ASSIGNMENT 4 Essay Example | Topics and Well Written Essays - 1000 words

ASSIGNMENT 4 - Essay Example The region above 75 miles of height is considered as highland. As kerala receives plenty of sunlight, it belongs to the hot climatic zone of the earth. Because of the nearness to sea most of the places have a humid condition. But some places in the eastern part of the state experiences moderate hot and cold weather conditions. The temperature will be low in thise places which are more than 1000m altitude. Therefore, these area are suitable for the cultivation of garden crops like cardamom, coffee and tea. The midland of kerala is a chain of hills and fields in between. The rain water which falls on hills is stored in the fields. A part of this forms the ground water. The remaining flows as streamlets. Kerala is one of the most loved tropical paradises, which boasts some of the richest biodiversity in the world. The climate here is more humid wetter. This part contains wet green forest and most complex and species rich vegetation. The rivers on Kerala have their origin in the ranges o f western Ghats , these rivers quickly drain to the Lakshwadweep sea. Owing to this, the rivers which are flooded during the rainy season become more channels with a lean flow of water during the rainy season. Only a small portion of water form the rainfall is stored in the soil. The major portion of water reaches the sea abruptly. Biodiversity4 The Western Ghats also known as the Sahyadri hills is a mountain chain , different types of vegetation : scrub jungles and grasslands at low altitudes, dry and moist deciduous forests, grasslands and shoals, and the precious tropical evergreen and semi evergreen forests. Complex topography, high rainfall and relative inaccessibility have helped the region retain its biodiversity. Of the 15,000 flowering plant species in India, there are an estimated 4,780 species in the Western Ghats region. There is also a great diversity of traditional crop plants and an equal diversity of animal life. A large number of amphibians, freshwater fishes and in vertebrate groups are endemic to Western Ghats . Man-Made causes for degradation of Environment in Kerala Deforestation DEFORESTATION has many ecological, social and economic consequences, one of which is the loss of biological diversity .The destruction of territory is the most effective form of removal of any particular form of life from the face of earth. Menon and Bava2 have estimated the rate of deforestation in the Western Ghats to be .057% annually during the Period 1920 -1990.The food chain depends on depends upon the vegetation. Forests are an integral part of the vegetation. A vast area of forest has been cut dawn in the name of industrialization And rapid urbanization. Moreover the rural mass depends on the wood from the forest to keep their kitchen fires alive. The recent unstable rain fall in the area is the result of the loss of forest cover. The reduction of annual rain fall in the area is also another observed disaster the region now faces. Large scale deforestation in to Western Ghats and introduction of plantation crops in the high land replacing the natural vegetation reduced the storage capacity of soil and resulted in surface soil erosion in watersheds and sedimentation in rivers. This has affected summer flow in river s and some perennial rivers and rivulets have become seasonal in the last few decades due to large scale land cover changes. Sand Quarrying and River Bank Agriculture Excessive instream san d-and

The Hygiene Hypothesis Essay Example | Topics and Well Written Essays - 1250 words

The Hygiene Hypothesis - Essay Example Accordingly, it is important to note that the immune system develops from repeated attempts to keep off disease from the low level of pathogens found in a normal environment; as such, when the germs invade the body in life threatening amounts, the immune system successfully wards them off. The need for this exposure in developed nations some decades back saw to larger families than today. This is because parents believed that the elder child would expose the younger one(s) to pathogens, hence harden their immunity (Ascherio &Munge, 2007). It has also been observed that children who are taken to baby care institutions are less susceptible to allergies and immune diseases. The research has indicated that, children who had earlier been exposed to measles or hepatitis A are also quite resistant to allergies. Autoimmune diseases are those that the body should be able to naturally protect itself from, as per the hygiene hypothesis. Such include acute lymphoblastic leukemia affecting young people in the developed world. This is a region where young children are less likely to be exposed, and thereby develop the needed immunity. Unconfirmed evidence also links the hypothesis indirectly to autism, suggesting that an immune disease causes it (Lang, et al. 2010). However, extensive research shows that the hypothesis is of more significance to allergies than to immune diseases (Christensen, 2010). Some of the common allergens, i.e. substances that cause allergic attacks, include pollen, dust, hay, household chemicals, synthetic material, pet fur, some foods and some food preservatives. When these come into contact with the body of the allergic person, his/ her system activates the white blood cells in response to the foreign negative stimulus. (These cells normally help us to fight disease-causing microorganisms). Once released,

Multivariate Multilevel Modeling

Multivariate Multilevel Modeling Literature Review This chapter tying up the various similar studies related to modeling responses multivariately in a multilevel frame work. As a start, this chapter begins by laying out the recent history of univariate techniques for analyzing categorical data in a multilevel context. Then it gradually presents the literature available on fitting multivariate multilevel models for categorical and continuous data. More over this chapter reviews the evidence for imputing missing values for partially observed multivariate multilevel data sets. The Nature of Multivariate Multilevel models A multivariate multilevel model can be considered as a collection of multiple dependent variables in a hierarchical nature. Though the multivariate analysis increases the complexity in a multilevel context, it is an essential tool which facilitates to carry out a single test of the joint effects of some explanatory variables on several dependent variables (Snijders Bosker (2000). These models have the power of increasing the construct validity of the analysis for complex concepts in the real world. Consider a study on school effectiveness which can be measured on three different output variables math achievement, reading proficiency and well-being at school. These data are collected on students those who are clustered within schools by implying a hierarchical nature. Although it is certainly possible to handle three outcomes separately, it is unable to show the overall picture about school effectiveness. Therefore multivariate analysis would be more preferable in these types of scen arios since it has the capability of decreasing the type 1 error and increasing the statistical power (Maeyer, Rymenans, Petegem and Bergh) (Draft). Hierarchical natures of multivariate models are not like as the univariate response models. Let us focus on above example; it implies a two level multivariate model. But in reality it has three levels. In this case, the measurements are the level 1 units, the students the level 2 units and the schools the level three units. Importance of Multivariate Multilevel Modeling Multivariate multilevel data structures may itself present a greater complexity as it leads to focus the multilevel effects together with the multivariate context. Therefore the traditional statistical techniques would fail to face these kinds of areas since it can decrease the statistical efficiency by producing overestimated standard errors. On the other hand violation of independence assumption may cause to under estimate the standard errors of regression coefficients. Therefore multivariate multilevel approaches play an important role to get rid of these kinds of situations by allowing variation at different levels to be estimated. Furthermore Goldstein (1999) has shown that clustering provides accurate standard errors, confidence intervals and significance tests. Some amount of articles have been published on multilevel modeling based on a single response context. Multivariate multilevel concept comes into the field of statistics during the past few years. When people want to identify the effect of set of explanatory variables on a set of dependent variables and by considering these effects separately on response variables, then if it shows a considerable difference among those effects then it can be handled only by means of a multivariate analysis (Snijders Bosker, 2000). Software for Multivariate Multilevel Modeling In the past decades, due to the unavailability of the software for fitting multivariate multilevel data some researchers tend to use manual methods such as EM Algorithm (Kang et al., 1991). As a result of developing the technical environment, the software such as STATA, SAS and S plus are emerged in to the Statistical field by providing facilitates to handle the multilevel data. But none of those packages have a capability of fitting multivariate multilevel data. However there is evidence in the literature that nonlinear multivariate multilevel model can be fitted using packages such as GLLAMM (Rabe-Hesketh, Pickles and Skrondal, 2001) and aML (Lillard and Panis, 2000). But it was not flexible to handle this software. Therefore MlwiN software which has become the under development since late 1980’s was modified at the University of Bristol in UK in order to fulfill that requirement. However, the use of MlwiN for fitting multivariate multilevel models has been challenged by Goldstein, Carpenter and Browne (2014) who concluded that MlwiN was useful if only when fitting the model without imputing for the missing values. However REALCOM software was then came into the field of Statistics and provided the flexibility to impute the missing values in the MLwiN environment. MLwiN is a modified version of DOS MLn program which uses a command driven interface. MLwiN provides flexibility to fitting very large and complex models using both frequentist and Bayesian estimation along with the missing value imputation in a user friendly interface. Some particular advanced features which are not available in the other packages are included in this software. Univariate Multilevel Modeling vs. Multivariate Multilevel Modeling In general, data are often collected on multiple correlated outcomes. One major theoretical issue that has dominated the field for many years is modeling the association between risk factors and each outcome in a separate model. It may cause to statistically inefficient since it ignores outcome correlations and common predictor effects (Oman, Kamal and Ambler) (unpublished) Therefore most of the researches tend to include all related outcomes in a single regression model within a multivariate outcome framework rather than univariate. Recently investigators have examined the comparison between Univariate and Multivariate outcomes and they have proven that Multivariate models would be preferable than several univariate models. According to the Griffiths, Brown and Smith (2004), they conducted a study to compare univariate and multivariate multilevel models for repeated measures of use of antenatal care in Uttar Pradesh, India. In here, they examined many factors which may have a relationship to the mother’s decision to use ante-natal care services for a particular pregnancy. For that they compared Univariate multilevel logistic regression model vs. Multivariate multilevel logistic regression model. However as a result of fitting univariate models, model assumptions became violated and couldn’t get stable parameter estimates. Therefore they preferred the multivariate context rather than the univariate context after performing the analysis. Generalized Cochran Mantel Haenzel Tests for Checking Association of Multilevel Categorical Data. The history of arising the concepts related to Generalized Cochran Mantel Haenzel was streaming to the late 1950’s. Cochran (1958), one of a great Statistician has firstly introduced a test to identify the independence of multiple 2 Ãâ€" 2 tables by extending the general chi-square test for independence of a single 2-way table. In here, the each table consists of one or two additional variables for higher levels to detect the multilevel nature. The test statistic is based on the row totals of each table. The assumption behind is that the cell counts have binomial distribution. As an extension to Cochran’s work, Mantel and Haenzel (1959) extended the Cochran’s test statistic for both row and column totals by assuming the cell counts of each table follows a hypergeommetric distribution. Since Cochran Mantel Hanzel (CMH) statistic has a major limitation on binary data, Landis et al (1978) generalized this test into handle more than two levels. However there is a major drawback of the Generalized Cochran Mantel Haenzel (GCMH) test. This test was unable to handle clustered correlated categorical data. Liang (1985) was proposed a test statistic for get rid of this problem. However that test statistic itself had major problems and it was fail to use. As development of the statistics field, a need for a test statistic capable of handling correlated data and variables with higher levels arouse. Zhang and Boos (1995) coming in to the field and introduced three test statistics TEL TP and TU as a solution to the above problems. However among these three test statistics TP and TU are preferred to TEL since these two use the individual subjects as the primary sampling units while TEL use the strata as the primary sampling unit (De Silva and Sooriyarachchi, 2012). Furthermore, by a simulation study TP shows better performance than TE by maintaining its error values even when the strata are small and it uses the pooled estimators for variance. Therefore it provides a guideline to select TP as the most suitable statistic to perform this study. De Silva and Sooriyarachchi (2012) developed a R program to carry out this test. Missing Value Imputation in Multivariate Multilevel Framework The problem of having missing values is often arising in real world datasets. However it contains little or no information about the missing data mechanism (MDM). Therefore modeling incomplete data is a very difficult task and may provide bias results. Therefore this major problem address to a need of a proper mechanism to check the missingness. As a solution to that, Rubin (1976) presented three possible ways of arising misingness. These are classified as Missing At Random (MAR), Missing Completely At Random (MCAR) and Missing Not At Random (MNAR). According to the Sterne et. Al (2009), missing value imputation is necessary under the assumption of missing at random. However, it can also be done under the case missing complete at random. On nowadays most statistical packages have the capability of identifying the type of missingness. After identifying the type of missingness, the missing value imputation comes into the field and it requires a statistical package to perform this. Since the missing value imputation in a hierarchical nature is little bit more advanced and it cannot be done using usual statistical packages such as SPSS, SAS and R etc. Therefore Carpenter et. al (2009), developed the REALCOM software to perform this task. However latter version of REALCOM was not deal with multilevel data in a multivariate context. Therefore the macros related to perform this task was recently developed by the Bristol University team in order to facilitate under this case. Estimation Procedure The estimation procedures for multilevel modeling are starting late 1980’s. However For parameter estimation using Maximum Likelihood Method, an iterative procedure called EM algorithm was used by early statisticians (Raudenbush, Rowan and Kang, 1991). Later on the program HLM was developed to perform this algorithm. The most operational procedures for estimating multivariate multilevel models in the presence of Normal responses are Iterative Generalized Least Squares (IGLS), Reweighted IGLS (RIGLS) and Marginal Quasi Likelihood (MQL) while for discrete responses are MQL and Penalized Quasi Likelihood (PQL). According to Rasbash, Steele, Browne and Goldstein (2004) all of these methods are implemented in MLwiN along with including first order or second order Taylor Series expansions. However since these methods are likelihood based frequentist methods they tend to overestimate the precision. Therefore more recently the methods which are implemented in a Bayesian framework using Marcov Chain Monte Carlo methods (Brooks, 1998) also used for parameter estimation which allows capability to use informative prior distributions. These MCMC estimates executed in MLwiN provides consistent estimates though they require a large number of simulations to control of having highly correlated chains. Previous researches conducted using Univariate and Multivariate Multilevel Models Univariate multilevel logit models Before take a look at to the literature on multivariate multilevel analysis, the literature of univariate multilevel analysis is also be necessary to concerned since this thesis is based on some univariate multilevel models prior to fit multivariate multilevel models. In the past decades, many social Scientists used to apply multilevel models for binay data. Therefore it is very important to review how they have implemented their work with less technology. As a aim of that, Guo and Zhao (2000) was able to do a review of the methodologies, hypothesis testing and hierarchical nature of the data involve of past literature. Also they conducted two examples for justify their results. First of all they made a comparison between estimates obtained from MQL and PQL methods which was implemented by MLn and the GLIMMIX method implemented by SAS by using examples. They have shown that the differences in PQL 1 and PQL 2 are small when fitting binary logistic models. Furthermore, they have shown that PQL- 1 and PQL-2 and GLIMMIX are probable to be satisfactory for most of the past studies undertaken in social sciences. Noortgate, Boeck and Meulders (2003) uses multilevel binary logit models for the purpose of analyzing Item Response Theory (IRT) models. For that they carried out an assessment of the nine achievement targets for reading comprehension of students in primary schools in Belgium. They performed a multilevel analyses using the cross-classified logistic multilevel models and used the GLIMMIX macro from SAS, as well as the MLwiN software. However they found that there were some convergence problems arisen by using PQL methods in MLwiN. Therefore they used SAS to carryout analysis. Furthermore they have shown that the cross-classification multilevel logistic model is a very flexible to handle IRT data and the parameters can still be estimated even with the presence of unbalanced data. Multivariate Multilevel Models In the past two decades a very few of researches have sought to fit the multivariate multilevel models to the real world scenarios. Among those also all most all the researches trying to focus basically in educational sectors as well as socio economic sectors. None of them were able to focus these into the medical scenarios. However lack of multivariate multilevel analysis which presents in the field of health and medical sciences this chapter consists of the literatures of multivariate multilevel models in other fields. According to the previous studies of education, Xin Ma (2001) examined the association between the academic achievements and the background of students in Canada by considering three levels of interest. For that the three level Hierarchical Linear Model (HLM) was developed in order to achieve his goals. This work allows him to draw the conclusions that both students and schools were differentially successful in different subject areas and it was more obvious among students than among schools. However the success of this study is based on some strong assumptions about the priors of student’s cognitive skills. Exclusive of the field of education Raudenbush, Johnson and Sampson (2003) carried out a study in Chicago to determine the criminal behavior at person level as well as at neighborhood level with respect to some personal characteristics. For this purpose they use a Rasch model with random effects by assuming conditional independence along with the additives. Moreover, Yang, Goldstein, Browne and Woodhouse (2002) developed a multivariate multilevel analysis of analyzing examination results via a series of models of increasing complexity. They used examination results of two mathematics examinations in England in 1997 and analyzed them at individual and institutional level with respect to some students features. By starting from a simpler model of multivariate normality without considering the institutional random effects, they gradually increased the complexity of the model by adding institutional levels together with the multivariate responses. When closely looked at, there work shows that the choice of subject is strongly associated with the performance. Along with this growth of applications of multivariate multilevel models, researches may tend to apply those in to the other fields such as Forestry etc. Hall and Clutter (2004) presented a study regarding modeling the growth and yield in forestry based on the slash pine in U.S.A. In their work, they developed a methodology to fit nonlinear mixed effect model in a multivariate multilevel frame work in order to identify the effects of the several plot-level timber quantity characteristics for the yield of timber volume. In addition to that they also developed a methodology to produce predictions and prediction intervals from those models. Then by using their developments they have predicted timber growth and yield at the plot individual and population level. Grilli and Rampichini (2003) carried out a study to model ordinal response variables according to the students rating data which were obtained from a survey of course quality carried out by the University of Florence in 2000-2001 academic years. For that they developed an alternative specification to the multivariate multilevel probit ordinal response models by relying on the fact that responses may be viewed as an additional dummy bottom level variable. However they not yet assess the efficiency of that method since they were not implemented it using standard software. When considering the evidences of the recent applications of these models the literature shows that Goldstein and Kounali (2009) recently conducted a study on child hood growth with respect to the collection of growth measurements and adult characteristics. For that they extended the latent normal model for multilevel data with mixed response types to the ordinal categorical responses with having multiple categories for covariates. Since data consists of counts they gradually developed the model by starting a model with assuming a Poison distribution. However since the data are not follow exactly a Poisson distribution they treated the counts as an ordered categories to get rid of that problem. Frank, Cerda and Rendon (2007) did a study to identify whether the residential location have an impact to the health risk behaviors of Latino immigrants as they are increasing substantially in every year. For that they used a Multivariate Multilevel Rasch model for the data obtained by Los Angelis family and neighborhood survey based on two indices of health risk behaviors along with their use of drugs and participation for risk based activities. They starting this attempt by modeling the behavior of adolescents as a function of the characteristics related to both individual and neighborhood .According to the study they found that there is an association between increased health risk behaviors with the above country average levels of Latinos and poverty particularly for those who born in U.S.A. Another application of multivariate multilevel models was carried out Subramanian, Kim and Kawachi (2005) in U.S.A. Their main aim was to identify the individual and community level factors for the health and happiness of individuals. For that they performed a multivariate multilevel regression analysis on the data obtained by a survey which was held on 2000. Their findings reflect that those who have poor health and unhappiness have a high relationship with the individual level covariates By looking at the available literature, it can be seen that there are some amount of studies conducted on education and social sciences in other countries but none of the studies conducted regarding health and medical sciences. Therefore it is essential to perform a study by analyzing the mortality rates of some killing diseases which are spread in worldwide to understand risk factors and patterns associated with these diseases in order to provide better insights about the disease to the public as well as to the responsibly policy makers.

Tylenol :: essays research papers

Tylenol What Happened?   Ã‚  Ã‚  Ã‚  Ã‚  In October of 1982, Tylenol, the leading pain-killer in the United States at the time faced a crisis. Seven people in Chicago were reported dead after taking Tylenol. 12-year-old Mary Kellerdman of Elk Grove Village, Illinois, Adam Janus of Arlington Heights, Illinois, his brother Stanley Janus, and his wife Theresa Janus, Mary Reiner of Winfield, Paula Price, and Mary McFarland of Elmhurst Illinois was the last victim of the cyanide-laced Tylenol capsules. This happened bﴱᄃecause there was Extra-Strength Tylenol capsules that had been distributed and tampered with. The capsules contained 65 milligrams of cyanide. The amount necessary to kill a human is five to seven micrograms, which means that the person used 10,000 times more poison that what was needed.. The tampering had occurred when the products reached the shelves. The connection between the deaths and the Tylenol was discovered within days by two off-duty firemen who were listing to their pol ice radios. Phillip Cappitelli and Richard Keyworth were the men to make the connection and tell there superiors. What did Tylenol do?   Ã‚  Ã‚  Ã‚  Ã‚  Tylenol is part of the Johnson & Johnson Company. Once they made the connection between the report and the Tylenol they put customer safety first, before they worried about the company’s profit. The company immediately informed customers not to consume any type of Tylenol product. To throw away what they had until the extent of the tampering could be determined. Johnson and Johnson stopped all production and advertising. The recall included approximately 31 million bottles of Tylenol.   Ã‚  Ã‚  Ã‚  Ã‚  Tylenol’s credo is, â€Å"We believe our first responsibility is to the doctors, nurses, and patients, to mothers and fathers and all others who use our products and services. We are responsible for our employees, the men and women who work with us throughout the world. We are responsible to the communities in which we live and work and to the world community as well. Our final responsibility is to our stockholders. How they recovered?   Ã‚  Ã‚  Ã‚  Ã‚  To recover from the crisis Tylenol did a number of things. The first, they knew that that needed to gain consumer confidence so when they re-introduced the product there was a triple-seal tamper-resistant seal. They become the first company to comply with the Food and Drug Administration tamper-resistant packaging. Second they needed to motivate customers to buy the product, so they offered a $2.50 coupon on their purchase. They were available in the newspapers as well as a free number to call. Tylenol :: essays research papers Tylenol What Happened?   Ã‚  Ã‚  Ã‚  Ã‚  In October of 1982, Tylenol, the leading pain-killer in the United States at the time faced a crisis. Seven people in Chicago were reported dead after taking Tylenol. 12-year-old Mary Kellerdman of Elk Grove Village, Illinois, Adam Janus of Arlington Heights, Illinois, his brother Stanley Janus, and his wife Theresa Janus, Mary Reiner of Winfield, Paula Price, and Mary McFarland of Elmhurst Illinois was the last victim of the cyanide-laced Tylenol capsules. This happened bﴱᄃecause there was Extra-Strength Tylenol capsules that had been distributed and tampered with. The capsules contained 65 milligrams of cyanide. The amount necessary to kill a human is five to seven micrograms, which means that the person used 10,000 times more poison that what was needed.. The tampering had occurred when the products reached the shelves. The connection between the deaths and the Tylenol was discovered within days by two off-duty firemen who were listing to their pol ice radios. Phillip Cappitelli and Richard Keyworth were the men to make the connection and tell there superiors. What did Tylenol do?   Ã‚  Ã‚  Ã‚  Ã‚  Tylenol is part of the Johnson & Johnson Company. Once they made the connection between the report and the Tylenol they put customer safety first, before they worried about the company’s profit. The company immediately informed customers not to consume any type of Tylenol product. To throw away what they had until the extent of the tampering could be determined. Johnson and Johnson stopped all production and advertising. The recall included approximately 31 million bottles of Tylenol.   Ã‚  Ã‚  Ã‚  Ã‚  Tylenol’s credo is, â€Å"We believe our first responsibility is to the doctors, nurses, and patients, to mothers and fathers and all others who use our products and services. We are responsible for our employees, the men and women who work with us throughout the world. We are responsible to the communities in which we live and work and to the world community as well. Our final responsibility is to our stockholders. How they recovered?   Ã‚  Ã‚  Ã‚  Ã‚  To recover from the crisis Tylenol did a number of things. The first, they knew that that needed to gain consumer confidence so when they re-introduced the product there was a triple-seal tamper-resistant seal. They become the first company to comply with the Food and Drug Administration tamper-resistant packaging. Second they needed to motivate customers to buy the product, so they offered a $2.50 coupon on their purchase. They were available in the newspapers as well as a free number to call.

Discrimination and Young People Essay

1.1 Explain what is meant by * diversity * equality * inclusion Diversity means difference. It means understanding that each individual is unique, and recognizing our individual differences such as race, ethnicity, gender, sexual orientation, age, physical abilities and religious beliefs. Equality means treating everyone the same regardless of their individual differences. It is the discovery of these differences in a safe, positive, and nurturing environment. Everyone has an equal right to be treated with dignity and respect. No one should be denied opportunities because of their race or ethnicity, their disability, their gender or sexual orientation, their age or religion. Inclusion means including people in a way that makes them feel appreciated and respected. Treating individuals fairly and respecting the differences between them makes it easier to include them. 1.2 Describe the potential effects of discrimination Discrimination is treating someone or a group of people in a different way to everyone else based on their individual differences. It involves the behavior towards a child or children such as excluding or restricting children from activities that other children are participating in. Discrimination happens when we fail to respect individuals and their choices. Discrimination affects everybody in different ways: Low self-esteem, depression, withdrawn behaviour, shyness, tearful, fearful etc. When someone is discriminated against, it can exclude them from friends, family, neighbours, and society in general. A child’s self-worth is reduced, as they feel isolated, and alone. Children’s & Young People’s Workforce (2010 page 21) states that â€Å"When children experience prejudiced attitudes, there is a danger of damage to their self-esteem and self-confidence†. Discrimination can limit a child’s right to achieve their potential and objectives, their right to learn, their right to succeed. The most common forms of discrimination are racial remarks, being insulted and being the butt of hurtful jokes. Discrimination, racism and harassment may have significant mental and physical health consequences such as frustration, stress, anxiety and depression. Effects of discrimination physically and emotionally: Depression Anger Low self-esteem Isolation Loss of confidence Low self-worth Feeling stressed or unable to cope Fear of rejection The long-term effects could include: Loss of motivation Missed opportunities that may affect the child’s experiences and development Limited access to services Mental illness caused by stress 1.3 Explain how inclusive practice promotes equality and supports diversity Inclusive practice is about the attitudes, approaches and approaches taken to ensure that people are not excluded or isolated. It means supporting diversity by accepting and welcoming children’s differences, and promoting equality by ensuring equal opportunities for all children. Child care workers show inclusive practice by working in ways that recognise, respect, value and make the most of all aspects of diversity. Children’s & Young People’s Workforce (2010 page 25) states that another type of inclusive practice is to â€Å"offer children equality of opportunity to  participate, develop and learn. This does not mean treating them all the same; we have to acknowledge their diversity and treat children as individuals, with equal concern†. Having a sound awareness of and responding sensitively to an individual’s diverse needs supports them in developing a sense of belonging, well-being and confidence in their identity and capabilities and it helps them to achieve their potential to take their place in society. In addition, inclusive practice involves having an understanding of the impact that discrimination, inequality and social exclusion can have on an individual’s physical and mental health. Having such an understanding ensures appropriate, personalised care and support, thereby enabling an individual to develop self-respect and maintain a valued role in society. Children’s & Young People’s Workforce (2010 page 20) states that â€Å"When children spend time in settings which promote diversity, equality of opportunity and inclusion, they are able to make progress in all areas of development†. Inclusive practice involves reflecting on and challenging one’s own prejudices, behaviours and work practices. It also involves challenging those of colleagues and other service providers with a view to changing ways of thinking and working and changing services to build on good practice and to better support diversity and promote equality. Bibliography Authors:Penny Tassoni, Kate Beith, Kath Bulman, Sue Griffin Year of publication:2010 Title:Children’s & Young People’s Workforce – Early Learning & Childcare Publisher:Heinemann

The Crucible’s Abigal and Mary Warren

Abigail ; Mary Warren In this essay I will explore the characters of both Mary and Abigail. These two seem to be within the same circle of friends however have to complete different personalities. However with one being a leader and the other a follower they match perfectly. In the last scenes towards the end of the play we start to see a stronger side towards Mary Warren. She enters the court with intentions of speaking the truth of what happened, to tell the court that they all lied about seeing the devil.However eventually she stops coming across as strong minded and starts to show her real timid side who doesn't like to be ‘left out’ or seen as an outcast. Whereas Abigail’s character is shown to be very strong minded and conniving she always strives for what she wants. In one of the scenes we see Abigail trying to seduce ex flame Proctor, during this it is clear to see that proctor is indeed finding this hard to keep away however he does manage to stick to No and not retaliating.In the court we see another side to her, where she is fighting for her life and doesn't care who she takes down with her, this is shown by calling out to a big yellow bird as referring to it as Mary, and telling us that this bird wants to destroy her face. Abigail is portrayed to be a leader, she has her group of ‘friends’ who look up to her and rely on her. This is shown twice throughout the play, the first time is when the girls go to meet her at the beside if Betty and after hearing of witchcraft in town a couple of the girls immediately go to Abby asking for help/advise on what they should say.On the other hand, Mary Warren is portrayed as a follower. This shows that she is a weak minded person. She always needs someone there to push her or to defend her. This is shown at it strongest when at the last scene in the court, Mary leave the house with proctor with intentions of telling the courts the truth and to talk about how they all lied about dan cing with spirits etc however it is then reversed when Abigail turns all the other irls against Mary and trying to make the judges believe that there is a big huge yellow bird that Mary has sent to deface her, after about 2-3 minutes of this the girls catch on and also start to join in with mimicking Mary and making the people of the court believe that Mary has sent her soul out to get them. At this point Mary is petrified and doesn't know what it is that she is to do. In the end she ends up following Abigail and the girls and puts all the blame on proctor, blaming him for bringing her here, and saying that he too has made a pact with the devil.

How to Get Good Grades

How to Get Good Grades 5 Tips for Boosting Your Grades Getting good grades in school isnt something that just happens. It takes persistence, patience and a lot of effort on your part. Going from getting mediocre grades into good grades isnt going to happen overnight. It takes time to get yourself organized and develop the skills you need to succeed. To help you boost your grades, here are a few simple tips you can start implementing today. TIPS FOR USING THE CONTROL PANEL 1. Attendance Isnt Optional You cant expect to learn anything if you arent actually in the classroom to take in the information being taught. Being present in the classroom is crucial to improving your grades. By just listening to what the teacher has to say, you stand a chance of being able to walk away with at least a C. When you take notes and study further about the subject matter at hand, you are going to boost your grade even further. The skipping class will cause you to lose points and make your grade suffer further. 2. Keep Distractions to a Minimum If there is anything around you that could be a distraction and prevent you from learning, you need to get rid of it. Dont play around with your phone, listen to music or sit so far back in the classroom that you cant see or hear what the teacher is talking about. Sit closer to the front of the room to make sure you can hear what the teacher is saying and take accurate notes. Dont allow other classmates who might not be interested in learning to distract you from bettering yourself. 3. Pay Attention to Your Note-Taking Whatever the teacher talks about in class, you can plan on it being on the exam. Because of this, you need to make sure you are taking accurate notes that you can study from before the exam. Most of the time, teachers discuss the things that they feel are the most important. With accurate notes, you should have no problem passing the test. Go over everything the teacher discussed and make sure you know the material inside and out. Make note cards, discuss the material with the teacher or a friend, do whatever it takes to come out ahead and make sure the material is embedded in your brain. 4. Read through Your Textbooks Regardless of how much your teacher might try to fit everything into their class session, it isnt going to happen. They only have so much time to go over all of the material. Because of this, you have to take it upon yourself to go through the textbook provided and do your own research and studying. For many students, the thought of reading through pages upon pages of text can be intimidating and overwhelming. This is where you need to implement techniques like scanning, skimming and spotting keywords. Skimming involves going through and reading just the most important parts of the content. Reading the first sentence of every paragraph can help you pick up what the text is about quickly. Scanning is where you look through the main parts in a book to figure out whether it relates to your given topic. By reading the preface, index, intro and conclusion, you can get a good idea whether the book is going to help you or not. Spotting keywords involve going through and picking out the important phrases or words within the text. Anything highlight in italics or bold tends to be the most significant piece of information in the text. Pay attention for this formatting when reading the text. 5. Compare Your Notes with the Textbooks The key to mastering the material at hand is reading, analyzing and memorizing the materials. Read through your notes, write down any questions you might have and ask your teacher for the answers. You can also search your textbook for answers to your questions. This will help your brain to retain all of the information being taught in class. So, what are the things we should remember in order to get good grades? By going through the tips above, you can begin improving your grades in no time at all. Before you know it, you will have the grades you want and be on your way to a new grade point average. There is also another way to get your A become our customer! Our team of professional writers and 24/7 support cant wait to help you!