Tuesday, August 20, 2019
Edward Snowden: The Most Famous Whistleblower Whistleblowers are some of the most important people to have in a democracy. They provide information that the government doesnt want to get out, while this could be dangerous in the case of Edward Snowden he released information that was valuable to the citizens of the united states. Snowden is not the first person to do something like this and has previously stated he was inspired by Daniel Ellsberg who leaked pentagon papers in the 1970s. Even though hes wanted by the government to some people Snowden is a hero. Edward Snowden who was born in North Carolina but later mover to Massachusetts had dropped out of of high school but was no degenerate. A bad case of mononucleosis kept him out of school for 9 months so instead of falling behind he decided that he would drop out. After dropping out he began studying computers at Anne Arundel Community College which was located in Maryland. His father was quoted saying We always considered Ed the smartest one in the family. and this was clear when Edward scored a 145 on two different IQ tests. He later enlisted into the special forces because he wanted to learn new languages, but never made it out of basic because he either broke both legs or washed out because of shin splints, it depends on who you ask. After this he was a security guard at a college in maryland that had ties to the NSA. After this he landed a job with the C.I.A.(Central Intelligence Agency) but quit after being suspected of attempting to break into classified files. While still with the C.I.A. he was on a mission in Switzerland where he first discovered corruption in the Government. This is where he first wanted to become a whistleblower but with Obama being soon elected he was optimistic about the changes he was going to make. After working for the C.I.A. for some time he moved to a private IT company where he worked as a contractor and would later work in a few offices for the N.S.A. this is where he notices a breach in security and got his hands on the classified information that he would leak. The definition of a hero is someone who is admired or idealized for courage, outstanding achievements, or noble qualities. When he was younger, saw sergeant Frank Ford reveal the information about the war in Iraq he thought of him as a hero for being honest, and letting the people know what was really going on in Iraq. Even though Ford was once Snowdens hero Snowden would make a bigger impact than Ford. Sowden and Ford are not the only whistleblowers who have made themselves public. Manning had leaked hundreds of documents that had to do with the wars in Iraq and Afghanistan. Before any of them Ellsberg had leaked a ton of information in the early seventies. Nixons administration alienated Ellsberg much like Obamas administration has done to Snowden but now Ellsberg is considered a hero. Now Snowden is considered the hero to some people but a lot of people within the government or who listen to the government would disagree. He has inspired many other anonymous leaks from within the U.S. Government. Snowden receives credit for most of these but he has said that many leaks come from another source or other sources. The U.S. government has made it clear that they know about the the copycats when a representative, Adam Schiff who is a member of the House Intelligence Committee claiming that it is a big concern of theirs. Schiff also said The degree that people have been lionizing Snowden, it encourages people to make a name for themselves by leaking which is true. Even Some Government officials have publicly claimed that they went too far. Though many people think the Government was in the wrong for so intensely tracking suspected terrorist it makes sense for the Government to do that because some 9/11 hijackers were tracked but then nothing was done about them. Officials say that this could have put the country in more danger by showing potential terrorist how the government tracks them it allows them to b ypass those methods. Schiff also claimed that the Government should be more careful with who gets access to what by saying Snowden should have never had access in the first place. The Pentagon has approved as many as 3.2 million people access to highly classified information from 2006 to 2011 (CNN). After fleeing the country Snowden got ahold of journalists and offered them an unprecedented scoop(PBS). Even though the two journalists had received the documents it was not until they were on a plane and out of the country when they felt safe to open them and look at the things Snowden had shared. Greenwald, one of the journalists was quoted saying I didnt sleep one second for the next 16 hours because the adrenaline made that impossible. He said that he understood that this would be a story like hed never written before and one that people would talk about for decades. The journalists were given thousands of documents that showed what the Obama administration had been doing to regular citizens who had no criminal records and were not suspected terrorists. They were simply eavesdropping on regular citizens who had not done anything wrong. Some of the eavesdropping was justified but a surprising amount was not. Snowdens leaks shed a serious amount of light on this problem and it le d to a two part series on Frontline that dove into the topic from after 9/11 all the way to when things were leaked by Snowden. This series went even further than Snowden when they had revealed the extent that the government went to to keep these secrets hidden. It was during this time where Snowden had revealed that the worst of the wiretapping and eavesdropping had come from when Bush was president. Snowden still cares about America though saying that he would like to return one day and I told the government Id volunteer for prison, as long as it served the right purpose, he says I care more about the country than what happens to me. But we cant allow the law to become a political weapon or agree to scare people away from standing up for their rights, no matter how good the deal. Im not going to be part of that. (Wired). These statements show his true character and that he really does care about America. Snowden claimed that he had tried to leave clues for the N.S.A. to show him what documents were actually copied and which ones were just looked at. Despite these efforts the N.S.A. had missed the clues and reported that he took over a million documents when in reality he on took a few thousand. Snowden sounded disappointed when speaking on the fact that the government had missed his clues because he had thought that they were obvious. Sponsors from both major political parties c an agree that this has shown that the U.S. government needs to stop their mass surveillance for clear reasons. This was such a big deal that President Obama himself as well as congress have both publicly talked about the issue and the Supreme Court has hinted at making a decision about the governments use of unwarranted surveillance. This was never Snowdens intention he had just wanted to share what the government was doing because he felt that it was unjust. Despite the efforts by the government to make Snowden out to be the bad guy more than half the population agrees with what he did. Many government officials have spoken on this but not in the favor of snowden, N.S.A. director Keith Alexander claimed that the russian government had manipulated him while the secretary of state called him a coward and a traitor.
A case referring to the beneficial use of the expert systems in the health sector was the attempt of the LDS Hospital in Salt Lake city,Utah to build “ the most complex artificial intelligence system ever created'; according to the words of DR David Classen.Its name was AIC or “Antibiotic Computer Consultant'; and it was part of HELP(Health Evaluation through Logical Processing), which was LDS’s hospital information system. The latter was existed, before the implementation of the Expert System. The role of AIC was to help doctors determine proper antibiotic treatment for specific patients.Achieving the specific purpose,the Expert System followed the above stages: 1) The doctor turned to the system with information on the infection type and site, and also identified the patient to the computer. 2) The system determined the pathogens, which are likely to have caused the infection. 3) The software examined the patient’s medical records( through the HELP information system) and searched for similar cases nationwide. 4) Finally, it displayed the five most likely antibiotic regimens to be effective and the cost of the prescription for each one. Altough,the system was extremely rewarding and expanded to include other cases involving antibiotics, some criticisms were made against it. It was stated that the system was unwieldy and that physicians had to enter much information, which was useless. Of course, the best answer came straightly from the physicians, who highlighted many important benefits of the AIC. The 88% of them believed that the use of AIC was very simple and they would recommend it to other colleagues. Another 85% stated that the program improved their selection of antibiotics, and 81% agreed that it enhanced patient care. Concerning its usability, doctors access into the system 3 times a day.
Monday, August 19, 2019
The Theory and Implementations of The Balance of Payments (BOP) To develop countryÃ¢â¬â¢s economic strength under the tendency of globalization, governments always seek to achieve two macroeconomic objectives, i.e. stable growth of internal economy and balanced development of external economic activities. The former can be realized by effectively adjusting Economic Growth, Unemployment and Inflation. However, how to realize the latter? An external macroeconomic variable is needed. In practice, the Balance of Payments fulfills this responsibility. (A). Balance of Payments (BOP used in following text), in principle, is a record of the countryÃ¢â¬â¢s transactions with the rest of the world. It shows the countryÃ¢â¬â¢s payment s to or deposits in other countries (debits) and its receipts or deposits from other countries (credits). The BOP account also shows the balance between these debits and credits under various headings, which are categorized into the Current Account, the Capital Account and the Financial Account, which compose the main elements of balance of payments. The Current Account largely measures flow of real resources including exports and imports of goods and services, income receivable and payable abroad, and current transfers from and to abroad. It is normally divided into three subdivisions (Figure 1). Trade in goods account (often as the trade balance) The total value of exports of goods, subtracting the total value of imports of goods. Trade in services account Imports and exports of services, such as banking and insurance, transport services, law, accountancy, management consultancy and tourism. Investment incomes Interest, profit and dividends flowing into and out of the country. Transfers of money Two sectors: government transfers and transfers made by other sectors. Government transfers include contributions to international organisations (e.g. UK to EU budget) and foreign aid. The Ã¢â¬Ëother sectorsÃ¢â¬â¢ section many highlights the transfer of assets by individuals to foreign bank accounts. The Capital Account measures external transactions in capital transfers, and in acquisition or disposal of non-produced, non-financial assets, which include land and subsoil assets, patents and copyrights etc. Capital transfers are transfers of ownership of a fixed asset or the forgiveness of a liability. The Financial Account records transactions in financial assets and liabilities between residents and non-residents. It shows how an economy's external transactions are financed. Transactions in the financial account are classified into direct investment, portfolio investment, other investment, and reserve assets (Figure 2). Direct investment Money flows across national boundaries for the purpose of investing and it is thus either a credit or a debit item. Portfolio investment Changes in the holding of paper assets, such as company shares and bonds. Other investment It comprises loans, currency, deposits, and short and long-term trade credits, financial derivatives and other accounts receivable and payable. Reserve assets This refers to the reserves of gold, special drawing rights (SDRs) and
Sunday, August 18, 2019
Powerful Theme and Allusions to Sex in Anderson's Womanhood Ã Catherine Anderson's poem "Womanhood" tells about a young girl and her transition to womanhood.Ã In this intricately woven poem the reader will learn very little about the girl.Ã Neither she nor her mother are ever named, and no information is given about them or their family life.Ã What the reader does discover is what lies ahead for her as she begins her first day sewing rugs.Ã The poem begins a few moments before she enters the gates of the sweatshop that symbolizes her entry into womanhood.Ã Anderson uses metaphor within this poem to dramatize the difference in what lies ahead for her.Ã She should be looking forward to a bright and cheerful future, instead, she is faced with the drudgery of a life working in a sweatshop sewing rugs.Ã Anderson has woven this poem together so there is a link created between the first and second stanzas of the poem.Ã Each line in the first stanza, describing the carefree attitude of the young girl correlates with a line in th e second stanza illustrating how her life will be far different after she enters the gates of the factory and womanhood.Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Ã Within this poem there are many references or allusions to sex.Ã Most women are considered to have entered womanhood when they have their first sexual experience with a man.Ã Anderson plays up this aspect of becoming a woman in the poem to symbolize the girl's losing her innocence and youth to work in the sweatshop.Ã In essence, she is losing her virginity to that same sweatshop.Ã The first of these allusions to sex is in the opening lines of the poem; "she slides over/the hot upholstery" (1,2).Ã The young girl is described as sliding over hot upholstery, like girls sometimes do to snuggle up next to their boyfriends when driving a car.Ã This verse can also be seen as a metaphor for the hot young skin of a beautiful young girl.Ã Another example of these references is when Anderson describes the girlÃ as "loves humming & swaying to the music" (5).Ã This can be seen as the act of sexual intercourse itself.Ã The rhythmic swaying of bodies can be seen as little else especially when paired with line 25, "rocking back and forth"(25).Ã This is further emphasized by Anderson by her use of the ampersand signs (&) which she only uses in these two lines.
Saturday, August 17, 2019
REGRESSION ANALYSIS Correlation only indicates the degree and direction of relationship between two variables. It does not, necessarily connote a cause-effect relationship. Even when there are grounds to believe the causal relationship exits, correlation does not tell us which variable is the cause and which, the effect. For example, the demand for a commodity and its price will generally be found to be correlated, but the question whether demand depends on price or vice-versa; will not be answered by correlation. The dictionary meaning of the Ã¢â¬ËregressionÃ¢â¬â¢ is the act of the returning or going back. The term Ã¢â¬ËregressionÃ¢â¬â¢ was first used by Francis Galton in 1877 while studying the relationship between the heights of fathers and sons. Ã¢â¬Å"Regression is the measure of the average relationship between two or more variables in terms of the original units of data. Ã¢â¬ The line of regression is the line, which gives the best estimate to the values of one variable for any specific values of other variables. For two variables on regression analysis, there are two regression lines. One line as the regression of x on y and other is for regression of y on x. These two regression line show the average relationship between the two variables. The regression line of y on x gives the most probable value of y for given value of x and the regression line of x and y gives the most probable values of x for the given value of y. For perfect correlation, positive or negative i. e. for r= Ã ±, the two lines coincide i. e. we will find only one straight line. If r=0, i. e. both the variance are independent then the two lines will cut each other at a right angle. In this case the two lines will be Ã ¦to x and y axis. The Graph is given below:- We restrict our discussion to linear relationships only that is the equations to be considered are 1- y=a+bx Ã¢â¬â x=a+by In equation first x is called the independent variable and y the dependent variable. Conditional on the x value, the equations gives the variation of y. In other words ,it means that corresponding to each value of x ,there is whole conditional probability distribution of y. Similar discussion holds for the equation second, where y acts as independent variable and x as dependent variable. What purpose does regression line serve? 1- The first object is to estimate the dependent variable from known values of independent variable. This is possible from regression line. Ã¢â¬â The next objective is to obtain a measure of the error involved in using regression line for estimation. 3- With the help of regression coefficients we can calculate the correlation coefficient. The square of correlation coefficient (r), is called coefficient of determination, measure the degree of association of correlation that exits between two variables. What is the difference between correlation and linear regression? Correlation and linear regression are not the same. Consider these differences: Ã¢â¬ ¢ Correlation quantifies the degree to which two variables are related. Correlation does not findÃ a best-fit line (that is regression). You simply are computing a correlation coefficient (r) that tells you how much one variable tends to change when the other one does. Ã¢â¬ ¢ With correlation you don't have to think about cause and effect. You simply quantify how well two variables relate to each other. With regression, you do have to think about cause and effect as the regression line is determined as the best way to predict Y from X. Ã¢â¬ ¢ With correlation,Ã it doesn't matter which of the two variables you call Ã¢â¬Å"XÃ¢â¬ and which you call Ã¢â¬Å"YÃ¢â¬ . You'll get the same correlation coefficient if you swap the two. With linear regression, the decision of which variable you call Ã¢â¬Å"XÃ¢â¬ and which you call Ã¢â¬Å"YÃ¢â¬ matters a lot, as you'll get a different best-fit line if you swap the two. The line that best predicts Y from X is not the same as the line that predicts X from Y. Ã¢â¬ ¢ Correlation is almost always used when you measure both variables. It rarely is appropriate when one variable is something you experimentally manipulate. With linear regression, the X variable is often something you experimental manipulate (time, concentrationÃ¢â¬ ¦ and the Y variable is something you measure. Regression analysis is widely used forÃ predictionÃ (includingÃ forecastingÃ ofÃ time-seriesÃ data). Use of regression analysis for prediction has substantial overlap with the field ofÃ machine learning. Regression analysis is also used to understand which among the independent variables are related to the dependent variable, and to explore the forms of these relationships. In restricted circumstances, regression analysis can be used to inferÃ causal relationshipsÃ between the independent and dependent variables. A large body of techniques for carrying out regression analysis has been developed. Familiar methods such asÃ linear regressionÃ andÃ ordinary least squaresÃ regression areÃ parametric, in that the regression function is defined in terms of a finite number of unknownÃ parametersÃ that are estimated from theÃ data. Nonparametric regressionÃ refers to techniques that allow the regression function to lie in a specified set ofÃ functions, which may beinfinite-dimensional. The performance of regression analysis methods in practice depends on the form of the data-generating process, and how it relates to the regression approach being used. Since the true form of the data-generating process is not known, regression analysis depends to some extent on making assumptions about this process. These assumptions are sometimes (but not always) testable if a large amount of data is available. Regression models for prediction are often useful even when the assumptions are moderately violated, although they may not perform optimally. However when carrying outÃ inferenceÃ using regression models, especially involving smallÃ effectsÃ or questions ofÃ causalityÃ based onÃ observational data, regression methods must be used cautiously as they can easily give misleading results. Underlying assumptions Classical assumptions for regression analysis include: ? The sample must be representative of the population for the inference prediction. ? The error is assumed to be aÃ random variableÃ with a mean of zero conditional on the explanatory variables. ? The variables are error-free. If this is not so, modeling may be done usingÃ errors-in-variables modelÃ techniques. ? The predictors must beÃ linearly independent, i. e. it must not be possible to express any predictor as a linear combination of the others. SeeMulticollinearity. The errors areÃ uncorrelated, that is, theÃ variance-covariance matrixÃ of the errors isÃ diagonalÃ and each non-zero element is the variance of the error. ? The variance of the error is constant across observations (homoscedasticity). If not,Ã weighted least squaresÃ or other methods might be used. These are sufficient (but not all necessary) conditions for the least-squares estimator to possess desirable propertie s, in particular, these assumptions imply that the parameter estimates will beÃ unbiased,Ã consistent, andÃ efficientÃ in the class of linear unbiased estimators. Many of these assumptions may be relaxed in more advanced treatments. Basic Formula of Regression Analysis:- X=a+by (Regression line x on y) Y=a+bx (Regression line y on x) 1st Ã¢â¬â Regression equation of x on y:- 2nd Ã¢â¬â Regression equation of y on x:- Regression Coefficient:- Case 1st Ã¢â¬â when x on y means regression coefficient is Ã¢â¬ËbxyÃ¢â¬â¢ Case 2nd Ã¢â¬â when y on x means regression coefficient is Ã¢â¬ËbyxÃ¢â¬â¢ Least Square Estimation:- The main object of constructing statistical relationship is to predict or explain the effects on one dependent variable resulting from changes in one or more explanatory variables. Under the least square criteria, the line of best fit is said to be that which minimizes the sum of the squared residuals between the points of the graph and the points of straight line. The least squares method is the most widely used procedure for developing estimates of the model parameters. The graph of the estimated regression equation for simple linear regression is a straight line approximation to the relationship between y and x. When regression equations obtained directly that is without taking deviation from actual or assumed mean then the two Normal equations are to be solved simultaneously as follows; For Regression Equation of x on y i. e. x=a+by The two Normal Equations are:- For Regression Equation of y on x i. e. y=a+bx The two Normal Equations are:- Remarks:- 1- It may be noted that both the regression coefficient ( x on y means bxy and y on x means byx ) cannot exceed 1. 2- Both the regression coefficient shall either be positive + or negative -. 3- Correlation coefficient (r) will have same sign as that of regression coefficient. Regression Analysis REGRESSION ANALYSIS Correlation only indicates the degree and direction of relationship between two variables. It does not, necessarily connote a cause-effect relationship. Even when there are grounds to believe the causal relationship exits, correlation does not tell us which variable is the cause and which, the effect. For example, the demand for a commodity and its price will generally be found to be correlated, but the question whether demand depends on price or vice-versa; will not be answered by correlation. The dictionary meaning of the Ã¢â¬ËregressionÃ¢â¬â¢ is the act of the returning or going back. The term Ã¢â¬ËregressionÃ¢â¬â¢ was first used by Francis Galton in 1877 while studying the relationship between the heights of fathers and sons. Ã¢â¬Å"Regression is the measure of the average relationship between two or more variables in terms of the original units of data. Ã¢â¬ The line of regression is the line, which gives the best estimate to the values of one variable for any specific values of other variables. For two variables on regression analysis, there are two regression lines. One line as the regression of x on y and other is for regression of y on x. These two regression line show the average relationship between the two variables. The regression line of y on x gives the most probable value of y for given value of x and the regression line of x and y gives the most probable values of x for the given value of y. For perfect correlation, positive or negative i. e. for r= Ã ±, the two lines coincide i. e. we will find only one straight line. If r=0, i. e. both the variance are independent then the two lines will cut each other at a right angle. In this case the two lines will be Ã ¦to x and y axis. The Graph is given below:- We restrict our discussion to linear relationships only that is the equations to be considered are 1- y=a+bx Ã¢â¬â x=a+by In equation first x is called the independent variable and y the dependent variable. Conditional on the x value, the equations gives the variation of y. In other words ,it means that corresponding to each value of x ,there is whole conditional probability distribution of y. Similar discussion holds for the equation second, where y acts as independent variable and x as dependent variable. What purpose does regression line serve? 1- The first object is to estimate the dependent variable from known values of independent variable. This is possible from regression line. Ã¢â¬â The next objective is to obtain a measure of the error involved in using regression line for estimation. 3- With the help of regression coefficients we can calculate the correlation coefficient. The square of correlation coefficient (r), is called coefficient of determination, measure the degree of association of correlation that exits between two variables. What is the difference between correlation and linear regression? Correlation and linear regression are not the same. Consider these differences: Ã¢â¬ ¢ Correlation quantifies the degree to which two variables are related. Correlation does not findÃ a best-fit line (that is regression). You simply are computing a correlation coefficient (r) that tells you how much one variable tends to change when the other one does. Ã¢â¬ ¢ With correlation you don't have to think about cause and effect. You simply quantify how well two variables relate to each other. With regression, you do have to think about cause and effect as the regression line is determined as the best way to predict Y from X. Ã¢â¬ ¢ With correlation,Ã it doesn't matter which of the two variables you call Ã¢â¬Å"XÃ¢â¬ and which you call Ã¢â¬Å"YÃ¢â¬ . You'll get the same correlation coefficient if you swap the two. With linear regression, the decision of which variable you call Ã¢â¬Å"XÃ¢â¬ and which you call Ã¢â¬Å"YÃ¢â¬ matters a lot, as you'll get a different best-fit line if you swap the two. The line that best predicts Y from X is not the same as the line that predicts X from Y. Ã¢â¬ ¢ Correlation is almost always used when you measure both variables. It rarely is appropriate when one variable is something you experimentally manipulate. With linear regression, the X variable is often something you experimental manipulate (time, concentrationÃ¢â¬ ¦ and the Y variable is something you measure. Regression analysis is widely used forÃ predictionÃ (includingÃ forecastingÃ ofÃ time-seriesÃ data). Use of regression analysis for prediction has substantial overlap with the field ofÃ machine learning. Regression analysis is also used to understand which among the independent variables are related to the dependent variable, and to explore the forms of these relationships. In restricted circumstances, regression analysis can be used to inferÃ causal relationshipsÃ between the independent and dependent variables. A large body of techniques for carrying out regression analysis has been developed. Familiar methods such asÃ linear regressionÃ andÃ ordinary least squaresÃ regression areÃ parametric, in that the regression function is defined in terms of a finite number of unknownÃ parametersÃ that are estimated from theÃ data. Nonparametric regressionÃ refers to techniques that allow the regression function to lie in a specified set ofÃ functions, which may beinfinite-dimensional. The performance of regression analysis methods in practice depends on the form of the data-generating process, and how it relates to the regression approach being used. Since the true form of the data-generating process is not known, regression analysis depends to some extent on making assumptions about this process. These assumptions are sometimes (but not always) testable if a large amount of data is available. Regression models for prediction are often useful even when the assumptions are moderately violated, although they may not perform optimally. However when carrying outÃ inferenceÃ using regression models, especially involving smallÃ effectsÃ or questions ofÃ causalityÃ based onÃ observational data, regression methods must be used cautiously as they can easily give misleading results. Underlying assumptions Classical assumptions for regression analysis include: ? The sample must be representative of the population for the inference prediction. ? The error is assumed to be aÃ random variableÃ with a mean of zero conditional on the explanatory variables. ? The variables are error-free. If this is not so, modeling may be done usingÃ errors-in-variables modelÃ techniques. ? The predictors must beÃ linearly independent, i. e. it must not be possible to express any predictor as a linear combination of the others. SeeMulticollinearity. The errors areÃ uncorrelated, that is, theÃ variance-covariance matrixÃ of the errors isÃ diagonalÃ and each non-zero element is the variance of the error. ? The variance of the error is constant across observations (homoscedasticity). If not,Ã weighted least squaresÃ or other methods might be used. These are sufficient (but not all necessary) conditions for the least-squares estimator to possess desirable propertie s, in particular, these assumptions imply that the parameter estimates will beÃ unbiased,Ã consistent, andÃ efficientÃ in the class of linear unbiased estimators. Many of these assumptions may be relaxed in more advanced treatments. Basic Formula of Regression Analysis:- X=a+by (Regression line x on y) Y=a+bx (Regression line y on x) 1st Ã¢â¬â Regression equation of x on y:- 2nd Ã¢â¬â Regression equation of y on x:- Regression Coefficient:- Case 1st Ã¢â¬â when x on y means regression coefficient is Ã¢â¬ËbxyÃ¢â¬â¢ Case 2nd Ã¢â¬â when y on x means regression coefficient is Ã¢â¬ËbyxÃ¢â¬â¢ Least Square Estimation:- The main object of constructing statistical relationship is to predict or explain the effects on one dependent variable resulting from changes in one or more explanatory variables. Under the least square criteria, the line of best fit is said to be that which minimizes the sum of the squared residuals between the points of the graph and the points of straight line. The least squares method is the most widely used procedure for developing estimates of the model parameters. The graph of the estimated regression equation for simple linear regression is a straight line approximation to the relationship between y and x. When regression equations obtained directly that is without taking deviation from actual or assumed mean then the two Normal equations are to be solved simultaneously as follows; For Regression Equation of x on y i. e. x=a+by The two Normal Equations are:- For Regression Equation of y on x i. e. y=a+bx The two Normal Equations are:- Remarks:- 1- It may be noted that both the regression coefficient ( x on y means bxy and y on x means byx ) cannot exceed 1. 2- Both the regression coefficient shall either be positive + or negative -. 3- Correlation coefficient (r) will have same sign as that of regression coefficient.
Friday, August 16, 2019
Culture refers to the norms, values and conceptions which influences an individualÃ¢â¬â¢s behavior. They are usually not tangible things though they greatly affect or influence the reactions or response of an individual to certain circumstances. Different communities have different cultures which are usually expressed through the various artifacts and symbols as well as ceremonies and traditions. The national culture of a place is usually expressed through the language spoken, the religion practiced, the etiquette and attitudes of the people, body language as well a literature, arts and music in such a country. The national culture of a country influences the way things and business are carried out and as such the performance of different entities within the country. Brazilian culture Brazil is located in the southern America and it is characterized by different and diverse culture which is as a result of cultural and ethnic mixing between the Africans, the native Americans and the Portuguese which occurred during the colonial era which. Other groups of people which have greatly influenced the culture of Brazil are the Spanish, Arabs, the Germans and the Italian immigrants who settled in Brazil between the 19th and the 20th century. This diverse nature of Brazilian people has given rise to a national culture which is so diverse. Portugal however was the major country which greatly influences the culture of Brazil since it was its colonizer. During the colonization period, the Brazilian people were having close contact with the Brazilians especially because Portuguese colonizers inhabited Brazil in large numbers. The slaves who were mostly black Africans also influenced greatly the formation of the Brazilian culture (Nava & Lauerhass, 2006). During the colonial period, the Portuguese wanted the Brazilians to be civilized and thus introduced Portuguese language as well as Catholicism. Portuguese is the most widely spoken language in Brazil although Spanish is also spoken in some parts. English is the second language which is spoken after Portuguese. However, the Brazilian Portuguese is different from Portuguese which is spoken in Portugal and other Portuguese speaking countries. The Brazilian Portuguese contains additional words which are coined from their native language. Most of the Brazilians can speak English though not frequently while a good number of them can hear and understand Spanish though they may not speak it. As mentioned above, Catholicism is widely practiced with most of the individuals thus being Christians. Brazil is one of the countries which have the largest number of catholic population although other beliefs like Hinduism, ayahuasca, spiritism, Judaism and Buddhism have evolved overtime. Other groups of Christianity like the Mormon Church, Methodism and Pentecostalism are also gaining root in Brazil. An annual religious celebration known as carnaval is held in Brazil for forty days and it is celebrated before Easter which marks the lent period (Thomas, 2007). The Brazilian music is composed mostly of traditional styles for example samba, frevo and forro among others. Brazil also has classical music which dates back to the 18th century. The music industry in Brazil is marked by diversity especially after Brazil become democratic in 1985 whereby hip hop music was largely adopted. Music in the past was largely influenced by social classes which existed between the rich, the middle class and the poor people. However, most of the traditional songs were neutral and did not favor any class thus unifying the country music industry. Another important feature of Brazilian culture is their literature which can be traced back to the 16th century. Portuguese explores during the colonial period wrote different poems, plays and chronicles describing Brazil. Brazilian writers started writing soon after independence in 1822 which marked the beginning of nativesÃ¢â¬â¢ prominence in literature. They also have a folk literature tradition although little of is known internationally. This folk literature is usually done by displaying verses in a booklet format which are hanged on the wall using strings in rhymed verses. This is common in the northeast region where illiteracy level is still high (Nava & Lauerhass, 2006). As mentioned above, carnival is one of the most celebrated events and acts as symbol of the Brazilian people. During this celebration, costumed dancers as well as musicians form parades both formal and even in the streets for a period of four days. This event is celebrated nationally with carnival symbolizing national ethos especially because it depicts the dualities of life of the Brazilians which is divided among the poverty and wealth, female and males and Europeans and Africans. Football is also another highly celebrated activity in Brazil. During major soccer matches like the world cup, all national attention is diverted to soccer with most of the people wearing clothes decorated with colors of their national flag (Garibaldi de Hilal, 2006). Brazilians unlike people in the North America have little sense especially of personal space when it comes to their etiquette. The Brazilians may be found in large and also crowded areas which do not bother them. Respect is usually accorded according to the dressing code of a person. To command respect, one thus has to wear appropriately to fit his or her class as dressing is used as a symbol of class. Also, these people tend to physically expressive and they convey some of their emotional information via touching. Touching in Brazil is translated to mean friendship or concern about the welfare of the other person. Women are more inclined to touching and kissing their fellow women as a sign of greetings while men usually pat or bear hug their male counterparts. People like doctors, professors and priests among other are addressed using their titles which is them followed by their first names. Body language is also used in Brazil and is usually varied depending on the social class or standing of an individual. Domestic or house servants greet their masters usually by a limp handshake while slightly bowing the head and lowering the eyes. They address their masters with respectful you (senhora) while masters address servants as voce. Graduates and other educated persons are addressed as doctor. The Brazilians are not bothered by nudity and this is verifiable through scanty dressing that is worn during carnival (Nava & Lauerhass, 2006). In Brazil, personal relationships are valued with body language being highly used while expressing emotions. Touching is one way of expressing concern, friendship and even interest on the other peopleÃ¢â¬â¢s point of view. People who tend to keep their distance while talking to their counterparts are usually considered to be cold and uninterested. Also the national language that is Portuguese is highly valued and even those who can speak English prefer speaking in their native Portuguese language. The Brazilians also value or regard highly their symbols which include the carnival and soccer (Garibaldi de Hilal, 2006). The national culture of a country affects in a great manner the running of the national affairs as well as the businesses. While carrying out business activities in an area, it is vital to understand the culture which the community holds as this would influence workers motivation and commitment to the business as well as the communityÃ¢â¬â¢s perception of the business. Apart from the expertise or experience of the workers and the managers, national culture contributes in largely to the growth or stagnation of a business and as such it should be treated carefully. Knowledge of the Brazilian culture would influence greatly how a business is to be carried out in this region. As mentioned above, personal relationship is very important to the Brazilians and as such, this would impact greatly to the way a business operates. While carrying out business in this region, it is vital for the managers to ensure that they create personal relationships with their workers as this would act as a motivation factor. Managers who keep their distance may be viewed as being cold or rude in Brazil and as such, understanding the culture of the Brazilians would help in managing and running a business successfully (Ferreira, et al, n. d). Brazilians also respect and adore their symbols which are mainly soccer and carnival celebrations. During this period, most of the Brazilians are committed to the celebrations and as such may not be willing to work as usual or for long hours. Understanding the value the Brazilians attach to these functions would influence how activities of a business are carried out. This is more so because these celebrations are nationally accepted as part of their culture. During the festive period, the business may be run fewer hours be closed till the festive seasons is over. Learning to value what the native Brazilians value would help in establishing an entity in this region and also earning the commitment of the workers to the business (Ferreira, et al, n. d). Conclusion For any business to be successful, it is vital to ensure that it observes and values the national culture in existence in a particular area. The culture of a community or a country determines the attitudes, behavior and response of the workers in an organization and as such, managers should ensure that they fully understand the national culture existing in a country as this is bound to influence not only the workers performance of tasks but also the running of the business. A company deemed to esteem the national culture is more likely to be successful that a company comprising of good management team but which does not respect or observe the national culture. Reference: Ferreira, M. C. et al (n. d): Organizational culture in Brazilian public and private companies. Retrieved on 2nd April 2009 from, http://ebooks. iaccp. org/ongoing_themes/chapters/ferreira/ferreira. php? file=ferreira&output=screen. Garibaldi de Hilal, A. V. (2006): Brazilian National Culture, Organizational Culture and Cultural Agreement. International Journal of Cross Cultural Management, Vol. 6 Nava, C. & Lauerhass, L. (2006): Brazil in the making: facets of national identity. ISBN 0742537579, Published by Rowman & Littlefield Thomas, V. (2007): Culture of BRAZIL. Retrieved on 2nd April 2009 from, http://www. everyculture. com/Bo-Co/Brazil. html.
Thursday, August 15, 2019