or Xt = b0 / (1 – b1)So the auto regression model predicts that time series will stay the same if its current value is b0/(1 – b1), increase if its current value is below b0 / (1 – b1), and decrease if its current value is above b0 / (1 – b1). Random Walks A random walk is a time series in which the value of the series in one period is the value of the series in the previous period plus an unpredictable error. Xt = Xt-1 + ? t, E(? t)=0, E(? t2) = ? 2, E(? t, ? s) = 0 if t? s Th is equation means that the time series Xt is in every period equal to its value in the previous period plus an error term, ? , that has constant variance and is uncorrelated with the error term in previous periods. Note, that this equation is a special case of auto correlation model with b0=0 and b1=1. The expected value of ? t is zero. Unfortunately, we cannot use the regression methods on a time series that is random walk. To see why, recall that if Xt is at its mean reverting level, than Xt = b0/ (1 – b1). As, in a random walk b0=0 and b1=1, so b0/ (1 – b1) = 0/0. So, a random walk has an undefined mean reverting level. However, we can attempt to convert the data to a covariance stationary time series.We create a new time series, Yt, where each period is equal to the difference between Xt and Xt-1. This transformation is called first-differencing. Yt= Xt – Xt-1 = ? t, E (? t) = 0, E (? t2) = ? 2, E (? t, ? s) = 0 for t? s The first-differenced variable, Yt, i s a covariance stationary. First note, that Yt=? t model is an auto regressive model with b0 = 0 and b1 = 0. Mean-reverting level for first differenced model is b0/ (1 – b1) = 0/1 = 0. Therefore, a first differenced random walk has a mean reverting level of 0. Note also the variance of Yt in each period is Var(? ) = ? 2. Because the variance and the mean of Yt are constant and finite in each period, Yt is a covariance stationary time series and we can model it using linear regression. Dickey-Fuller Test for a Unit Root If the lag coefficient in AR model is equal to 1, the time series has a unit root: It is a random walk and is not covariance stationary. By definition all random walks, with or without drift term have unit roots. If we believed that a time series Xt was a random walk with drift, it would be tempting to estimate the parameters of the AR model Xt = b0 + b1 * Xt -1 + ? using linear regression and conduct a t-test of the hypothesis that b1=1. Unfortunately, if b1=1 , then xt is not covariance stationary and the t-value of the estimated coefficient b1 does not actually follow the t distribution, consequently t-test would be invalid. Dickey and Fuller developed a regression based unit root test based on a transformed version of the AR model Xt = b0 + b1 * Xt -1 + ? t. Subtracting xt-1 from both sides of the AR model produces xt- xt-1=b0+(b1-1)xt-1+ ? t or xt-xt-1 = b0 + g1xt-1+ ? t, E(? ) = 0 where gt = (b1-1). If b1 = 1, then g1 = 0 and thus a test of g1 = 0 is a test of b1 = 1. If there is a unit root in the AR model, then g1 will be 0 in a regression where the dependent variable is the first difference of the time series and the independent variable is the first lag of the time series. The null hypothesis of the Dickey-Fuller test is H0: g1 =0 that is, that the time series has a unit root and is non stationary and the alternative hypothesis is Ha: G1 ; 0, that the time series does not have a unit root and is stationary.To conduct the test, on e calculates a t- statistic in the conventional manner for g(hat)1 but instead of using conventional critical values for a t- test, one uses a revised set of values computed by Dickey and Fuller; the revised set of critical values are larger in absolute value than the conventional critical values. A number of software packages incorporate Dickey- Fuller tests. REGRESSIONS WITH MORE THAN ONE TIME SERIES Up to now, we have discussed time-series models only for one time series. In practice regression analysis with more than one time-series is more common.If any time series in a linear regression contains a unit root, ordinary least square estimates of regression test statistics may be invalid. To determine whether we can use linear regression to model more than one time series, let us start with a single independent variable; that is, there are two time series, one corresponding to the dependent variable and one corresponding to the independent variable. We will then extend our discuss ion to multiple independent variables. We first use a unit root test, such as the Dickey-Fuller test, for each of the two time series to determine whether either of them has a unit root.There are several possible scenarios related to the outcome of these test. One possible scenario is that we find neither of time series has a unit root. Then we can safely use linear regression to test the relations between the two time series. A second possible scenario is that we reject the hypothesis of a unit root for the independent variable but fail to reject the hypothesis of a root unit for the independent variable. In this case, the error term in the regression would not be covariance stationary.Therefore, one or more of the following linear regression assumptions would be violated; 1) that the expected value of the error term is 0. 2 that the variance of the error term is constant for all observations and 3) that the error term is uncorrected across observations. Consequently, the estimated regressions coefficients and standard errors would be inconsistent. The regression coefficient might appear significant, but those results would be spurious. Thus we should not use linear regression to analyze the relation between the two time series in this scenario.A third possible scenario is the reverse of the second scenario: We reject the hypothesis of a unit root for the dependent variable but fail to reject the hypothesis of a unit root for the independent variable. In the case also, like the second scenario, the error term in the regression would not be covariance stationary, and we cannot use linear regression to analyze the relation between the two time series. The next possibility is that both time series have a unit root. In this case, we need to establish where the two time series are co-integrated before we can rely on regression analysis.Two time series are co-integrated if a long time financial or economic relationship exists between them such that they don’ t diverge from each other without bound in the long run. For example, two time series are co-integrated if they share a common trend. In the fourth scenario, both time series have a unit root but are not co-integrated. In this scenario, as in the second and third scenario above, the error term in the linear regression will not be covariance stationary, some regressions assumptions will be violated, the regression coefficients and standard errors will not be consistent, and we cannot use them for the hypothesis tests.Consequently, linear regression of one variable on the other would be meaningless. Finally, the fifth possible scenario is that both time series have unit root, but they are co-integrated in this case, the error term in the linear regression of one term series on the other will be covariance stationary. Accordingly, the regression coefficients and standard errors will be consistent, and we can use them for the hypothesis test. However we should be very cautious in interp reting the results of regression with co-integrated variables.The co-integrated regression estimates long term relation between the two series but may not be the best model of the short term relation between the two series. Now let us look at how we can test for co-integration between two time series that each have a unit root as in the last two scenarios above. Engle and Granger suggest this test: if yt and xt are both time series with a unit root, we should do the following: 1) Estimate the regression yt = b0 + b1xt + ? t 2) Test whether the error term from the regression in Step 1 has a unit root coefficients of the regression, we can’t use standard critical values for the Dickey – Fuller test.Because the residuals are based on the estimated coefficients of the regression, we cannot use the standard critical values for the Dickey- Fuller test. Instead, we must use the critical values computed by Engle and Granger, which take into account the effect of the uncertaint y about the regression parameters on the distribution of the Dickey- Fuller test. 3) If the (Engle – Granger) Dickey- Fuller test fails to reject the null hypothesis that the error term has a unit root, then we conclude that the error term in the regression is not covariance stationary.Therefore, the two time series are not co-integrated. In this case any regression relation between the two series is spurious. 4) If the (Engle- Granger) Dickey- Fuller test rejects the null hypothesis that the error term has a unit root, then we conclude that the error term in the regression is covariance stationary. Therefore, the two time series are co-integrated. The parameters and standard errors from linear regression will be consistent and will let us test hypotheses about the long – term relation between the two series. .If we cannot reject the null hypothesis of a unit root in the error term of the regression, we cannot reject the null hypothesis of no co-integration. In this sc enario, the error term in the multiple regressions will not be covariance stationary, so we cannot use multiple regression to analyze the relationship among the time series. Long-run Relationship For our analysis we use EUR/AMD and GBP/AMD exchange rates with respect to AMD from 1999 to 2013 with monthly bases. After estimating the normality of these time series we found out that the normality has rejected.We got right skewness result and to correct them we used log values of exchange rates. Studying the trade between Armenia and Europe or Great Britain we found out that there is almost no trade relationship between them. Besides we assume, that Armenian Central Bank keeps floating rate of AMD. Taking into consideration these two factors the impact of AMD is negligible to have an essential influence on EUR/GBP rate. That is why we assume that the next models we will build show the relation between EUR and GBP. Graph 1 represents movement of EUR/AMD ; GBP/AMD since 1999 to 2013.From it we can assume that these two currencies have strong long run relationship until Global Financial Crisis. As a result of shock in 2008 the previous relationship has been changed. However, it seems to be long term co-movement between the currencies. To accept or reject our conclusions we examine exchange rates until now including Global Financial Crisis, without crisis and after crisis. Co-integration of period from 1999 to 2013 To be considered as co-integrated the two variables should be non-stationary. So the first step in our model is to check the stationarity of variables by using Augmented Dickey-Fuller Unit Root Test.EViews has three options to test unit-root: * Intercept only * Trend and Intercept * None From the first graph it is visible, that the sample average of EUR/AMD time series is greater than 0, which means that we have an intercept and it should be included in unit-root test. Although, series goes up and down, data is not evolving around the trend, we do not have increasing or decreasing pattern. Besides, we can separately try each of the components and include trend and intercept, if they are significant. In the case of EUR/AMD the appropriate decision is only intercept. Table 1. 1Table 1. We see it from the Table 1. 1, where Augmented Dickey-Fuller test shows p-value of 0. 1809 and as we have decided to use 5% significance level, Null Hypothesis cannot be rejected, which means there is a unit root. So, EUR/AMD exchange rate time-series is non-stationary. The same step should be applied with GBP/AMD exchange rates. We have estimated it and found out, that Augmented Dickey-Fuller test p-value is 0. 3724, which gives us the same results, as in the previous one: the variable has unit root. Since, the two variables are non-stationary, we can build the regression model yt = b0 + 1xt + ? t (Model 1. 1) and use et residuals from this model. So, the second step is to check stationarity for these residuals. Here we should use Eagle Granger 5% critic al value instead of Augmented Dickey Fuller one, which is equal to -3. 34. Comparing this with Augmented Dickey-Fuller t-Statistic -1. 8273. Here minus signs should be ignored. So, comparing two values, we cannot reject Null Hypothesis, which means residuals have unit-root, they are non-stationary. This outcome is not desirable, which means the two variables are not co-integrated.Co-integration till crisis period (1999-2008) Referring back to graph 1, we assume that in 1999-2013 time series two variables are not co-integrated because of shock related to financial crisis. That is why it will be rational first to exclude data from 2008 to 2013 and then again check co-integration between two variables. Here the same steps should be applied as in checking co-integration for time series from 1999 to 2013. For time series from 1999 to 2008, for EUR/AMD exchange rate, Augmented Dickey-Fuller test p-value is 0. 068. From the p-value it is clear that we cannot reject Null Hypothesis, which m eans it has a unit root. Having unit root means EUR/AMD exchange rate time-series is non-stationary. Now we should test stationarity of GBP/AMD exchange rates. The Augmented Dickey-Fuller test p-value is 0. 2556, which means the variable is non-stationary. Since, the two variables are non-stationary, we should build the regression model and using residuals check stationarity. Table 2. 1 In the table above Augmented Dickey Fuller t-test is 3. 57 and so greater than Eagle-Granger 5% significance level critical value 3. 34. That is why we can reject Null Hypothesis and accept Alternative Hypothesis, which means that residuals in regression model has no unit root. Consequently, they are stationary and we can conclude, that EUR/AMD and GBP/AMD time series are co-integrated: have long run relationship. As the variables such as EUR/AMD and GBP/AMD are co-integrated, we can run the error correction model (ECM) as below D(yt) = b2 + b3*D(xt) + b4*Ut-1 +V (Model 1. 2) * D(yt) and D(xt) are fi rst differenced variables b2 is the intercept * b3 is the short run coefficient * V white noise error term * Ut-1 is the one period lag residual of ? t . Ut-1 is also known as equilibrium error term of one period lag. This Ut-1 is an error correction term that guides the variables of the system to restore back to equilibrium. In other words, it corrects this equilibrium. The sign before b4 or the sign of error correction term should be negative after estimation. The coefficient b4 tells as at what rate it corrects the previous period disequilibrium of the system.When b4 is significant and contains negative sign, it validates that there exists a long run equilibrium relationship among variables. After estimating Model 1. 2, short run coefficient value b3 has been 1. 03 and was found significant. And b4, the coefficient of error term has been 5. 06 percent meaning that system corrects its previous dis-equilibrium at a speed of 5. 06% monthly. Moreover, the sign of b4 is negative and s ignificant indicating that validity of long run equilibrium relationship between EUR and GBP.Co-integration during crises period (2008-2013) Now is the time to check stationarity of variables in the period after crisis by the same way as we did above. From the ADF test it is clear that the two variables are non-stationary, after which we can construct ADF ; Eagle Granger test for residuals. However, because of ADF t-statistic is smaller, than Eagle Granger critical value, we could not reject that the residuals have unit-root. So, they are non-stationary and co-integration does not exist between the two currencies.

The Role of HBCUs in American Society Essay - 872 Words

For almost two hundred years, Historically Black Colleges and Universities or HBCUs have played a pivotal role in the education of African-American people, and negro people internationally. These schools have provided the majority of black college graduates at the Graduate and Post-Graduate level; schools such as Hampton University, Morehouse University, Spellman University and Howard University are four universities at the forefront of the advanced education of blacks. For sometime there has been a discussion on whether or not these institutes should remain in existence or if they are just another form of racism. There were also concerning the quality of education provided at these institutions. In my opinion, from the evidence provided†¦show more content†¦Most people who believe that HBCUs are no longer useful also believe that because the law forbids the practice of racism HBCUs should be shut down. However, few take into consideration the many white historically white i nstitutions with a legacy of turning away talented African-Americans. What about these schools? Should they not be closed down as well? I believe that persons who are proponents of the abolition of HBCUs are subconsciously practicing racism, because they are not making mention of the many schools in existence with a predominantly white student body; HBCUs are not meant to be a form of segregation but a part of history. nbsp;nbsp;nbsp;nbsp;nbsp;I also believe that HBCUs are a better alternative to affirmative action. These institutions have the capacity to attract and motivate many young black people, to advance their education. By seeing people just like them, with similar backgrounds and similar interest making great achievements, it provides those young black people with a pride and a sense of empowerment. This is most effective in the poorer neighborhoods where morale is low. It is true that HBCUs enroll students with the lowest test scores in American education; according to Elias Blake Jr. in the article from Emerge, â€Å"Black colleges are still enrolling a majority of the most vulnerable students that have the lowest income and the lowest test scores†¦Ã¢â‚¬  (par. 7). Studies show that in many disadvantaged communities, the quality ofShow MoreRelatedThe Role of Hbcus in American Society880 Words   |  4 PagesFor almost two hundred years, Historically Black Colleges and Universitie s or HBCUs have played a pivotal role in the education of African-American people, and negro people internationally. These schools have provided the majority of black college graduates at the Graduate and Post-Graduate level; schools such as Hampton University, Morehouse University, Spellman University and Howard University are four universities at the forefront of the advanced education of blacks. For sometime there has beenRead MoreThe Education Of African Americans Essay867 Words   |  4 PagesHistorically black colleges and universities, otherwise known as HBCUs, have played an integral role in advancing the education of underprivileged black teenagers since their inception after the American Civil War. They have had students extremely well known in their fields today, such as billionaire entertainer Oprah Winfrey, the first African American Supreme Court Justice Thurgood Marshall, and civil rights activist Martin Luther King, Jr. Though their graduation rates tend to be aroun d 1 in 3Read MoreGraduation Speech : A College Application And Writing An Essay Essay1439 Words   |  6 Pagesthe two should also be included. Predominantly White Institutions (PWI) is colleges or Universities where the student populace is primarily White. Whereas Historically Black Colleges and Universities (HBCUs) are higher education institutions specifically established to educate African Americans. 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Although one can and will receive a degree within their major at either of the two, it is better to be a part of a University where a person knows the birthplace, can personally relate to, and most importantlyRead MoreWhat Is Minority Serving Institutions?916 Words   |  4 Pagesoften surrounds MSIs extends to both women’s colleges and Historically Black Colleges and Universities (HBCUs) and the students who choose to attend them. These institutions must balance their unique histories and specific missions, while simultaneously adapting to an ever-changing social landscape. While women’s colleges must fight the traditional ideas of what a woman is and is not, HBCUs must address systems of oppression and ra cism that continue to impact their work. At one time in historyRead MoreThe Historical And Evolutionary Process That Occurred Essay1387 Words   |  6 Pagesare still in place like siting the pledge at the beginning of school. What is important to note is that education was provided for wealthy White males. Poor people, people of color, slaves and women were not included in the plans for an educated society. This paper will describe, the formation of the first Black Colleges, the current state of affairs, and conclude with the cultural significance of HBCU’s. Segregation During the era of slavery in this nation, the education of slaves was frownedRead MorePredominantly White Institutions vs Historically Black Colleges2755 Words   |  12 Pagesrace to attend an HBCU even if attending a PWI would better further their chances for success. For minority students, this is a part of the process, because we now have more options. We can choose between PWIs which educate mainstream America, or HBCUs which only educate individuals with the same experience, history and background. Being able to choose from different types of schools can be bittersweet. The most important goal however is to receive a good education from a good school, which is aRead MoreAfrican Americans And African American Studies844 Words   |  4 Pagesshed light on African Americans. The progress the students created is seen today in American Universities ,and also HBCUs, where (AAS)African American Studies is implemented into the curriculum. Before, the dissection the formation of AAS, it should be noted that without the sacrifice from others I undoubtedly would not be writing about AAS ,or reflecting on the significance it has created for generations so far. There have always been African Studies, just not in the American Education System, blackRead MoreDoes Joining A Minority Organization Affect The Social, Mental, And Psychological Being Of Minority Students On Predominantly928 Words   |  4 Pagesminority students on predominantly white campuses? In today’s society, Predominately white institutions and campus climate can contribute and play a key role to the success and achievement of minority students. In the twenty-first century, African American (black) students will continue to enroll in predominantly white institutions (PWIs) at greater rates than black students enrolling at historically black colleges and universities (HBCUs); yet, if this current trend continues, over half of black studentsRead MoreThe Field Of Student Affairs1904 Words   |  8 PagesBelow will discuss how the field of student affairs changed because of SPPV (1949) and how it was reflective of the period. The main outcome of SPPV (1949) is it finally prompted the separation of student affairs from faculty. Educators were in dual roles, acting both as faculty and student affairs professionals. SPPV (1949) brought this need to forefront of the discussion and showed how the need for faculty and student affairs workers separation had been growing for the past century (ACE, 1949). These