Ableism of Those Who Are Deaf Discriminationa and...

Ableism is defined as, â€Å"the all-encompassing discrimination and exclusion of people living with disabilities† (Adams et al, 461). However, in order to determine if ableism is occurring, then one must first know what constitutes a disability. According to the Americans with Disabilities Act, someone has a disability if they have a considerable handicap that hinders the actions that are important for life, such as â€Å"walking, seeing, hearing, learning, speaking, breathing, standing, lifting, or caring for one’s self† (Adams et al, 461). Disabled people make up the largest minority in the world with their estimated population at 650 million people (Adams et al, 461). Of this 650 million people, 360 million people have some sort of disabling†¦show more content†¦Problem Statement When the deaf or hearing impaired people are put into prison their language barriers cause them to experience a lack of access to fair legal treatment. Language Barrier A major factor or variable contributing to the lack of access to fair legal treatment for hearing impaired prisoners is the language barrier that they face. This makes language barriers the independent variable to lack of fair legal treatment for hearing impaired prisoners, the dependent variable. According to the Free Dictionary, a language barrier is defined as a, â€Å"barrier to communication resulting from speaking different languages† (â€Å"Language Barrier†). In the case of hearing impaired prisoners, these barriers apply to them in many ways. First, deaf and hearing impaired in the United States normally use American Sign Language, ASL, to communicate (Vernon). However, most prisons, despite laws established by the American Disabilities Act and the Individuals with Disabilities Education Act (IDEA), do not employ interpreters in order to allow the prisoners to establish communications with someone for purposes of taking education classes, acce ss to health care, access to counseling, and for hearings about parole, complaints, or punishments (Vernon). McCay Vernon states people in charge of prisons overestimate the ability of the hearing impaired to read lips. Even if the conditions for lip reading were perfect, meaning a well lit room, the speaker facing the hearing

The Current State Of South Africa Essay - 2016 Words

The current state of South Africa, 20 years post-apartheid, is regarded by many as desegregation achieved. However, in order for this to be completely true, it has to apply on every level. Pettigrew (2008), defined desegregation as the mere physical mixing of groups, and on this level, yes, we can say that the racial mixing of those previously segregated, is desegregation achieved. Yet, there is a distinct line between desegregation and genuine integration between the same people (Pettigrew, 2008). Contact theory has been widely studied for many years, the conditions crucial for it to be successful and to facilitate the effect of reducing prejudice between the groups are: cooperation between the groups/’s members, equal status between the two groups, authority support, and common goals (Pettigrew, 2008). Members of the dominant group have negative distorted perceptions about members of the subordinate group (Reicher, 2007). The theory was developed during a time when racial tension and racism were thought to be rooted from irrational beliefs and attitudes of and towards outgroups, as well as the assumption that behaviour and attitude were connected and that if one changed, the other would follow (Emerson, Kimbro, Yancey, 2002). Although contact theory is very effective in increasing intergroup relationships and reducing prejudice, there are limitations. Contact theory requires a utopian setting for it to be tested and rated effectively, where optimal contact andShow MoreRelatedThe Current State Of South Africa1175 Words   |  5 PagesBACKGROUND ON SOUTH AFRICA 1. South Africa was called the hopeless continent 16 years ago. Much of the negative world view stemmed from wounds created by government supported racial segregation which continues to affect South Africa’s economy today; however, the abundant resources and potential economic growth of this country should not be overlooked. Despite wounds from its past South Africa has a wealth of resources which make it an important country to the world and to the United States. South Africa’sRead MoreThe Epidemic Of Botswana, South Africa Essay1282 Words   |  6 Pages1 ​Today, in the world, especially African Countries in the South are facing an epidemic that has gone completely ignored by their very own government. Instead of proposing policies directed towards reducing the amount of HIV/AIDS cases that continue to rise each year, they have chosen to implement failed policies or none at all. Countries that have attempted to enact government policy to try to decrease the spread of the epidemic has ultimately failed in a broad sense. The epidemic is known asRead MoreThe Global Economic and Political Implications of the South African 2014 General Elections1164 Words   |  5 Pagesyear for South Africa. The first elections after the death of South African ex-president Nelson Mandela will take place and after twenty years of democracy, the world will be watching us again. The world holds much interest in the economy and politics of South Africa as was discussed in Appendix A and Appendix B and it is safe to assume that the world is a stakehold er in the politics and economy of South Africa. The purpose of this essay is to explore the world’s stake in South Africa, its natureRead MoreSouth Afric A Country Of Diversity1269 Words   |  6 PagesSouth Africa is a country of diversity, with 11 languages that are officially recognized--Afrikaans, English, Ndebele, Northern Sotho, Sotho, Swazi, Tsonga, Tswana, Venda, Xhosa, and Zulu (Statistics South Africa, 2011). Although South Africa has diverse communities, much of its history has proven a lack of representation. Up until 1994, South Africa was ruled by a white minority government, which came into power in 1948 and enforced a racial segregation policy called apartheid—a policy that mandatesRead MoreThe Long Term Potential Growth Rate Of South Africa Essay1006 Words   |  5 PagesThe long-term potential growth rate of South Africa under the current policy environment has been estimated at 3.5%.Per capita GDP growth has proved mediocre, though improving, growing by 1.6% a year from 1994 to 2009, and by 2.2% over the 2000–09 decade, compared to world growth of 3.1% over the same period. The high levels of unemployment, at over 25%, and inequality are considered by the government and most South Africans to be the most salient economic problems facing the country. These issuesRead MoreThe Curious Enlightenment Of Professor Caritat By Steven Lukes1283 Words   |  6 PagesCurious Enlightenment of Professor Caritat, by Steven Lukes (whom will be referred to as â€Å"Lukes† from now), the professor is sent out to find the best possible world. The essay will include a discussion on which society will best work in South Africa. In the current society, Communitarian and Libertarian systems are already evident, whereas Utilitarian rule is not. Utilitaria encourages people to be helpful and contribute to society; everyone is treated equally, hence creating an overall sense of purposeRead MoreTaking a Look at the Monash University896 Words   |  4 Pagescampuses affiliated to it spread across the world, in India, China, South Africa, Italy and Malaysia, at the same t ime linked to the Monash website. This essay will make an attempt to provide a critical analysis of the Monash website and the current affiliation with Laureate group of universities. Firstly, an analysis of Monash around the world link will be explored. Secondly, an attempt to discuss the affiliation of Monash South Africa University as part of the Laureate family with respect to the MonashRead MoreAuditing as a profession as evolved drastically over decades and as time has passed auditing1000 Words   |  4 PagesInternal Auditing Standards, the Current Role of Internal Auditing in SA, reviewing current crisis, the importance of Internal Auditing to management is evident. 2. FUNDAMENTAL PRINCIPLES RELATED TO GOVERNANCE 2.1 Corporate Governance in South Africa To understand the role internal auditors play in improving governance processes, one has to fully understand the meaning of the word governance and also the role governance plays in South Africa. Smerdon states that corporate governance is ‘theRead MoreForeign Policy : The Transition Of Democracy1039 Words   |  5 Pagesrelations with each other as well as international organisations and non-governmental actors. South Africa s post-apartheid foreign policy vision has become prosperous, peaceful, democratic, non-racial, non-sexist and united which contributes to the world that is equitable. This essay will discuss the transition to democracy and how the different heads have contributed to foreign policy since 1994 using the state and individual levels of analysis. This will be done with the following headings; heads ofRead MoreEconomic Growth And Development Of South Africa1193 Words   |  5 Pages2. CURRENT IMPLICATIONS 2.1. Growth and development According to Parson Viviers (cited by Vollgraaf 2016:p2) as a result of Brexit South Africa’s economic growth is expected to have a 0.1% cut-back due to its trading relations with the countries concerned. Bowler (2016:p1) stated that the UK’s pound depreciated after the Brexit occurrence, which could result in the UK’s imports being expensive. The country will be inclined to import less causing its trading import partners to suffer in the process

The Death of a Salesman by Arthur Miller †Linda Free Essays

Ms. Woods ENG 252 Sec 400 October 29, 2012 Linda – A Pillar of Strength and Balance In the Death of a Salesman by Arthur Miller My question for discussion is what I think of Linda, the wife of Willie Lohman in the play â€Å"The Death of a Salesman†. We will write a custom essay sample on The Death of a Salesman by Arthur Miller – Linda or any similar topic only for you Order Now This is my response. I feel that Linda is the strongest character in the play. Everyone around her has major issues, her sons and her husband. Even in the reflections of the past her brother-in-law had his issues – greed being one of them. She represents stability, goodness and balance in this story. She can be looked at as the foundation of this family, like most strong women. This story takes place in the 1940’s when the environment or way of living was the woman stayed home and tended to the family and the husband was the provider. And we also have a male dominated, sort of male chauvinist society at that time. So being that the man was the provider, a man had a sense of being the King of his home. Because of this general idea, it reduced the importance or view of women and their roles. Meaning a woman’s role was less than important because the man was King. Therefore, we see the questionable, forceful and harsh tones that Willie uses sometimes when speaking to Linda which can be interpreted or misinterpreted in different ways. And when this happens we see Linda back down or just close her mouth. But it also should be noted that Willie is losing everything around him, at home he feels that is the only place he can control what is going on. Then we see Willie’s dementia coming to a serious level of illness. This is not mentioned in the story but we see something wrong with Willie’s mental state. By the evidence given in the story, we can conclude many things – guilt, dementia, pressure and stress or just getting old and not wanting to face it. We are not given a reason for this deteriation. But it is evident by the reflections Willie has and how he is stuck in the past and/or stuck in a fantasy that something very deep is going on. This story is very male dominated with the symbolic theme of women are just extra’s. We hear this thru Willy Jr and Biff. They don’t seem to respect women either. Thru out the story no one seems to listen to her, her sons and neither Willie her husband. Linda is a faithful wife, playing her role. She stands and supports her husband. You never hear her say a bad word about her husband other than him being sick. She knows what’s wrong but I don’t think she knows how to handle it. At a time when medically no one really knew about mental illness, I think she viewed it as stress driven. Willis has been reduced at his job, he doesn’t want to face he’s getting old and his sons not being productive are just a few issues that contribute to the unrest in this household. She tries to explain to her sons what is going on but the fact that Willie probably was traveling salesmen for a long time and has been away so much that he has no real relationship with his son’s. Therefore they feel no pity for him, especially Willy Jr. who lost faith in his father a long time ago. So part of them being worthless and non productive can be contributed to not having their father around while they were growing up. So they do not have any attachment to him or what is going on with him nor does Willie Jr. care because of what he discovered when his father was having an affair. They only have attachment to their mother, Linda. She loves her boys regardless and her husband but she feels her duty first is to her husband. We also conclude that Linda does not know about the affair Willie had nor does she know that Willy Jr. knew about it. All she knows is the relationship between big Willie and junior Willy has been severely altered. Clinging to the suspicion that Willie (husband) is suffering from mental deterioration she wants to do whatever it takes to let him just grow old gracefully and peacefully, even if it means turning her back on her children. This is not to be taken as rejection or meanness because they are grown and are not contributing anything positive to the situation or conditions that are evolving. That is evident when they leave Willie in the bathroom at the restaurant and he suffers a severe breakdown and they don’t even come back to check on him. I feel that when she unloaded on her sons and voiced all the truths that were said is her finally being fed up with all the confusion going on around her. She is fighting to stay strong, guide and stay dedicated to her husband while moving all negatives out of the way. That is a sign of strength and dedication. This is symbolic of how she is truly the foundation and the balance of this family. Willie is losing control of everything, his job, his mind, his finance, his pride, his youth, etc. and Linda sees all of this. Thus his harsh treatment of her I do not feel is meant to hurt her. Remember a woman’s value in this era is reduced so she has no voice, no say and she abides by that. But in today’s time we would consider that disrespectful. I am considering the era of this story. But Linda stays strong and is always positive. Willie does realize he loves his wife and she loves him because at the end before he leaves to commit suicide he sends her to bed because he knows she would try to stop him from going out. And he knows she would do that out of love for him. Even though in his mind he sees this as a way of taking care of her and his sons. So in conclusion, the question remains do I believe that Linda was a dishrag? No I do not. Linda was the epitimy of a good wife, supportive, grounded, sacrificial and wise. She knew when to back down and when to be strong and speak out. She held Willie together as long as she could, until it was out of her hands. As she stated at his grave site, she truly did not understand how deep Willie’s issues really were. Thru all the symbolism of this story, good and bad (the sons), rich and poor (the environment and Willie’s associates), young and old (his reflections back to his younger days) Linda was the central figure in this story representing neutrality, balance and humbleness. How to cite The Death of a Salesman by Arthur Miller – Linda, Essay examples

Statistics Business Transformation Business Techniques

Question: 1. Statisticians divide variables into different classes (or types). Describe the classes of variables and give examples of each. Briefly describe (for each class of variables) the methods used to compare 2 independent groups of cases. Describe the assumptions and/or limitations of each technique. 2. What do you understand by the following statistical and epidemiological terms? You may find it helpful to use examples to illustrate your explanations. a)Boxplot (box and whisker plot) [20 marks] b)Addition law of probability [15marks] c)Retrospective study [15marks] d)R-squared (r2)[15marks] e)Cluster sampling[15marks] f)Standard error of a mean[20 marks] 3.This question is concerned with statistical measures to assess the reliability and accuracy of tests (for example, for diagnosing caries based on radiographs). a) What method(s) would you use to measure the extent to which 2 observers agree whether teeth are carious or not (reliability)? b) What method(s) would you use to measure the extent to which an observer agrees with a gold standard test (accuracy)? c) When might you use a ROC curve? d) Show the principles behind ROC curves by presenting a small example. 4.What is a 95% Confidence Interval for the mean of a variable? Explain how you would calculate it and state the assumptions behind the method you describe. Explain the relationship between a 95% Confidence Interval for the mean and a one-sample t-test. Explain briefly the principles behind, and the use and limitations of threeof the following. Suggest situations where they might be used when analysing dental data. [equal marks for each sub-section] a)Oneway analysis of variance (ANOVA) b)Survival analysis c)Log transformation d)Paired samples t-test 6 A researcher claims the mean DMFT of males aged 14 to 16 in a particular British region is 6. a) How you would set up a study to assess this? b) What are the appropriate hypotheses? c) How would you summarize the observations? d) What statistical test you would apply? e) How would you interpret the results of such a test? f) How would the size of your sample tend to affect the results? Answer: 1: Observations on a particular trait or character that are distinguishable or countable are called variables. A variable can be any number or measurement or characteristics whose value can vary over a certain range. Income of a person in a month is an example of a variable. Income of a person can take any values starting from 0. Age of students in class, the color of a flower, the number of books in a library is other examples of variables. Variables are classified into two types. By counting, the variables are categorized in to Qualitative and quantitative variables. Variables that can be counted are called quantitative variables. Age of students, the number of books in a library is examples of quantitative variables. On the other hand, the variables like the color of a flower, the first letter in the number plate of a car cannot be counted. These variables are referred to as qualitative variables. A quantitative variable can be classified into two types-discrete and continuous variables. Variables that can take values only a discrete set of points are referred to as discrete variables. While, on the other hand, if a variable takes values on a continuous scale then it is known as continuous variables. Number of books in a library, the number of people in a household is examples of discrete variables as these variables take distinct values. Height, weight, age are examples of continuous variables. Qualitative variables are also referred to as categorical variables as they describe a particular characteristic of a data point like to which category the data point belongs. Categorical variables can be of two types: Nominal variable: The categorical variables that cannot be arranged in an increasing or decreasing order are called nominal variables. Nominal variables can only be classified into a particular group. Type of business, eye color of a person is examples of nominal variables. Ordinal variables: The categorical variables that can be arranged in an increasing or decrease order are termed as ordinal variables. Grades that are given in an examination, any attitude towards a decision (disagree, agree, moderate, strongly agree) are examples of the ordinal variable. Two independent groups of variables can be compared using a different test. If the variables are quantitative, then t-test can be performed to test the whether the two groups are independent. If the variables are qualitative, then a two sample proportion test can be performed. The t-test can be used for the test of equivalence of two means of two independent samples. The hypothesis is given by H0: 1= 2 against H1: The means are unequal. The statistic for the test is: If the calculated t value greater than tabulated t value then the given hypothesis is rejected. The rejection of hypothesis implies that the two means are equal. If the variables are quantitative, then test for proportion can be performed. The hypothesis to be tested is p1=p2 against H1: proportions are unequal. The test statistic is given by Z= /s.d S.d=sqrt((p(1-p)(1/n1+1/n2)) Where p1 is the estimated proportion of the first sample and p2 denotes the estimated proportion of the second sample. "n1" and "n2" are the sizes of the two samples. The test statistic is rejected if the calculated p-value is less than the level of significance . The limitation of t-test is that the underlying distribution of the sample is assumed to be normal. If the distribution is not a normal distribution, then a robust statistic like median has to be used. Then the median test can be performed. In the median test, the hypothesis to be tested is H0:me1=me2 against H1: me1me2. In the proportion test, the sample variance is the pooled variance of the two samples. Pooled variance can be assumed if the variance of each group is more or less same. If the two groups greatly differ by variance, then pooled variance cannot be used. In that case, test for proportion is invalid. 2: Box Plot: Box plot or box and whiskers plot is a way to represent statistical data graphically. A box plot is also termed as box and whiskers plot. The lines that extend vertically from two sides of the box are called the whiskers. A box plot is a nonparametric representation. It does not assume any underlying distribution. The Box in the box plot is the space between first and the third quartile. Outliers can be easily detected with the help of box plot. The box plot gives an idea about the spread or dispersion of the dataset. Any box and whiskers plot depicts the following statistical measures: Median: The median is the midpoint of the data and is represented in the box plot by the line inside the box. From the position of the median in the box plot, one can determine whether the distribution is skew or symmetric. Sometimes an additional line for the arithmetic mean is also given inside the box. If the mean and median line coincides, then the distribution is symmetric. Otherwise, it is skewed. Quartile: 75 percent of the observation falls below the first quartile, and 25 percent of the observations fall below the first quartile. Range: It is the difference between the minimum and maximum observation in a dataset. Interquartile range: Interquartile range is the length of the box.50% of the observations are expected to lie within the range. Outlier: Any outlier if present is detected in the outside the interquartile range. The outliers lie between the points 1.5 IQR and 3 IQR. Addition law of probability: Two events A and B are considered. The events are mutually exclusive if the probability of their intersection equals zero. Two events are collectively exhaustive if the union of the two events makes up the entire sample space. P( Addition law of probability states that A1, A2,,, An be n events The events possesses the above two properties that are the events are events collectively exhaustive and mutually exclusive. Then the probability of the union of the events is equal to the sum of their probabilities. Retrospective study: A retrospective study refers to the longitudinal study design of two cohorts. In this kind of study, one cohort is exposed to particular disease and another cohort is not exposed to the disease. The two cohorts are compared to identify the factors in their history that can be associated with the disease. The data are collected from past values. The study is mainly conducted to determine the risk associated with the disease and to estimate the number of causalities from the disease. The risk ratio or Odd ratio of the two groups is calculated which gives the relative risk of the disease in the particular cohort. The Risk ratio is given by the following formula: DISEASE PRESENT DISEASE ABSENT Group1 A b a+b Group 2 C d c+d a+c b+d n Then risk ratio is given by Odds ratio is given by: OR=ad/bc If the value of Risk ratio is greater than one, then, the cohort has a less chance of developing the disease.If the value of risk ratio is greater than one, then the cohort has a higher chance of developing the disease. Same interpretation also applies for the Odds ratio. The advantages of Retrospective study is that it is less costly, less time consuming and could easily be conducted and gives a better comparison of disease between the cohorts. For example, if one wants to compare the oral health status of two groups, an idea about the oral health status of the new generation can be obtained from the oral health status of the mothers. R-squared: R-squared values are calculated to determine how good a fitted model is. The R-squared value is the ratio of the residual and total sum of the squared values. The greater the value of R squared statistic in the case of a regression model; the better is the fitted model. R-squared=RSS/TSS. A good model is expected to have the minimum error. The sum of errors is equal to zero. To make a comparison, squared sum of errors has to be considered. The smaller the value of RSS or residual sum of the square the better is the model. So more the value of R squared, the better is the model. R-squared value does not consider the number of parameters involved in a model. For a model to be good, the model should be parsimonious. For this, another measure of R-squared is developed which is called adjusted R-squared. The adjusted R-squared measure is given by the following formula: R-squared (adjusted)= 1- (RSS/n-k)/(TSS/n-1) .K is the number of parameters. So higher the value of adjusted R-squared the better is the fitted model regarding both parsimony (minimum no of parameters) as well minimum errors. Cluster Sampling: Sampling is the procedure in which only a drawn sample from the population is considered for the purpose of statistical computation. Cluster sampling is an efficient sampling procedure where the total population is at first divided into some clusters and then the sample is collected from this clusters. The clusters are made as homogeneous as possible. Cluster sampling can be one stage or two stages. For example, for obtaining sample of household expenditure from a city, at first, the city can be divided into several blocks according to locality and then sample could be collected from each of the blocks. These blocks form the cluster. Standard error of a mean: The average sample value is an unbiased estimate of the average value of a population. The deviation of the mean of sample from the population mean value is the error. The standard deviation of the mean of sample value is called the standard error of the mean. 3: Inter-rater reliability is used to measure the extent to which two observers agree whether the teeth are carious or not. Inter-rater reliability is used in case of subjective judgment. If the rating scale is continuous, then Pearson's product moment correlation is used. If the rating scale is ordinal, then Spearman's product moment is calculated. For the case of a categorical variable, Cohen's Kappa is used. The formula for Cohen's Kappa is: Where O is the observed agreement, and E is the expected value of the agreement. N is the total sample size. The failure rate is used to measure the extent to which an observer agrees with the gold standard test. The failure rate is given by f(t)/R(t) where f(t) is time to failure of an event and R(t)=1-F(t).F(t) is the cumulative distribution function of t. C.ROC curve is drawn to discriminate between the presence or absence of a disease.ROC curve is drawn by plotting FPR against the TPR. The FPR is equal to (1- specificity), and true positive rate is calculated by sensitivity. Sensitivity refers to the proportion of population with the disease tests positive. Specificity relates to the part of population without the disease testing negative. The area inside the curve of ROC helps to determine the level of discrimination between the individuals with test positive and individual with test negative. The underlying principles of the ROC curve are: The threshold value for drawing the ROC curve influences the specificity and sensitivity values. The threshold value should be so chosen that distribution of test results for presence or absence of disease should not overlap. In most of the cases, the two distributions overlap. But in most of the cases, the two distributions overlap. So the diseased people are misclassified as normal people. Lowering the threshold value will increase specificity while higher threshold value decreases specificity. 4: The mean of a variable that is to be calculated is the sample mean. The population mean is different from the sample mean. In a practical situation, a confidence interval with confidence coefficient 95 for any statistic gives the probability that the value of the mean lies within the interval with confidence limit 95%. That means if the sample is repeated as many times as possible, the probability that the mean value lies within the interval is 0.95.if the distribution of test statistic is standard normal, then the confidence interval is given by the following formula: Ucl=xbar +s/sqrt(n)*z Lcl= xbar-s/sqrt(n)*z Again if the test statistic follows a t distribution, then the upper and the lower control limits are given by: Ucl=xbar +s/sqrt(n)*t Lcl= xbar-s/sqrt(n)*t The t statistic is generally used in case of confidence interval if the standard deviation value is to be calculated from the sample. If the population standard deviation value is given then, one can use z test to determine the value. 5: The following methods are used for analysis of dental data: One way ANOVA: One way ANOVA or variance analysis is carried out to test whether the means of several groups are equal or not in the case of fixed effect model and equality of variance of several groups in case of random effects model. In one way ANOVA, there is only one factor affecting the values of the variable. The one-way ANOVA model is given by: Where yij represents j the observation in the ith cell. is the common mean effect and i is the effect due to the ith group and eij is the error assumed to follow N(0,^2) distribution. The random effect model is given by Yij=+ai +eij , where eij is the random effect due to the ith group. An example where ANOVA test can be conducted in dental study: One wants to measure the performance of five brands of toothpaste that heals tooth sensitivity. Certain volunteers are selected and each of them is given a brand of toothpaste to use. After the completion of one tube, the patients were asked to give a score about how their sensitivity problem is. The mean score from each volunteer is collected, and the mean scores are tested with the help of ANOVA, and the toothpaste that performs best can be found out. ANOVA test has certain assumptions: The error is distributed as normal with zero mean and uniform variance ^2 across all groups. The observations are supposed to be independent. If the above assumptions are violated, then ANOVA test cannot be carried out. Besides, ANOVA can tell only if all the means are equal. If the means are unequal, then one has to perform t-test to compare two means. Survival Analysis: Survival analysis determines the time to failure (or survival) of an event. Survival analysis is particularly useful in case of censored data. For example, if one wants to find the time required f or recovering from a disease then survival analysis can be used. Survival Analysis can be used to study a particular impact of certain dental surgery on the patients. For this analysis, one can study the time to the occurrence of the event(death) of the patient along with other factors. The study can be done with the help of Kaplan-Meir estimator. If there are several factors affecting the time, then a regression model such as Cox model of proportional hazard functions can be used. This analysis aims to study the time to occurrence of an event. It gives the chance or probability of survival from a particular disease. Survival analysis also takes into account the effect of other covariates over time to survival. But survival analysis has certain limitations. The limitations of Survival regression is same as that of ordinary regression problems. The statistical data and real life data are different. So the estimates from survival analysis are valid up to certain extent and may not be true for every case. The error in survival models is assumed to be normally distributed. Another important feature in survival analysis is censored observations. If the number of edited cases is too many, then survival analysis can lead to faulty results. C.Log transformation: Log transformation is used in the following cases: 1.To make the data skewed: Log transformation is mainly used to make a skewed data more less skewed. Taking logarithm of the values, one can compare the geometric mean of the values instead of arithmetic mean. For example, if the brain weight of a person is plotted with body weight then the distribution is skewed as the body weight is very large as compared to brain weight. Plotting the log-transformed variables, the distribution becomes less skewed. 2.Log transformation is used if the dependent variable is discrete or binary and the response variables are continuous. By taking logarithm of variable, the response variable can be converted into a discrete variable. This often happens if the response variable is dependent on some categorical variable. To standardize the data: Sometimes data do not follow normal distribution. Taking a log transformation of the values will make the data follow normal distribution. Log transformation has certain limitations. It is not applicable to confounded data. Data point has to be independent. Otherwise, change is not useful. D.T-test: This is a test of paired sample observations which is used to test the dependence of the arithmetic mean value of two variables. Paired sample t-test can only be done if the sample size of two samples is equal. In paired sample t test the difference of each observation is calculated. Let di denote dit. The mean of the observation is tested to be equal to zero or not. The hypothesis of interest is to test H0: The mean value of the paired observation is equal to zero against H1: not H0.and the test statistic is (dbar/sd) where dbar is the mean of di and sd is the standard deviation of di values. The statistic for performing the test is said to follow a t distribution. In this case, the d.f will be equal to n-1 where n is the sample size. The limitations of paired t-test are that it is applicable when the groups have same sample size. If the sample size varies then, another t-test has to be performed. It is also applicable to datasets that have standard normal distribution. If underlying distribution is nonnormal, then nonparametric tests could be performed. 6: The DMF index is a method used in dentistry for testing dental caries. The dmft of males between 12 to 14 years of age is six as claimed by a certain researcher. So to support this claim a test has to be conducted. A sample has to be drawn from the population of males between the age group 12 to 14 years. Then the mean value of dmft obtained from the sample has to be tested. The hypothesis that has to be tested in this case is whether the mean or median of the population is equal to 4 or not. H0: = 6 against h1: six where represents the mean of the distribution. Or, h0: me=6 against h1: me6. The distribution of the population of males can be assumed to be normally distributed. In that case, one can test whether the mean value is equal to 6 or not. The mean value of the population can be estimated by sample mean. Then the problem is to test whether the sample mean value is less than a particular value. If the population does not follow standard normal distribution, then a nonparametric test for median of the observation can be done. If the population distribution is assumed to be normal, then a test for the sample mean could be performed. Then the problem is to test h0: =6 against h1: 6. If the value of s.d of population is known, then z-test can be performed. If the population value of standard deviation has to be estimated from sample value, a t-test has to be performed. The statistic for the z test is given by: Z=( - )/ where is the sample mean. The test statistic for t distribution is: T=( - )/s where s is the s.d of sample. Interpreting test results: A test is rejected if probability value of the test is less than level of significance. H0 is rejected if z-value is greater than z/2 at level of significance . Z/2 is the tabulated of value of upper alpha point from the standard normal distribution table. In case of t test the null hypothesis is rejected at level of significance if tt value determined from sample is greater than tabulated t value at the level of significance /2 at degrees of freedom n-1. The size of the sample is important in case of performing a test. The accuracy of a test depends on the sample size. The value of sample size is given by the following formula: N = (1.96*sigma^2)/e^2 .here sigma denotes value of standard deviation. E denotes the correction limit within which the value of the mean that is to be estimated.