Human Rights and Business Ethics

Human Rights and Business Ethics The enthusiasm of corporate associations in human rights has expanded throughout the years because of the analysis and worries over the utilization of youngster work, low wages, female separation and misuse industrial facilities. Joining esteems and morals into any business has gotten critical to corporate associations, government, and the general population when all is said in done. As the world turns out to be ever littler because of globalization, there has been an expansion in the development of work, information and innovation from nation to nation. This has lead to organizations setting up manufacturing plants in nations with modest work and exceptionally poor human right laws so they can satisfy the need for their item. Administration of these poor nations have been compelled to move to the tune of enormous business. Business ethic developed because of the maltreatment of human rights and in view of the requirement for corporate association to be progressively moral and others conscious in working together. This has gone to the fore front in ongoing time with the media watching out for corporate associations that misuse or decline to up hold their social duties in any capacity. Because of this associations presently give more consideration to business ethic instruction and preparing so as to meet this regularly developing moral duty. The development and improvement of organizations worldwide has realized an expansion in the way of life yet then again it has brought about the maltreatment of laborers in numerous pieces of the world. Corporate social duty has enter another stage wherein the obligation of business must be obviously characterized. As indicated by Andrew chapman and Scott Jerbi there are developing desire that company ought to do everything their forces to advance general human rights principles even in strife circumstance where administration structure have separated. War on Want has distributed research which shows that Bangladeshi laborers making garments for Primark, Tesco and Asda work as long as 80 hours every week and procure as meager as a large portion of a living compensation. http://uk.oneworld.net/article/see 4/04/2010 War on Want senior battles official Simon McRae stated: â€Å"British organizations keep on submitting genuine human rights maltreatment over the world. However the administrations just reaction is to thought of deliberate activities which organizations are allowed to overlook. At the point when will clergymen make genuine move to hold these organizations to account?† For any commercial center to be viable there must be moral conduct with respect to purchasers and dealers. As per Solomon (1996) moral conduct with respect to the two purchasers and dealers is equivalent to the adequacy of the commercial center. Notwithstanding the level of the opposition, the effective working of the commercial center lay on the establishment of commonly tons of direct and shared intrigue. For the relationship to stay gainful to the two gatherings it must be of an incentive to them two. Untrustworthy conduct by either party upsets the relationship and produces trades that are both useless and inadequate (Morgan and Hunt, 1994) Diary of business morals: Sam fullerton, KatShleen B kerch,H Robert Dodge 805-814, 1996 II. Structure of the report The report is an emphasis on the retail fabric industry according to its business morals. As of late there has been bunches of issue in transit apparel retailers manage human right. Individuals feel that they are not doing what's needed to manage human right maltreatment universally. The report will cause to notice the difficulties looked by work as aftereffect of globalization and the requirement for an enduring arrangement through compelling corporate approaches and systems. Initially, the report will distinguish and explain companys obligations in the security of human rights, opportunity fromslavery and constrained work, opportunity from torment and debasing treatment. Which if not up held by any organization will harm its image picture and achieve lost certainty by clients. Different sections will chat on ongoing conversations on business morals and how purchasers see human right principles as respects utilization of items utilizing diaries, web, reports and so on. The point is to draw out the various speculations and perspectives by different creators for better understanding. In the second part which manages the writing audit it will concentrate on the different thoughts and hypotheses that discussions about the requirement for maintaining human right guidelines in the apparel business. The distinctive hypothetical methodologies will be examined in light of ongoing happenings for a vastly improved comprehension and furthermore help figure better business morals practice in the dress business. Contextual investigations, ongoing discoveries and current happenings will be managed in section three with connection to the different hypotheses as respects the material business. The back ground of conversation for the investigation will be taken from the different discoveries and the information gathered. From the examinations of various distributions shoppers have various perspectives on the work law as it relates with products, evaluating, and human rights principles. Utilizing the different speculations and rules that underline the contention the effect of business morals on globalization will examined in section four. The report will show that human right maltreatment in poor areas of the world are on the expansion in the attire business. It will likewise accentuation the significance of maintaining human rights for evenhandedness and security. The Final part will concentrate on the end and suggestions drawn from investigation of information gathered.

Journalism Is Art

News coverage Is Art Journalism is characterized as â€Å"writing that reflects shallow idea and research, a well known inclination, and rushed organization thought about as representing topical paper or mainstream magazine composing as recognized from researcher composing. † Art is characterized as â€Å"the quality, creation, articulation, or domain, as per stylish standards, of what is lovely, engaging, or of more than common essentialness. † So how are the two related? Reporting and workmanship are connected by definition as a result of two things. To begin with, they are connected in light of the fact that the two of them require shallow thought.Without imagination or a basic reasoning procedure the article won't be not quite the same as anybody else’s. What isolates the New York Times columnist from a school paper writer? It isn't simply pay. It is unadulterated experience and imagination. Any great composing requires imaginative reasoning. Each bit of comp osing is individualized by the character and imagination of the essayist Same with craftsmanship. On the off chance that everybody thought a similar way, at that point we wouldn’t have astounding canvases like the Mona Lisa by Leonardo Devinci or Starry Night by Vincent Van Gaugh that stands apart from your neighborhood artist.Each craftsman has various styles of painting. A model would be current workmanship and view craftsmanship. Each requires various fortifications in various regions of ability. Much the same as writers, one essayist may compose stunning sections however with regards to a hard news story they are not as solid. Besides news coverage and craftsmanship is connected by definition since the two of them have more than standard noteworthiness. Sylvia, who composes for the TAXI configuration organize cites, â€Å"When we are so profoundly moved by an encounter that we need to impart it to other people, we are the place workmanship starts. Craftsmanship shouldn't be â€Å"understood† or to be enjoyed.Like life itself, it can essentially be experienced. However the more we comprehend what craftsmanship can offer, the more extravagant our experience of it will be. † This announcement can be identified with news coverage. As a columnist, we expound on what moves us to share or educate others. Articles are not constantly written to be appreciated. They are some of the time used to break the most frightful news. These kinds of articles simply can just essentially be experienced. This is a piece of the craft of news coverage. It is a piece of life. Great news coverage just as great craftsmanship has sway on our life. An article may uncover secretes of the administration and ddress issues that we ought to know about in our locale. Craftsmanship impacts our life a similar way. The work of art La Maja Desnuda by Spanish painter Francisco Goya brought a lot of debate up in the late 1700’s. This canvas was one of the primary naked artistic creations portraying pubic hair on a lady. Goya was deprived of his situation of a Spanish court painter after this composition was uncovered. It affected individuals, much the same as news coverage. This semester I have had my first experience as a writer. I am taking a paper print class and composing for the school paper, The Bridge.When I initially began the class I did not understand what I was getting into. Tight cutoff times, various styles of articles, gathering data from at times non-willing sources, and the entire separate specialty of photojournalism were a stun to me. I see news-casting as a craftsmanship on account of understanding. Much the same as a work of art it requires some investment, innovative idea, and has various styles Many individuals contend that news coverage is a withering craftsmanship or not a workmanship by any stretch of the imagination. I can concur with the way that news coverage is a withering craftsmanship. Prior to TV and radio, paper pr int was the main method of coursing the news by some other means than expression of mouth.It is entirely different in this day and time. We currently have TV that have columnists report to us live news. A paper can not break the news live for its crowd. Papers are thinking that its harder to be effective in this day and time. On the opposite side of this contention, individuals have greater chance to compose as a columnist in light of web. It no longer ties us to neighborhood composing. An individual in Kentucky can compose an article for the New York Times and basically send it by email in the matter of seconds. A few people don't think news coverage is a workmanship since they have not experienced it for themselves.Just like me, before I encountered news coverage for myself I thought it was much the same as some other kind of composing. These individuals think reporting is antiquated and would much rather have their news conveyed to them by TV, bypassing perusing a genuine article since they need to be educated the least demanding way that could be available. They accept broadcast media is progressively precise and simpler to be understood. We have to spare the specialty of print reporting. When was the last time you seen a young person perusing a genuine print of the paper when they were not in it?I figure schools should make understudies read news papers to be educated regarding current issues in the network. This would better improve their understanding aptitudes and advance paper print. Reporting as a workmanship will possibly cease to exist on the off chance that we let it. Work Cited â€Å"Art† Dictionary. com Random House, Inc. February 13, 2013. â€Å"Journalism†. Word reference. com. Arbitrary House, Inc. February 13, 2013 Sylvia. â€Å"Visual Arts-More Than Ordinary Significance† designtaxi. com. TAXI configuration arrange August 16, 2005. Web February 3, 2013. â€Å"10 Most Famous Paintings ever. †touropia. com. Touropi a. October 30, 2010 Web. February 3, 2013 .

Essay Topics For Parable of the Sower - Important Essay Topic Ideas

Essay Topics For Parable of the Sower - Important Essay Topic IdeasFor students who are writing essays on the parable of the sower, it is good to find several essay topics in this area. The best parable essay topics will be those that delve into the basic concepts of the parable, such as its message, characters, or underlying theme.Content is also a key to a well-written essay. While a character can make for great subject matter for an essay, students should take note that they are not the only things students should focus on when crafting a sentence or paragraph. This is because a good story begins with the dialogue and leads to the characters.For example, a parable of the sower can take two likely main characters. However, students need to first consider how the characters interact. It is for this reason that they should think about the characters' roles in their own lives. To create a character who works at a daycare center, a student may want to place the narrator (the one who ge ts the facts) in a post office, a dentist, or a veterinarian.The more characters and roles the writer can place, the better the overall story will be. After all, when students start working on their essay, they will be looking for something that is both meaningful and helpful.Interest can also be a topic for the essay. Students should take note that the sower is a savior to the four Hebrew children who watched in awe as he pulled up his weeds. They then began to do work in order to help out their favorite sower. By doing so, they gave the man something of value.However, the man realized that without the crops, he would never be able to buy bread from the local bakery. In response, he planted the four children (the sower's) with vegetables.Thus, the main characters of the parable served as the basis for the children to help out their friend. Through their actions, they were given a means of food and shelter. Therefore, the subject matter is a good example of how to introduce a main c haracter and his importance to the parable.Parable of the sower essay topics can be quite varied. A student needs to be willing to brainstorm several ideas for essay topics and to consider the idea of developing a greater meaning through the main characters.

Regression Of Financial Techniques Example For Free - Free Essay Example

Sample details Pages: 14 Words: 4234 Downloads: 9 Date added: 2017/06/26 Category Finance Essay Type Analytical essay Did you like this example? The Pearson Correlation Coefficient (r) or correlation coefficient for short is a measure of the degree of linear relationship between two variables. While in regression the emphasis is on predicting one variable from the other, in correlation the emphasis is on the degree to which a linear model may describe the relationship between two variables. In regression the interest is directional, one variable is predicted and the other is the predictor; in correlation the interest is non-directional, the relationship is the critical aspect. Don’t waste time! Our writers will create an original "Regression Of Financial Techniques Example For Free" essay for you Create order The coefficient of correlation can vary from positive one (indicating a perfect positive relationship), through zero (indicating the absence of a relationship), to negative one (indicating a perfect negative relationship). As a rule of thumb, correlation coefficients between .00 and .30 are considered weak, those between .30 and .70 are moderate and coefficients between .70 and 1.00 are considered high. Correlation between NSE and FII Correlations FII NSE FII Pearson Correlation 1 .313** Sig. (2-tailed) .002 N 96 96 NSE Pearson Correlation .313** 1 Sig. (2-tailed) .002 N 96 96 **. Correlation is significant at the 0.01 level (2-tailed). The above table is showing the relationship among the NSE and FII which is taken from year Jan 2003 to Dec 2010. The Pearson correlation coefficient measures the linear association between two scale variables. The correlation reported in the table is 0.313. This suggests that NSE and FII are showing a weak positive relationship i.e. with the increase in FII, NSE indices increases and vice versa. Correlation between Sensex and FII Correlations FII SENSEX FII Pearson Correlation 1 .306** Sig. (2-tailed) .002 N 96 96 SENSEX Pearson Correlation .306** 1 Sig. (2-tailed) .002 N 96 96 **. Correlation is significant at the 0.01 level (2-tailed). The above table is showing the relationship among the Sensex and FII which is taken from year Jan 2003 to Dec 2010. The Pearson correlation coefficient measures the linear association between two scale variables. The correlation reported in the table is 0.306. This suggests that Sensex and FII are showing a weak positive relationship i.e. with the increase in FII, Sensex indices increases and vice versa. Correlation between Consumer Durables and FII Correlations FII CONSUMER DURABLES FII Pearson Correlation 1 .310** Sig. (2-tailed) .002 N 96 96 CONSUMER DURABLES Pearson Correlation .310** 1 Sig. (2-tailed) .002 N 96 96 **. Correlation is significant at the 0.01 level (2-tailed). The above table is showing the relationship among the Consumer Durables and FII which is taken from year Jan 2003 to Dec 2010. The Pearson correlation coefficient measures the linear association between two scale variables. The correlation reported in the table is 0.310. This suggests that Consumer Durables and FII are showing a weak positive relationship i.e. with the increase in FII, Consumer Durables indices increases and vice versa. Correlation between Capital Goods and FII Correlations FII Capital Goods FII Pearson Correlation 1 .265** Sig. (2-tailed) .009 N 96 96 Capital Goods Pearson Correlation .265** 1 Sig. (2-tailed) .009 N 96 96 **. Correlation is significant at the 0.01 level (2-tailed). The above table is showing the relationship among the Capital Goods and FII which is taken from year Jan 2003 to Dec 2010. The Pearson correlation coefficient measures the linear association between two scale variables. The correlation reported in the table is 0.265. This suggests that Capital Goods and FII are showing a weak positive relationship i.e. with the increase in FII, Capital Goods indices increases and vice versa. Correlation between FMCG and FII Correlations FII FMCG FII Pearson Correlation 1 .340** Sig. (2-tailed) .001 N 96 96 FMCG Pearson Correlation .340** 1 Sig. (2-tailed) .001 N 96 96 **. Correlation is significant at the 0.01 level (2-tailed). The above table is showing the relationship among the FMCG and FII which is taken from year Jan 2003 to Dec 2010. The Pearson correlation coefficient measures the linear association between two scale variables. The correlation reported in the table is 0.340. This suggests that FMCG and FII are showing a moderate positive relationship i.e. with the increase in FII, FMCG indices increases and vice versa. Correlation between Health Care and FII Correlations FII Health_Care FII Pearson Correlation 1 .375** Sig. (2-tailed) .000 N 96 96 Health_Care Pearson Correlation .375** 1 Sig. (2-tailed) .000 N 96 96 **. Correlation is significant at the 0.01 level (2-tailed). The above table is showing the relationship among the Health Care and FII which is taken from year Jan 2003 to Dec 2010. The Pearson correlation coefficient measures the linear association between two scale variables. The correlation reported in the table is 0.375. This suggests that Health Care and FII are showing a moderate positive relationship i.e. with the increase in FII, Health Care indices increases and vice versa. Correlation between IT and FII Correlations FII IT FII Pearson Correlation 1 .337** Sig. (2-tailed) .001 N 96 96 IT Pearson Correlation .337** 1 Sig. (2-tailed) .001 N 96 96 **. Correlation is significant at the 0.01 level (2-tailed). The above table is showing the relationship among the IT and FII which is taken from year Jan 2003 to Dec 2010. The Pearson correlation coefficient measures the linear association between two scale variables. The correlation reported in the table is 0.337. This suggests that IT and FII are showing a moderate positive relationship i.e. with the increase in FII, IT indices increases and vice versa. Linear Regression Regression between NSE FII Variables Entered/Removedb Model Variables Entered Variables Removed Method 1 FIIa . Enter a. All requested variables entered. b. Dependent Variable: NSE Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .313a .098 .088 1449.98694 a. Predictors: (Constant), FII ANOVAb Model Sum of Squares df Mean Square F Sig. 1 Regression 2.146E7 1 2.146E7 10.205 .002a Residual 1.976E8 94 2102462.122 Total 2.191E8 95 a. Predictors: (Constant), FII b. Dependent Variable: NSE Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 3157.700 167.700 18.829 .000 FII .062 .019 .313 3.195 .002 a. Dependent Variable: NSE The above Regression is between NSE and FII the above tables are showing R, the multiple correlation coefficient, is the linear correlation between the observed and model-predicted values of the dependent variable. Its large value indicates a strong relationship. R is 0.313 that is showing strong correlation between NSE and FII and also R Square, the coefficient of determination, is the squared value of the multiple correlation coefficient. R ² which is 0.098 that is 10% of the variations are showing by this model. The significance value of the F statistic is less than 0.05, which means that the variation explained by the model is not due to chance. The ANOVA table is a useful test of the models ability to explain any variation in t he dependent variable; it does not directly address the strength of that relationship. Regression between Sensex FII Variables Entered/Removedb Model Variables Entered Variables Removed Method 1 FIIa . Enter a. All requested variables entered. b. Dependent Variable: SENSEX Model Summaryb Model R R Square Adjusted R Square Std. Error of the Estimate 1 .306a .094 .084 4976.73956 a. Predictors: (Constant), FII b. Dependent Variable: SENSEX ANOVAb Model Sum of Squares df Mean Square F Sig. 1 Regression 2.409E8 1 2.409E8 9.727 .002a Residual 2.328E9 94 2.477E7 Total 2.569E9 95 a. Predictors: (Constant), FII b. Dependent Variable: SENSEX Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 10493.779 575.591 18.231 .000 FII .208 .067 .306 3.119 .002 a. Dependent Variable: SENSEX The above Regression is between Sensex FII the above tables are showing R, the multiple correlation coefficient, is the linear correlation between the observed and model-predicted values of the dependent variable. Its large value indicates a strong relationship. R is 0.306 that is showing strong correlation between Sensex FII and also R Square, the coefficient of determination, is the squared value of the multiple correlation coefficient. R ² which is 0.094 that is 10% of the variations are showing by this model. The significance value of the F statistic is less than 0.05, which means that the variation explained by the model is not due to chance. The ANOVA table is a useful test of the models ability to explain any variation in the dependent variable; it does not directly address the strength of that relationship. Regression between Consumer Durables FII Variables Entered/Removedb Model Variables Entered Variables Removed Method 1 FIIa . Enter a. All requested variables entered. b. Dependent Variable: CONSUMER_DURABLES Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .310a .096 .086 1535.08070 a. Predictors: (Constant), FII ANOVAb Model Sum of Squares df Mean Square F Sig. 1 Regression 2.351E7 1 2.351E7 9.976 .002a Residual 2.215E8 94 2356472.743 Total 2.450E8 95 a. Predictors: (Constant), FII b. Dependent Variable: CONSUMER_DURABLES Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 2636.743 177.542 14.851 .000 FII .065 .021 .310 3.159 .002 a. Dependent Variable: CONSUMER_DURABLES The above Regression is between Consumer Durables FII the above tables are showing R, the multiple correlation coefficient, is the linear correlation between the observed and model-predicted values of the dependent variable. Its large value indicates a strong relationship. R is 0.310 that is showing strong correlation between Consumer Durables FII and also R Square, the coefficient of determination, is the squared value of the multiple correlation coefficient. R ² which is 0.096 that is 10% of the variations are showing by this model. The significance value of the F statistic is less than 0.05, which means that the variation explained by the model is not due to chance. The ANOVA table is a useful test of the models a bility to explain any variation in the dependent variable; it does not directly address the strength of that relationship. Regression between Capital Goods FII Variables Entered/Removedb Model Variables Entered Variables Removed Method 1 FIIa . Enter a. All requested variables entered. b. Dependent Variable: Capital_Goods Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .265a .070 .060 5141.56855 a. Predictors: (Constant), FII ANOVAb Model Sum of Squares df Mean Square F Sig. 1 Regression 1.877E8 1 1.877E8 7.101 .009a Residual 2.485E9 94 2.644E7 Total 2.673E9 95 a. Predictors: (Constant), FII b. Dependent Variable: Capital_Goods Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 7531.033 594.654 12.665 .000 FII .184 .069 .265 2.665 .009 a. Dependent Variable: Capital_Goods The above Regression is between Capital Goods FII the above tables are showing R, the multiple correlation coefficient, is the linear correlation between the observed and model-predicted values of the dependent variable. Its large value indicates a strong relationship. R is 0.265 that is showing strong correlation between Capital Goods FII and also R Square, the coefficient of determination, is the squared value of the multiple correlation coefficient. R ² which is 0.070 that is 7% of the variations are showing by this model. The significance value of the F statistic is less than 0.05, which means that the variation explained by the model is not due to chance. The ANOVA table is a useful test of the models ability to exp lain any variation in the dependent variable; it does not directly address the strength of that relationship. Regression between FMCG FII Variables Entered/Removedb Model Variables Entered Variables Removed Method 1 FIIa . Enter a. All requested variables entered. b. Dependent Variable: FMCG Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .340a .116 .106 734.24192 a. Predictors: (Constant), FII ANOVAb Model Sum of Squares df Mean Square F Sig. 1 Regression 6630011.310 1 6630011.310 12.298 .001a Residual 5.068E7 94 539111.190 Total 5.731E7 95 a. Predictors: (Constant), FII b. Dependent Variable: FMCG Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 1718.599 84.920 20.238 .000 FII .035 .010 .340 3.507 .001 a. Dependent Variable: FMCG The above Regression is between FMCG FII the above tables are showing R, the multiple correlation coefficient, is the linear correlation between the observed and model-predicted values of the dependent variable. Its large value indicates a strong relationship. R is 0.340 that is showing strong correlation between FMCG FII and also R Square, the coefficient of determination, is the squared value of the multiple correlation coefficient. R ² which is 0.116 that is 12% of the variations are showing by this model. The significance value of the F statistic is less than 0.05, which means that the variation explained by the model is not due to chance. The ANOVA table is a useful test of the models ability to explain any variation in the d ependent variable; it does not directly address the strength of that relationship. Regression between Health Care FII Variables Entered/Removedb Model Variables Entered Variables Removed Method 1 FIIa . Enter a. All requested variables entered. b. Dependent Variable: Health_Care Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .375a .141 .132 1132.37039 a. Predictors: (Constant), FII ANOVAb Model Sum of Squares df Mean Square F Sig. 1 Regression 1.976E7 1 1.976E7 15.409 .000a Residual 1.205E8 94 1282262.700 Total 1.403E8 95 a. Predictors: (Constant), FII b. Dependent Variable: Health_Care Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 3185.402 130.966 24.322 .000 FII .060 .015 .375 3.925 .000 a. Dependent Variable: Health_Care The above Regression is between Health Care FII the above tables are showing R, the multiple correlation coefficient, is the linear correlation between the observed and model-predicted values of the dependent variable. Its large value indicates a strong relationship. R is 0.375 that is showing strong correlation between Health Care FII and also R Square, the coefficient of determination, is the squared value of the multiple correlation coefficient. R ² which is 0.141 that is 14% of the variations are showing by this model. The significance value of the F statistic is less than 0.05, which means that the variation explained by the model is not due to chance. The ANOVA table is a useful test of the models ability to explain any variation in the dependent variable; it does not directly address the strength of that relationship. Regression between IT FII Variables Entered/Removedb Model Variables Entered Variables Removed Method 1 FIIa . Enter a. All requested variables entered. b. Dependent Variable: IT Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .337a .114 .104 1334.92982 a. Predictors: (Constant), FII ANOVAb Model Sum of Squares df Mean Square F Sig. 1 Regression 2.150E7 1 2.150E7 12.065 .001a Residual 1.675E8 94 1782037.614 Total 1.890E8 95 a. Predictors: (Constant), FII b. Dependent Variable: IT Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 3256.374 154.393 21.091 .000 FII .062 .018 .337 3.473 .001 a. Dependent Variable: IT The above Regression is between IT FII the above tables are showing R, the multiple correlation coefficient, is the linear correlation between the observed and model-predicted values of the dependent variable. Its large value indicates a strong relationship. R is 0.337 that is showing strong correlation between IT FII and also R Square, the coefficient of determination, is the squared value of the multiple correlation coefficient. R ² which is 0.114 that is 11% of the variations are showing by this model. The significance value of the F statistic is less than 0.05, which means that the variation explained by the model is not due to chance. The ANOVA table is a useful test of the models ability to explain any variation in the depend ent variable; it does not directly address the strength of that relationship. Granger Causality Correlation does not necessarily imply causation in any meaningful sense of that word. The econometric graveyard is full of magnificent correlations, which are simply spurious or meaningless. Interesting examples include a positive correlation between teachers salaries and the accident rate in the city. Economists debate correlations which are less obviously meaningless. The Granger (1969) approach to the question of whether causes is to see how much of the current can be explained by past values of and then to see whether adding lagged values of can improve the explanation. is said to be Granger-caused by if helps in the prediction of , or equivalently if the coefficients on the lagged s are statistically significant. Note that two-way causation is frequently the case; Granger causes and Granger causes . It is important to note that the statement Granger causes does not imply that is the effect or the result of . Granger causality measures precedence and information conten t but does not by itself indicate causality in the more common use of the term. Granger Causality test between FII and Sensex Pairwise Granger Causality Tests Date: 03/06/11 Time: 17:53 Sample: 1 96 Lags: 2   Null Hypothesis: Obs F-Statistic Prob. Â  SENSEX_RETURN does not Granger Cause FII   94   0.17300 0.8414   FII does not Granger Cause SENSEX_RETURN   0.89225 0.4134 This shows influence of FII inflow on Indian Stock Market. The probability in all the above tests is more than 0.05 at which you can reject the null hypothesis. The above table shows that there is cause and effect relationship between Sensex and Net FII because the probability is greater than 0.05 thus FII investment patterns affects the Sensex. This relationship is also depicted when during Jan 08 to Feb 09 FII net sales were for Rs. 58.751.70 Crore and as a result Sensex fell from 17648.71 in Jan 08 to 8891.61 in Feb 09, i.e. a drop of 8757.10 which was approximately 49% in just over a year. Granger Causality test between FII and NSE Pairwise Granger Causality Tests Date: 03/06/11 Time: 21:11 Sample: 1 96 Lags: 2   Null Hypothesis: Obs F-Statistic Prob. Â  NSE_RETURN does not Granger Cause FII   94   0.05355 0.9479   FII does not Granger Cause NSE_RETURN   0.45150 0.6381 This shows influence of FII inflow on Indian Stock Market. The probability in all the above tests is more than 0.05 at which you can reject the null hypothesis. The above table shows that there is cause and effect relationship between NSE and Net FII because the probability is greater than 0.05. Thus, FII investment patterns affect the NSE. This relationship is also depicted when during Jan 08 to Feb 09 FII net sales were for Rs. 58.751.70 Crore and as a result NSE fell from 5137.45 in Jan 08 to 2763.65 in Feb 09, i.e. a drop of 2373.80 which was approximately 46% in just over a year. Granger Causality test between FII and BSE Consumer Durables Pairwise Granger Causality Tests Date: 03/06/11 Time: 17:54 Sample: 1 96 Lags: 2   Null Hypothesis: Obs F-Statistic Prob. Â  CONSUMER_DURABLES_RETURN does not Granger Cause FII   94   0.30374 0.7388   FII does not Granger Cause CONSUMER_DURABLES_RETURN   0.93166 0.3977 This shows influence of FII inflow on Indian Stock Market. The probability in all the above tests is more than 0.05 at which you can reject the null hypothesis. The above table shows that there is cause and effect relationship between BSE Consumer Durables and Net FII because the probability is greater than 0.05. Thus, FII investment patterns affect the BSE Consumer Durables. This relationship is also depicted when during Jan 08 to Feb 09 FII net sales were for Rs. 58.751.70 Crore and as a result BSE Consumer Durables fell from 5103.86 in Jan 08 to 1542.67 in Feb 09, i.e. a drop of 3561.19 which was approximately 70% in just ov er a year. Granger Causality test between FII and BSE Capital Goods Pairwise Granger Causality Tests Date: 03/06/11 Time: 17:55 Sample: 1 96 Lags: 2   Null Hypothesis: Obs F-Statistic Prob. Â  CAPITAL_GOODS_RETURN does not Granger Cause FII   94   0.24639 0.7821   FII does not Granger Cause CAPITAL_GOODS_RETURN   0.11010 0.8959 This shows influence of FII inflow on Indian Stock Market. The probability in all the above tests is more than 0.05 at which you can reject the null hypothesis. The above table shows that there is cause and effect relationship between BSE Capital Goods and Net FII because the probability is greater than 0.05. Thus, FII investment patterns affect the BSE Capital Goods. This relationship is also depicted when during Jan 08 to Feb 09 FII net sales were for Rs. 58.751.70 Crore and as a result BSE Capital Goods fell from 16387.70 in Jan 08 to 5897.92 in Feb 09, i.e. a drop of 10489.78 which is approximately 64% in just over a year. Granger Causality test between FII and BSE FMCG Pairwise Granger Causality Tests Date: 03/06/11 Time: 17:55 Sample: 1 96 Lags: 2   Null Hypothesis: Obs F-Statistic Prob. Â  FMCG_RETURN does not Granger Cause FII   94   0.08588 0.9178   FII does not Granger Cause FMCG_RETURN   2.04411 0.1355 This shows influence of FII inflow on Indian Stock Market. The probability in all the above tests is more than 0.05 at which you can reject the null hypothesis. The above table shows that there is cause and effect relationship between BSE FMCG and Net FII because the probability is greater than 0.05. Thus, FII investment patterns affect the BSE FMCG. This relationship is also depicted when during Jan 08 to Feb 09 FII net sales were for Rs. 58.751.70 Crore and as a result BSE FMCG fell from 2167.34 in Jan 08 to 2043.26 in Feb 09, i.e. a drop of only 124.08 which is approximately 6% in over a year. Granger Causality test between FII and BSE Health Care Pairwise Granger Causality Tests Date: 03/06/11 Time: 17:56 Sample: 1 96 Lags: 2   Null Hypothesis: Obs F-Statistic Prob. Â  HEALTH_CARE_RETURN does not Granger Cause FII   94   0.40226 0.6700   FII does not Granger Cause HEALTH_CARE_RETURN   1.34690 0.2653 This shows influence of FII inflow on Indian Stock Market. The probability in all the above tests is more than 0.05 at which you can reject the null hypothesis. The above table shows that there is cause and effect relationship between BSE Health Care and Net FII because the probability is greater than 0.05. Thus, FII investment patterns affect the BSE Health Care. This relationship is also depicted when during Jan 08 to Feb 09 FII net sales were for Rs. 58.751.70 Crore and as a result BSE Health Care fell from 3603.52 in Jan 08 to 2597.00 in Feb 09, i.e. a drop of 1006.52 which is approximately 27% in just over a year. Granger Causality test between FII and BSE IT Pairwise Granger Causality Tests Date: 03/06/11 Time: 17:56 Sample: 1 96 Lags: 2   Null Hypothesis: Obs F-Statistic Prob. Â  IT_RETURN does not Granger Cause FII   94   0.15074 0.8603   FII does not Granger Cause IT_RETURN   2.36452 0.0999 This shows influence of FII inflow on Indian Stock Market. The probability in all the above tests is more than 0.05 at which you can reject the null hypothesis. The above table shows that there is cause and effect relationship between BSE IT and Net FII because the probability is greater than 0.05. Thus, FII investment patterns affect the BSE IT. This relationship is also depicted when during Jan 08 to Feb 09 FII net sales were for Rs. 58.751.70 Crore and as a result BSE IT fell from 2096.17 in Feb 09, i.e. a drop of 1613.94 which is approximately 43% in just over a year. FINDINGS, SUGGESTIONS AND CONCLUSION The findings Suggestions of the research are: All the dependent variables taken for the research i.e. Sensex, NSE, BSE capital goods, BSE consumer durables, BSE FMCG, BSE Health Care BSE IT have shown positive correlation with FII equity investment patterns i.e. with the increase in FII, Various Stock indices also increases and vice versa. From the data we can observe, worst bearish phase was from Jan 08 to Feb 09. During this phase FII net sales was for Rs. 58.751.70 Crore and as a result of such withdrawals: Sensex fell from 17648.71 in Jan 08 to 8891.61 in Feb 09, i.e. a drop of 8757.10 which was approximately 49% in just over a year. NSE fell from 5137.45 in Jan 08 to 2763.65 in Feb 09, i.e. a drop of 2373.80 which was approximately 46% in just over a year. BSE Consumer Durables fell from 5103.86 in Jan 08 to 1542.67 in Feb 09, i.e. a drop of 3561.19 which was approximately 70% in just over a year. BSE Capital Goods fell from 16387.70 in Jan 08 to 5897.92 in Feb 09, i.e. a drop of 10489.78 which is approximately 64% in just over a year. BSE FMCG fell from 2167.34 in Jan 08 to 2043.26 in Feb 09, i.e. a drop of only 124.08 which is approximately 6% in over a year. BSE Health Care fell from 3603.52 in Jan 08 to 2597.00 in Feb 09, i.e. a drop of 1006.52 which is approximately 27% in just over a year. BSE IT fell from 3710.11 in Jan 08 to 2096.17 in Feb 09, i.e. a drop of 1613.94 which is approximately 43% in just over a year. BSE FMCG and BSE Health Care have shown the most resistance to FII withdrawals, this is due to the fact that both of these sectors are Defensive Sectors, they have a low Beta. Besides FII Other Macroeconomic variables like inflation, Govt. policies etc also affect the various stock market indices. CONCLUSION In developing countries like India foreign capital helps in increasing the productivity of labour and to build up foreign exchange reserves to meet the current account deficit. Foreign Investment provides a channel through which country can have access to foreign capital. This research helps to find out empirical relationship among FII equity investments and stock market indices. According to Data analysis and findings, it can be concluded that FII do have significant impact on the Indian Stock Market but there are other factors like government policies, budgets, inflation, economical and political condition, etc. do also have an impact on the Indian stock market. There is a positive correlation between various stock indices and FIIs i.e. with increase in FIIs investment, various stock indices also increases and vice versa. Retail investors can also keep a watch at FIIs investment data and derive benefit from it; since FIIs have better exposure to market informations than ret ail investors. FIIs also results in increased volatility in stock markets. FIIs have their advantages as well as disadvantages; Govt. needs to regulate FIIs so as to reduce their impact on stock markets and should try to develop domestic sources of funds to enhance growth. REFRENCES Bose Suchismita and Coondoo Dipaankar (2005): The Impact of FII Regulations in India, Journal: International Journal of financial market trends. Vol 30. Publisher: MCB UP Ltd Chakrabarti (2001), Journal: Journal of foreign institution investments Vol 27. Publisher: SSRN Group Publishing Limited Khan, Mohd. Amir; Goyal, Siddarth; Ranjan, Vinit; Agrawal, Gaurav; Investigation of Causality between FIIs Investment and Stock Market Returns, International Research Journal of Finance and Economics, Issue 40, 2010. Batra, Amita; The dynamics of foreign portfolio inflows equity returns in India, Indian council for research on international economic relations, wp109, September 2003. Bansal, Anand Pasricha, J.S.; Foreign institutional investors impact on stock prices in India, Journal of academic research in economics, Vol. 1 No. 2, October 2009 S.S.S Kumar, Role of Institutional Investors in Indian Stock Market, International Journal of Management Practices Contemporary Thoug hts. Rajkumar Gupta, Hariom; FIIs flows to India: Economic Indicators, SCMC journal of Indian management, January-March 2010. Trivedi Nair, and Agarwal, Chakrabarti (2003), Journal: International Journal of foreign money supply Management, Vol: 19. Publisher: MCB UP Ltd. Prasanna, P. Krishna; Foreign Institutional Investors: Investment Preferences in India, JOAAG, Vol. 3. No. 2, 2008 Saraogi, Ravi; Determinants of FII Inflows: India, Munich Personal RePEc Archive (MPRA), February 2008. Bose, S. Coondoo, D.; The impact of FII regulations in India: A time series intervention analysis of equity flows, ICRA Bulletin, July-Dec 04. https://www.ibef.org/economy/foreigninvestors.aspx https://www.citeman.com/4005-fiis-and-their-impact-on-indian-stock-market/ https://www.sebi.gov.in/workingpaper/stock.pdf

The Obesity Of Childhood Obesity - 894 Words

Up until the late 1990s, seeing an obese child was extremely abnormal because children’s main form of entertainment was playing outside. The rate of childhood obesity drastically increased due to the fact that children’s main form of entertainment has shifted from outdoor activities, to vast outlets of easily accessible technology. Children are also being served a variety of unhealthy meals from fast food restaurants, such as McDonald’s or Taco Bell. Unfortunately, most parents do not know the underlying truth about what they are feeding their children and often choose the cheapest route for feeding their families. Research indicates that the corpulence of today’s youth is becoming severely problematic, and drastic steps are being taken to solve the obesity concern in adolescents. Michelle Obama, who is a known advocate of the fight against childhood obesity, is using her resources as the First Lady to help remedy this situation. Obesity is only a symptom of a worse disease, being a slave to food. (L. 2). Research used to write the journal â€Å"Pregnancy, Delivery, and Childhood Obesity† signifies that â€Å"†¦ over 12% of children age 2-5 are considered obese, more than double the percentage (5.0%) occurring from 1976 – 1980† (qtd. In Squibb 73). In 2010, the Lets Move campaign launched, helping to change the lives of many children in need (â€Å"Michelle Obama†¦Ã¢â‚¬  44). Michelle initiated the movement focusing on four pillars: â€Å"Spread the number of healthy schools in this country,Show MoreRelatedChildhood Obesity : Obesity And Obesity Essay1671 Words   |  7 PagesFight to End Obesity Childhood obesity has increased drastically over the past years and has become a health risk to children. In fact, childhood obesity has doubled in numbers in the past thirty years (Childhood Obesity Facts). Obesity occurs when an individual becomes overweight and can be diagnosed by using the body mass index or BMI scale. 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Effects of John Brown’s Raid On Northern-southern Relations Free Essays

John Brown’s raid of the federal armory at Harpers Ferry, Virginia involved only a few abolitionists, freed no slaves, and ended after only two short days. Brown’s initial idea was that after raiding the federal armory slaves would rise up and rebel against their owners, not only in the north but eventually in the south. This was a radical idea, and although his raid was primarily condemned in the north, Brown became a hero. We will write a custom essay sample on Effects of John Brown’s Raid On Northern-southern Relations or any similar topic only for you Order Now Southerners became offended when in the years following Brown’s raid northerners felt compassion and even regarded him as a hero. The southerners however felt that he wanted to cause upheaval in the south. The issue however united the north for the cause of abolishing slavery. †Congress can contribute much to avert [southern withdrawal from the Union] by proposing†¦ an explanatory amendment of the Constitution on the subject of slavery†¦Ã¢â‚¬  (Doc G) The Northern view of John Brown had changed drastically in the years leading up to the civil war. Initially John Brown was viewed as an irrational for his actions in Pottawatomie, Kansas. It was in Pottawatomie where Brown and a few colleagues took violent measures of vengeance against five pro-slavery southerners in Response to the Bleeding Kansas crisis. The northern view of Brown changed however after his 1859 raid on Harpers Ferry, Virginia. The northern people did not immediately view him as a hero however. Many northerners viewed his raid as â€Å"utterly mistaken and, in its direct consequences, pernicious†. (Doc A) Southern people viewed Brown’s raid as a commotion and an appeal to rebellion. The previous Bleeding Kansas crisis also pushed the south more towards succession. It was by delegates chosen by the several states†¦ that the Constitution of the United States was framed in 1787 and submitted to the several states for ratification†¦ that of a compact between independent states. † (Doc H) President Lincoln responded â€Å"Having never been States, either in substance, or in name, outside of the Union, whence this magical omnipotence of ‘States Rights’, asserting a claim of power to lawfully destroy the Union itself? † (Doc I). Both of these statements were made in 1861, and clearly represent the division that sent our nation to war. While the years progressed the northern view of John Brown became increasingly more positive, people began to view Brown as a hero, as well as a martyr. Many believed while what he did was irrational and fanatical at the time, he paved the way for many northerners to become decided on the topic of abolition. John Brown’s raid ultimately made the Northern-southern relations even more strained, but caused the north to band together and fight against slavery and succession. In conclusion, the raid on Harpers Ferry, Virginia pushed the North and the south farther apart, but was a small step to becoming the free country that America is today. How to cite Effects of John Brown’s Raid On Northern-southern Relations, Essay examples

Mcdonaldization of Olympics Case free essay sample

McDonaldization of Olympics case Im going to analyse this case because I want to understand how this process of McDonaldization is affecting the Olympic games in his traditions and whos deciding what happens on the competitions in considerations of scheduling times and events broadcasting. Why is it so important for NBC to put the events in prime time for the United States ? And how can the will of â€Å"one big company† decide over many others entities that are involved in the Olympics ? But first a brief description of what McDonaldization is: Process of rationalization, albiet taken to extreme levels. Rationalization is a sociological term that simply means the substitution of logically consistent rules for traditional (or illogical) rules. One of the fundamental aspects of McDonaldization is that almost any task can (and should) be rationalized. † (Stewart Clegg 2004) NBC influenced the decision of IOC ( International Olympic Committee ) IOC decision was dictated by money. We will write a custom essay sample on Mcdonaldization of Olympics Case or any similar topic specifically for you Do Not WasteYour Time HIRE WRITER Only 13.90 / page The athletes were not use to a morning competition and many of them complained about the choice made. But the NBCs money invested in the broadcasting of the events played a major role in deciding that some events had to be shown to Americans in a prime time during the day. After all more than 50% of the revenue of the Olympic committee was paid by the American broadcasting channel. Obviously all this NBCs effort to have the better broadcasting times is for a very good reason, having the most of the audience watching during that hours means that the broadcasting giant can sell many Ad spots during those times and that more people are going to watch them. And they also have had a tradition that they have to carry with the Olympic games as said in the NBC website: NBC has held the American broadcasting rights of the Summer Olympics since the 1988 games and the broadcasting rights to the Winter Olympics since the 2002 games. ( nbcolympics. com 2009). Broadcasting the Olympics in the US is just good for their image and reputation. But is it good for the reputation of the Olympics ? Is this an example of globalization ? Also, is it good for the reputation of the Olympics ? Here we analyse some key points of globalization: The worldwide integration in virtually every sphere achieved principally through markets †¢ A process whereby the world becomes more interconnected and the fates of those people and organizations in it become more intertwined. †¢ In business terms, globalization means business without frontiers, crossing national boundaries, and dealing with the world, not just the home base. (Stewart Clegg 2004) As said in the textbook one of the key points of globalization is to cross national boundaries and dealing with the world, but this is not happening between the NBC and IOC for the Olympics. The interest is made only for a specific nation, which has more capital invested and makes an illogical decision for the athletes and for audience around the world, but which is logical in the strategic plan of the interested company. ( In the case of the swimming final times , Olympics Beijing 2008 ). We see a Globalization of the Olympic games that tends to go more towards the favour of the US which brings most of the revenue for the IOC, not only with the NBC channel but also with other private companies that add a big portion of the money to the lot and therefore have to be considered by the organizing association when making decisions of that kind ( time of events ). ( D. Jones 2012) The price for all this is being paid by countries that dont have much influence in the committee decisions and have to cope with crazy times and a big amount of ads to cover the costs of the broadcasting. What is the problem? Is the IOC doing something wrong? Are they focusing their attention on the biggest investor of the event just to not lose the large amount of revenues that this companies bring? And if so how can this be changed and what is the management issue? Why can NBC really shape and manage parts of a big event like the Olympics ? The main issue that we find in the managing choice of the IOC is the hegemony of power enforced by the main investors. Some people may rile against the commercialization or Americanization of the Olympics but figures show that the dollars from the US is critical for the sustenance of the Olympic movement. Besides TV, the IOC’s another major stream of income is private partnership. †( D. Jones 2012) On the NBC side, it was a very smart move that took place a while ago during the cold war, when USA used the Olympics to prove the supremacy over the USSR. Its not only about broadcasting the games in their own country, but also getting th e visibility globally as the main protagonists of the global event. All this income from the US for the committee is vital to keep the games happening, the big problem now days is that the structure of the Olympics is entirely based on big companies paying â€Å"the bills† for the massive costs that have to be covered to organize, manage and built facilities and events for the games. So from a IOCs managing perspective the choice of keeping happy major investors makes sense and it wouldnt be so criticized if it was a little less against the Olympic spirit. Athletes being forced to race at early morning hours by McDonald’s, Coca-Colas etc ads is not really what the spirit of the event should be. But to make everything happen, someone has to pay for everything that we see during races, competition, games and ceremonies. The Olympic committee has to accept some compromises to keep this a reality. As a solution to this, it is not very easy to come up with one, seen that if IOC loses the economic support from big American investors the Games will struggle to tackle the huge amount of money needed to make it happen. Conclusions: In recent times the US has lost multiple bids to bring the Olympic games back in their country, due to the conflict between the share that the USOC ( United States Olympic Committee ) and the IOC get from investments in the event. IOC decided to reject all the bids from US states to host the games, sometimes with humiliating results like the bid for Chicago 2016 that was rejected first round. We have a conflict of interests between the two organizations, that needed to be solved. This happened with a new revenue sharing model in 2012 that will probably help to bring the games back to the US in the near future. NBC has also renewed the contract with IOC for broadcasting Olympic Games until 2020, that means that despite the US taking control over the games, IOC hasnt found a different source of income big enough to say no to the American company. ( nbcolympic. com 2012 ) References Billings, Andrew C (2008) Olympic media : Inside the biggest show on television, London: Routledge , pp. 120-125. Dow Jones (2012) McDonaldization of Olympics, Factiva, pp. 1-2 [Online]. (Accessed: 29th March 2013). Gough, Paul J (2008) NBC: Olympic viewers dive in, Hollywood Reporter,406(00183660), pp. -14. G. Hayes J. Karamichas (2010) Olympic Games, Mega-Events and Civil Societies Globalization, Environment, Resistance. Social Sciences Collection 2012 [Online]. Available at: http://www. palgraveconnect. com. ezproxy. uow. edu. au/pc/doifinder/10. 1057/9780230359185 (Accessed: 1st April 2013). RICHARD SANDOMIR (2003) OLYMPICS; NBCs Olympic Run Is Extended to 2012 With $2 Billion Bid, Available at: http://www. n ytimes. com/2003/06/07/sports/olympics-nbc-s-olympic-run-is-extended-to-2012-with-2-billion-bid. html (Accessed: 1st April 2013). RICHARD SANDOMIR (2012) NBC Is Looking for Big Payoff on Olympics, Available at: http://www. nytimes. com/2012/02/13/sports/olympics/nbc-is-looking-for-big-payoff-on-olympics. html? _r=0 (Accessed: 27th March 2013). Stewart Clegg, Martin Kornberger, Tyrone Pitsis (2004) MANAGING ORGANIZATIONS an introduction to theory practice, 3rd edn. , London, California, Singapore, New Delhi: SAGE Pubblications. Szalai, Georg ; Guthrie, Marisa (2011) NBC Olympics: Who Wins, Hollywood Reporter, 417(00183660), pp. 11-12. William W. Kelly (2011) East Asian Olympics, Beijing 2008, and the globalisation of sport,History of sport,28(16), pp. 2261-2270. (2007). What Is McDonaldization?. Available: http://www. mcdonaldization. com/whatisit. shtml. Last accessed 27th April 2013. (2009). Olympics on NBC. Available: http://www. nbcolympics. com/. Last accessed 20th April 2013. (2009) IOC Rejects the EBU Bid for 2014-16 Olympic Games Broadcast Rights, The International Sports Law Journal, No. 1-2(), pp. 67-82 [Online]. Available at:http://www. questia. com/library/1G1-249053666/ioc-rejects-the-ebu-bid-for-2014-16-olympic-games (Accessed: 27th March 2013).