Describe the possible signs Essay Example for Free

Describe the possible signs Essay Bullying is not defined as a form of abuse in Working Together but there is clear evidence that it is abusive and will include at least one, if not two, three or all four, of the defined categories of abuse. Recognising child abuse is not easy. It is not our responsibility to decide whether or not child abuse has taken place or if a child is at significant risk of harm from someone. We do however, have both a responsibility and duty, as set out in your organisation’s child protection procedures, to act in order that the appropriate agencies can investigate and take any necessary action to protect a child. Physical abuse Physical abuse is deliberately causing physical harm to a child. This might involve punching; kicking, biting, burning, scalding, shaking, throwing or beating with objects such as belts, whips, or sticks. It also includes poisoning, giving a child alcohol or illegal drugs, drowning or suffocation. Physical harm may also be caused when a parent or carer fabricates the symptoms of illness in a child. Signs of Physical Abuse There are certain signs that need to be acknowledged when suspicion arises that physical abuse is occurring: Any injuries not consistent with the explanation given to staff. Injuries which occur to any part of the body but usually in places which are not normally exposed to falls or rough games Injuries which have not received medical attention Reluctance to change in the heat, or to change/participate in activities such as, PE or swimming Bruises (usually in clusters), human bites, cigarette burns and fractures, for example, which do not have an accidental explanation multiple burns with a clearly demarcated edge Fear of parents being approached for an explanation Flinching when approached or touched Aggressive behaviour and/or sudden anger outbursts Depression Running away from home Possible effects of physical abuse Physical abuse can lead directly to neurological damage, physical injuries, disability and in extreme cases death. Physical abuse has been linked to aggressive behavior in children, emotional and behavioral problems and learning difficulties. Emotional Abuse Emotional abuse is where repeated verbal threats, criticism, shouting, lack of love and affection causes a severe adverse effect on a childs emotional development. It consists of communicating to children that they are worthless, unloved, and inadequate or valued. Emotional abuse may include not giving a child opportunities to express their views, deliberately silencing them or making fun of what they say. It may feature inappropriate expectations being imposed on a child, over protection and limitation of exploration and learning, or preventing the child from taking part in normal social interaction. Signs of possible emotional abuse †¢ Depression, aggression, extreme anxiety, changes or regression in mood or behavior, particularly where a child withdraws or becomes clingy †¢ Obsessions or phobias †¢ Sudden underachievement or lack of concentration †¢ Seeking adult attention and not mixing well with other children †¢ Sleep or speech disorders †¢ Low self-esteem †¢ Fear of parents/carer being approached regarding their behavior †¢ Fear of making mistakes Possible effects of emotional abuse This type of abuse can lead to adverse long-term effects on the child’s development. Emotional abuse has a significant impact on a developing childs mental health, behavior and self-esteem. This type of abuse is as important as the other three types, and can be detected as the signs are more visible and can be easily detected. Domestic violence, adult mental health problems and parental substance misuse may be features in families where children are exposed to such abuse. Sexual Abuse Sexual abuse involves forcing or enticing a child or young person to take part in sexual activities, whether or not the child is aware of what is happening. This may involve physical contact including penetrative sex, oral sex, masturbation, kissing, rubbing, or touching outside of clothing, or it may involve non-contact activities such as involving children in watching sexual activities, producing or looking at sexual images, encouraging children to behave in sexually inappropriate ways, or grooming a child in preparation for abuse (including via the internet). Abusers can be men, women or other children. Between 21% and 36% of sexually abused children will display few or no symptoms but it is usually a child’s behavior which becomes a cause for concern. Children who tell of sexual abuse do so because they want it to stop therefore is extremely important to listen to a child that discloses such an allegation. Signs of possible sexual abuse †¢ Any allegations made by a child concerning sexual abuse †¢ self-harming, sometimes leading to suicide attempts †¢ Sexual activity through words, play or drawing †¢ Repeated urinary infections, itching or bleeding around genital area and/or unexplained stomach pains †¢ The child is sexually provocative or seductive with adults †¢ Saying they have a secrets that they cannot share with anyone †¢ Severe sleep disturbances with fears, phobias, vivid dreams or nightmares which sometimes have overt or veiled sexual connotations or bedwetting †¢ Eating disorders such as anorexia or bulimia Possible effects of sexual abuse Behavior such as self-harm, inappropriate sexual behavior, sadness, depression and loss of self-esteem has all been linked to sexual abuse. The effects of sexual abuse can affect the individual into their adult life. The extent or the severity of each case is determined by the time span of abuse, the more serious the abuse, the younger the child is and the relationship of the child to the abuser. Once sexual abuse has been identified the support of an adult who believes the child helps, starts to help the child understand the abuse and can therefore offer help and protection to the abused child. Neglect Neglect has been described as the â€Å"most serious type of child maltreatment and the least understood† (Crittenden 1999: 67). It is the most common reason for a child to be placed on the child protection register in the UK. Neglect is the failure to meet a child’s basic physical and or psychological needs, which is likely to affect the child’s health or development. Neglect is when a parent or carer fails to provide adequate food, clothing, shelter (including exclusion from home or abandonment), medical care, or protection from physical and emotional harm or danger. Additionally failure to ensure access to education or to look after a child because the carer is under the influence of alcohol or drugs, is considered as Neglect. Signs of possible neglect †¢ Dirty skin, body smells, unwashed, uncombed hair and untreated lice †¢ Clothing that is dirty, too big or small, or inappropriate for weather conditions †¢ frequently left unsupervised or alone †¢ Frequent diarrhoea †¢ complaints of being tired all the time †¢ Untreated illnesses, infected cuts or physical complaints which the carer doesn’t respond to †¢ frequently hungry sometimes stealing other children’s food †¢ Being underweight Possible effects of neglect Neglect can seriously impair a childs health, physical and intellectual growth and development, and can cause long term difficulties with social functioning, relationships and educational progress. Extreme cases of neglect can cause death. Bullying Bullying is also recognized as a type of abuse. Bullying is always distressing for the victim and can have serious consequences. Bullying should always be taken seriously. Emotional bullying is the most commonly reported by children and young people and is often more difficult to spot. Bullying can take place both inside and outside of the school. Bullying happens when an individual or a group show hostility towards an individual and this can be: †¢ Emotional, such as name-calling, not talking to someone, taking or hiding personal items, humiliating, spreading rumors or teasing †¢ Physical, such as pushing, kicking, hitting, pinching or threatening to use physical force †¢ Racist, such as racial taunts or gestures †¢ Sexual, such as inappropriate physical contact, sexual comments and innuendo, or homophobic taunts. Signs of possible bullying Loss of personal possessions, dinner money or items of clothing Torn clothing, maybe even having cuts and bruises (if physically bullied) Shyness, withdrawn behavior, lack of self-esteem and depression Aggressive, bad tempered behavior and may become aggressive to younger siblings Threaten or attempt suicide Not achieving very well academically Not wanting to leave their home Possible effects of bullying Bullying will most definitely affect a child’s social and emotional development as they have very low self-esteem maybe depression and will probably try to isolate themselves from others which will have a profound effect on their social skills with their peers and pretty much everybody around them, they may become aggressive and bad tempered and may threaten or attempt suicide and in some extreme cases may actually commit suicide. Cyber-bullying In recent years, a new form of bullying known as ‘cyber-bullying’ has become increasingly common. Cyber-bullying may be emotional, racist or sexual forms of abuse. It happens through emails, text messages or telephone calls. Information about someone may also be shared by putting it on to social networking sites. This can include the sharing of private photographs. Children and young people who use this method of bullying often feel disassociated from their actions, but the consequences can be just as serious for the child. This type of bullying can be particularly distressing as children are unable to get away from it, it even invades their home.

Normal Approximation in R-code

Normal Approximation in R-code Normal approximation using R-code Abstract The purpose of this research is to determine when it is more desirable to approximate a discrete distribution with a normal distribution. Particularly, it is more convenient to replace the binomial distribution with the normal when certain conditions are met. Remember, though, that the binomial distribution is discrete, while the normal distribution is continuous. The aim of this study is also to have an overview on how normal distribution can also be concerned and applicable in the approximation of Poisson distribution. The common reason for these phenomenon depends on the notion of a sampling distribution. I also provide an overview on how Binomial probabilities can be easily calculated by using a very straightforward formula to find the binomial coefficient. Unfortunately, due to the factorials in the formula, it can easily lead into computational difficulties with the binomial formula. The solution is that normal approximation allows us to bypass any of these problems. Introduction The shape of the binomial distribution changes considerably according to its parameters, n and p. If the parameter p, the probability of â€Å"success† (or a defective item or a failure) in a single experimental, is sufficiently small (or if q = 1 – p is adequately small), the distribution is usually asymmetrical. Alternatively, if p is sufficiently close enough to 0.5 and n is sufficiently large, the binomial distribution can be approximated using the normal distribution. Under these conditions the binomial distribution is approximately symmetrical and inclines toward a bell shape. A binomial distribution with very small p (or p very close to 1) can be approximated by a normal distribution if n is very large. If n is large enough, sometimes both the normal approximation and the Poisson approximation are applicable. In that case, use of the normal approximation is generally preferable since it allows easy calculation of cumulative probabilities using tables or other tec hnology. When dealing with extremely large samples, it becomes very tedious to calculate certain probabilities. In such circumstances, using the normal distribution to approximate the exact probabilities of success is more applicable or otherwise it would have been achieved through laborious computations. For n sufficiently large (say n > 20) and p not too close to zero or 1 (say 0.05 To find the binomial probabilities, this can be used as follows: If X ~ binomial (n,p) where n > 20 and 0.05 So is approximately N(0,1). R programming will be used for calculating probabilities associated with the binomial, Poisson, and normal distributions. Using R code, it will enable me to test the input and model the output in terms of graph. The system requirement for R is to be provided an operating system platform to be able to perform any calculation. Firstly, we are going to proceed by considering the conditions under which the discrete distribution inclines towards a normal distribution. Generating a set of the discrete distribution so that it inclines towards a bell shape. Or simply using R by just specifying the size needed. And lastly compare the generated distribution with the target normal distribution Normal approximation of binomial probabilities Let X ~ BINOM(100, 0.4). Using R to compute Q = P(35 X ≠¤ 45) = P(35.5 X ≠¤ 45.5): > diff(pbinom(c(45,35), 100, .4)) [1] -0.6894402 Whether it is for theoretical or practical purposes, Using Central Limit Theorem is more convenient to approximate the binomial probabilities. When n is large and (np/q, nq/p) > 3, where q = 1 – p The CLT states that, for situations where n is large, Y ~ BINOM(n, p) is approximately NORM(ÃŽ ¼ = np, ÏÆ' = [np(1 – p)]1/2). Hence, using the first expression Q = P(35 X ≠¤ 45) The approximation results as follows: l ÃŽ ¦(1.0206) – ÃŽ ¦(–1.0206) = 0.6926 Correction for continuity adjustment will be used in order for a continuous distribution to approximate a discrete. Recall that a random variable can take all real values within a range or interval while a discrete random variable can take on only specified values. Thus, using the normal distribution to approximate the binomial, more precise approximations of the probabilities are obtained. After applying the continuity correction to Q = P(35.5 X ≠¤ 45.5), it results to: ÃŽ ¦(1.1227) – ÃŽ ¦(–0.91856) = 0.6900 We can verify the calculation using R, > pnorm(c(1.1227))-pnorm(c(-0.91856)) [1] 0.6900547 Below an alternate R code is used to plot and illustrate the normal approximation to binomial. Let X ~ BINOM(100, l4) and P(35 45) > pbinom(45, 100, .4) pbinom(35, 100, .4) [1] 0.6894402 # Normal approximation > pnorm(5/sqrt(24)) pnorm(-5/sqrt(24)) [1] 0.6925658 # Applying Continuity Correction > pnorm(5.5/sqrt(24)) pnorm(-4.5/sqrt(24)) [1] 0.6900506 x1=36:45 x2= c(25:35, 46:55) x1x2= seq(25, 55, by=.01) plot(x1x2, dnorm(x1x2, 40, sqrt(24)), type=l, xlab=x, ylab=Binomial Probability) lines(x2, dbinom(x2, 100, .4), type=h, col=2) lines(x1, dbinom(x1, 100, .4), type=h, lwd=2) Poisson approximation of binomial probabilities For situations in which p is very small with large n, the Poisson distribution can be used as an approximation to the binomial distribution. The larger the n and the smaller the p, the better is the approximation. The following formula for the Poisson model is used to approximate the binomial probabilities: A Poisson approximation can be used when n is large (n>50) and p is small (p Then X~Po(np) approximately. AN EXAMPLE The probability of a person will develop an infection even after taking a vaccine that was supposed to prevent the infection is 0.03. In a simple random sample of 200 people in a community who get vaccinated, what is the probability that six or fewer person will be infected? Solution: Let X be the random variable of the number of people being infected. X follows a binomial probability distribution with n=200 and p= 0.03. The probability of having six or less people getting infected is P (X ≠¤ 6 ) = The probability is 0.6063. Calculation can be verified using R as > sum(dbinom(0:6, 200, 0.03)) [1] 0.6063152 Or otherwise, > pbinom(6, 200, .03) [1] 0.6063152 In order to avoid such tedious calculation by hand, Poisson distribution or a normal distribution can be used to approximate the binomial probability. Poisson approximation to the binomial distribution To use Poisson distribution as an approximation to the binomial probabilities, we can consider that the random variable X follows a Poisson distribution with rate ÃŽ »=np= (200) (0.03) = 6. Now, we can calculate the probability of having six or fewer infections as P (X ≠¤ 6) = The results turns out to be similar as the one that has been obtained using the binomial distribution. Calculation can be verified using R, > ppois(6, lambda = 6) [1] 0.6063028 It can be clearly seen that the Poisson approximation is very close to the exact probability. The same probability can be calculated using the normal approximation. Since binomial distribution is for a discrete random variable and normal distribution for continuous, continuity correction is needed when using a normal distribution as an approximation to a discrete distribution. For large n with np>5 and nq>5, a binomial random variable X with X∠¼Bin(n,p) can be approximated by a normal distribution with mean = np and variance = npq. i.e. X∠¼N(6,5.82). The probability that there will be six or fewer cases of these incidences: P (X≠¤6) = P (z ≠¤ ) As it was mentioned earlier, correction for continuity adjustment is needed. So, the above expression become P (X≠¤6) = P (z ≠¤ ) = P (z ≠¤ ) = P (z ≠¤ ) Using R, the probability which is 0.5821 can be obtained: > pnorm(0.2072) [1] 0.5820732 It can be noted that the approximation used is close to the exact probability 0.6063. However, the Poisson distribution gives better approximation. But for larger sample sizes, where n is closer to 300, the normal approximation is as good as the Poisson approximation. The normal approximation to the Poisson distribution The normal distribution can also be used as an approximation to the Poisson distribution whenever the parameter ÃŽ » is large When ÃŽ » is large (say ÃŽ »>15), the normal distribution can be used as an approximation where X~N(ÃŽ », ÃŽ ») Here also a continuity correction is needed, since a continuous distribution is used to approximate a discrete one. Example A radioactive disintegration gives counts that follow a Poisson distribution with a mean count of 25 per second. Find probability that in a one-second interval the count is between 23 and 27 inclusive. Solution: Let X be the radioactive count in one-second interval, X~Po(25) Using normal approximation, X~N(25,25) P(23≠¤x≠¤27) =P(22.5 =P ( ) =P (-0.5 =0.383 (3 d.p) Using R: > pnorm(c(0.5))-pnorm(c(-0.5)) [1] 0.3829249 In this study it has been concluded that when using the normal distribution to approximate the binomial distribution, a more accurate approximations was obtained. Moreover, it turns out that as n gets larger, the Binomial distribution looks increasingly like the Normal distribution. The normal approximation to the binomial distribution is, in fact, a special case of a more general phenomenon. The importance of employing a correction for continuity adjustment has also been investigated. It has also been viewed that using R programming, more accurate outcome of the distribution are obtained. Furthermore a number of examples has also been analyzed in order to have a better perspective on the normal approximation. Using normal distribution as an approximation can be useful, however if these conditions are not met then the approximation may not be that good in estimating the probabilities.

African Americans and Healthcare :: Papers Health Insurance Medical Essays

African Americans and Healthcare African Americans face a multidimensional health care crisis that affects the young or old, rich or poor. Too many African Americans are uninsured or underinsured. The elderly cannot afford long-term health care leaving the family to care for them. Health care cost is constantly rising and are out of control, reform is the only way out. The growing number of uninsured and underinsured is on the rise. In 1979, 11 million African americans were uninsured (Jaffe 10). Today, the number is 15 million and it is increasing every year (Jaffe 11). According to the Department of Health and Human Services, thirteen million blacks in America have health care and fourteen million do not (Fitzgerald 31). Also, those who are insured today may be at risk tomorrow if their employer drops coverage, or the head of the household changes or loses their job. Most blacks in the United States who are uninsured simply cannot receive health care at an affordable price because their employer does not offer it and self-insurance cost much more. The lack of adequate insurance can be devastating to families both in financial terms and in terms of timely access to needed health care (Jaffe 12). Altogether, collection agencies report every year that most blacks are in debt due to unpaid medical bills, because they are not insured or they are underinsured. African American senior citizens face a health care crisis too. They have worked all of their lives to secure retirement, but their retirement has been threatened because of the rising cost of long-term medical care. Insurance companies have failed to provide affordable long-term care, protection that most senior citizens need. This lack of long term care and affordability has been a serious problem for the health care system. In some cities, the shortage of hospital beds is so serious that it is common for patients to stay in emergency rooms before they can be admitted to an inpatient room (Drake 109). More than one thousand hospital beds are occupied by people who could be better care for in nursing homes or through home health care (Drake 110). Of the disabled elderly 1.3 million reside in nursing homes (Drake 10). These patients are unable to perform two or more of the basic activities of daily living without assistance.

Uncle Toms Cabin: Stowes Paradoxical Christian Message Essay

Uncle Tom's Cabin: Stowe's Paradoxical Christian Message Perhaps the greatest criticism levied against Stowe's Uncle Tom's Cabin is that it comprises of nothing more than Victorian sentimentality, and that the death of its two moral exemplars, Tom and Little Eva, do little which actually remedies the injustices of slavery. Critic Ann Douglas sees the novel as emblematic of the "feminization of American culture," which in religious terms figures as "a move away from the morally forceful Calvinism to the sloppiness of the humanistic cult of gentle Jesus" (Rachel Bowlby's paraphrase, 205). In order to recoup the novel from such charges, critics such as Jane Tompkins have attempted to demonstrate that the novel's coupling of sentimentality and Christianity results in far more than a luxuriating in lachrymose emotions. For Tompkins, the force behind the novel's sentimental Christianity is its subversion of the power hierarchy. Incidents like the deaths of Tom and Little Eva enact a "theory of power" in which "the powerless die to save the power ful and corrupt, and thereby show themselves more powerful than those they save" (128). Thus, the traditional locus of power, is in effect, decentered, and religious faith gives marginalized figures like slaves, children, and women a power, to which in strictly secular terms, they have no access. One problem with readings which stress the salvific function of the deaths of Tom and Little Eva is their failure to account for the novel's self-conscious acknowledgment of the social forces which constantly challenge the brand of Christianity which it advocates. The Christian message of Uncle Tom's Cabin is ultimately paradoxical. On the one hand, the examples of Tom and Little Eva demonstrate ... ...f sustaining one's Christianity within the context of slavery, as well as the limitations of the individual's power to challenge such a large institution. George, in deferring his acceptance of Christianity until he reaches a place of freedom, ultimately comes closest to Stowe's agenda of establishing a true Christian nation, uncorrupted by slavery, on earth. Works Cited: Bowlby, Rachel. "Breakfast in America--Uncle Tom's Cultural Histories." Nation and Narration. Ed. Homi K. Bhabha. New York, NY: Routledge Press, 1990, 197-212. O'Connel, Catherine E. "`The Magic of the Real Presence of Distress': Sentimentality and Competing Rhetorics of Authority." The Stowe Debate. Eds. Mason I. Lowance, Jr., Ellen E Westbrook, R.C. De Prospo. Amherst, MA: U. Massachusetts Press, 1994, 13-36. Tompkins, Jane. Sensational Designs. New York, NY: Oxford U. Press, 1985.

Hypocrisy in The Enormous Radio Essay -- Enormous Radio Essays

Hypocrisy in The Enormous Radio  Ã‚     Ã‚  Ã‚   In the short story, "The Enormous Radio," by John Cheever, the radio acts as a wake up call for Jim and Irene Westcott. Even though they believe that their life is better than their neighbors’ lives, the radio proves them wrong. The Westcott’s life can be compared to a freshly painted ten-year-old car: nice and shiny on the outside but falling apart on the inside. In the beginning, Jim and Irene seem to have a good life with no problems; they seem to be average, ordinary people. The story states, "The Westcotts differed from their friends, their classmates, and their neighbors only in an interest they shared in serious music" (Cheever 812). This already hints that they might have their share of problems, especially since they are almost exactly like everyone they know. One reason why they might think they have a better life is because of their music, but in actuality, this is where their conflicts arise. Once they get the new radio, everything seems fine, even though they can hear all of the neighbors’ conversations. The Westcotts ...

Solutions Hmwk

ISDS-361AExercises 1. Mean, Median, Mode, Range, Variance & SD Panayiotis Skordi 1. A basketball player has the following points for seven games: 20, 25, 32, 18, 19, 22, 30 Compute the following measures of central location: a. mean b. median c. mode Answers a. Mean[pic] b. Median[pic] c. Mode There is no mode. 2. Consider the following population of measurements: 162, 152, 177, 157, 184, 176, 165, 181, 170, 163 a. compute the mean b. compute the median Answers a. Mean[pic] b. Median [pic] [pic] 3. The following data represent the number of children in a sample of 10 families from a certain community: , 2, 1, 1, 5, 3, 0, 1, 0, 2 a. compute the range b. compute the variance c. compute the standard deviation Answers a. Range [pic] b. Variance[pic] Remember that [pic] [pic][pic][pic][pic] 14 2. 14. 41 22 0. 10. 01 31-0. 90. 81 41-0. 90. 81 55 3. 19. 61 63 1. 11. 21 70-1. 93. 61 81-0. 90. 81 90-1. 93. 61 102 0. 10. 01 Total1924. 9 [pic] Method 2[pic] [pic][pic][pic] 1416 224 311 411 5525 639 700 811 900 1024 Total1961 [pic] This is the same answer – as we would expect. c. The standard deviation is [pic] 4. Consider the following population of measurements: 162, 152, 177, 157, 184, 176, 165, 181, 170, 163 a. ompute the standard deviation Answer [pic] Remember that [pic] [pic][pic][pic][pic] |1 |162 | |-6. 70 | |44. 89 | |2 |152 | |-16. 70 | |278. 89 | |3 |177 | |8. 30 | |68. 89 | |4 |157 | |-11. 70 | |136. 89 | |5 |184 | |15. 30 | |234. 09 | |6 |176 | |7. 30 | |53. 29 | |7 |165 | |-3. 0 | |13. 69 | |8 |181 | |12. 30 | |151. 29 | |9 |170 | |1. 30 | |1. 69 | |10 |163 | |-5. 70 | |32. 49 | | | | | | | | | | | | | | | |Total |1687. 0 | | | |1016. 10 | [pic] The standard deviation is the square root of the variance [pic] Method 2[pic] pic][pic][pic] |1 |162 | |26244 | |2 |152 | |23104 | |3 |177 | |31329 | |4 |157 | |24649 | |5 |184 | |33856 | |6 |176 | |30976 | |7 |165 | |27225 | |8 |181 | |32761 | |9 |170 | |28900 | |10 |163 | |26569 | | | | | | | | | | | | |1687 | |285613 | [pic] As before, the standard deviation is the square root of the variance pic] 5. Monthly rent data in dollars for a sample of one-bedroom apartments in a small town in Iowa are as follows: 220, 216, 220, 205, 210, 240, 195, 235, 204 and 205. a. compute the sample monthly average rent. b. compute the sample median. c. what is the mode? Answers a. Average [pic] [pic][pic] |1 |220 | |2 |216 | |3 |220 | |4 |205 | |5 |210 | |6 |240 | |7 |195 | |8 |235 | |9 |204 | |10 |205 | | | | | |2,150 | | | [pic] b. MEDIAN 195 204 205 205 210 216 220 220 235 240 [pic] c. MODE205 and 220 (bimodal) 6. A sample of 25 families was asked how many pets they owned. Their responses were summarized in the following table: |Number of Pets |0 |1 |2 |3 |4 |5 | |Number of Families |3 |10 |5 |4 |2 |1 | Determine the mean, median and the mode of the number of pets owned per family. ANSWERS a. MEAN[pic] [pic][pic][pic][pic] 0 |3 |0 | |1 |10 |10 | |2 |5 |10 | |3 |4 |12 | |4 |2 |8 | |5 |1 |5 | | | | | | |25 |45 | [pic] b. MEDIAN1 median is 13th observation. c. MODE 1 most families have 1 pet. 7.The following data represent the ages in years of a sample of 25 employees from a government department: 31,43,56,23,49,42,33,61,44,28,48,38,44,35,40,64,52,42,47,39,53,27,36,35 and 20. Construct a relative frequency distribution for the data, using five class intervals and the value 20 as the lower limit of the first class. |20 | | | |23 | | | |27 | | | |28 | |4 | |31 | | | |33 | | | |35 | | | 35 | | | |36 | | | |38 | | | |39 | |7 | |40 | | | |42 | | | |42 | | | |43 | | | |44 | | | |44 | | | |47 | | | |48 | | | |49 | |9 | |52 | | | 53 | | | |56 | |3 | |61 | | | |64 | |2 | |Class Limits |Frequency |Relative Frequency | | | | | |20 upto 30 |4 |0. 16 | |30 upto 40 |7 |0. 28 | |40 upto 50 |9 |0. 36 | |50 upto 60 |3 |0. 12 | |60 upto 70 |2 |0. 8 | | | | | | |25 |1. 00 | 8. How many hours a day do college students spend studying? That question was asked to 100 college students, and the data are p resented in the table below. Hours per DayFrequency 0-225 2-448 4-615 6-89 8-103 a. compute the range b. compute the average hours per day spent studying. c. compute the variance of the number of hours per day spent studying d. find the median e. find the mode Answers a. The range is 10-0 = 10 b. Average[pic] [pic][pic][pic][pic][pic] 1 |0-2 |25 |1 |25 | |2 |2-4 |48 |3 |144 | |3 |4-6 |15 |5 |75 | |4 |6-8 |9 |7 |63 | |5 |8-10 |3 |9 |27 | | | | | | | | | |100 | |334 | [pic] c. compute the variance of the number of hours per day spent studying [pic] note that [pic] [pic][pic][pic][pic][pic][pic][pic] |1 |0-2 |25 |1 |-2. 34 |5. 4756 |136. 89 | |2 |2-4 |48 |3 |-0. 34 |0. 1156 |5. 488 | |3 |4-6 |15 |5 |1. 66 |2. 7556 |41. 334 | |4 |6-8 |9 |7 |3. 66 |13. 3956 |120. 5604 | |5 |8-10 |3 |9 |5. 66 |32. 0356 |96. 1068 | | | | | | | | | | | |100 | | |53. 7780 |400. 4400 | [pic] Method 2 [pic] [pic][pic][pic][pic][pic][pic] 1 |0-2 |25 |1 |25 |25 | |2 |2-4 |48 |3 |144 |432 | |3 |4-6 |15 |5 |75 |37 5 | |4 |6-8 |9 |7 |63 |441 | |5 |8-10 |3 |9 |27 |243 | | | | | | | | | | |100 | |334 |1516 | [pic] d. Find the MEDIAN3 e. Find the MODE3 9. The following data is for the daily room rate in $, for staying at various hotels in downtown LA Hotels Offering RateDaily room rate 130 50 1470 690 3110 4130 1150 1170a. Compute the range b. Compute the average daily room rate. c. Compute the variance of the room rate. d. Find the median. e. Find the mode. Answers a. Range 170-30 =140 b. Average[pic]where [pic] [pic][pic][pic][pic] | 1 |1 |30 |30 | |2 |7 |50 |350 | |3 |14 |70 |980 | |4 |6 |90 |540 | |5 |3 |110 |330 | |6 |4 |130 |520 | |7 |1 |150 |150 | 8 |1 |170 |170 | | | | | | | |37 | |3070 | [pic] c. Variance of the room rate [pic] [pic][pic][pic][pic][pic][pic] |1 |1 |30 |-52. 9730 |2806. 1359 |2806. 1359 | |2 |7 |50 |-32. 9730 |1087. 2169 |7610. 5186 | |3 |14 |70 |-12. 9730 |168. 2980 |2356. 1724 | |4 |6 |90 |7. 0270 |49. 3791 |296. 747 | |5 |3 |110 |27. 0270 |730. 4602 |2191. 3806 | |6 |4 |130 |47. 0270 |2211. 5413 |8846. 1651 | |7 |1 |150 |67. 0270 |4492. 6224 |4492. 6224 | |8 |1 |170 |87. 0270 |7573. 7034 |7573. 7034 | | | | | | | | | |37 | |136. 2162 | |36172. 9730 | [pic]Method 2 [pic] [pic][pic][pic][pic][pic] |1 |1 |30 |30 |900 | |2 |7 |50 |350 |17500 | |3 |14 |70 |980 |68600 | |4 |6 |90 |540 |48600 | |5 |3 |110 |330 |36300 | |6 |4 |130 |520 |67600 | |7 |1 |150 |150 |22500 | |8 |1 |170 |170 |28900 | | | | | | | | |37 | |3,070 |290,900 | [pic] d. Find the MEDIAN70 e. Find the mode70 Solutions Hmwk ISDS-361AExercises 1. Mean, Median, Mode, Range, Variance & SD Panayiotis Skordi 1. A basketball player has the following points for seven games: 20, 25, 32, 18, 19, 22, 30 Compute the following measures of central location: a. mean b. median c. mode Answers a. Mean[pic] b. Median[pic] c. Mode There is no mode. 2. Consider the following population of measurements: 162, 152, 177, 157, 184, 176, 165, 181, 170, 163 a. compute the mean b. compute the median Answers a. Mean[pic] b. Median [pic] [pic] 3. The following data represent the number of children in a sample of 10 families from a certain community: , 2, 1, 1, 5, 3, 0, 1, 0, 2 a. compute the range b. compute the variance c. compute the standard deviation Answers a. Range [pic] b. Variance[pic] Remember that [pic] [pic][pic][pic][pic] 14 2. 14. 41 22 0. 10. 01 31-0. 90. 81 41-0. 90. 81 55 3. 19. 61 63 1. 11. 21 70-1. 93. 61 81-0. 90. 81 90-1. 93. 61 102 0. 10. 01 Total1924. 9 [pic] Method 2[pic] [pic][pic][pic] 1416 224 311 411 5525 639 700 811 900 1024 Total1961 [pic] This is the same answer – as we would expect. c. The standard deviation is [pic] 4. Consider the following population of measurements: 162, 152, 177, 157, 184, 176, 165, 181, 170, 163 a. ompute the standard deviation Answer [pic] Remember that [pic] [pic][pic][pic][pic] |1 |162 | |-6. 70 | |44. 89 | |2 |152 | |-16. 70 | |278. 89 | |3 |177 | |8. 30 | |68. 89 | |4 |157 | |-11. 70 | |136. 89 | |5 |184 | |15. 30 | |234. 09 | |6 |176 | |7. 30 | |53. 29 | |7 |165 | |-3. 0 | |13. 69 | |8 |181 | |12. 30 | |151. 29 | |9 |170 | |1. 30 | |1. 69 | |10 |163 | |-5. 70 | |32. 49 | | | | | | | | | | | | | | | |Total |1687. 0 | | | |1016. 10 | [pic] The standard deviation is the square root of the variance [pic] Method 2[pic] pic][pic][pic] |1 |162 | |26244 | |2 |152 | |23104 | |3 |177 | |31329 | |4 |157 | |24649 | |5 |184 | |33856 | |6 |176 | |30976 | |7 |165 | |27225 | |8 |181 | |32761 | |9 |170 | |28900 | |10 |163 | |26569 | | | | | | | | | | | | |1687 | |285613 | [pic] As before, the standard deviation is the square root of the variance pic] 5. Monthly rent data in dollars for a sample of one-bedroom apartments in a small town in Iowa are as follows: 220, 216, 220, 205, 210, 240, 195, 235, 204 and 205. a. compute the sample monthly average rent. b. compute the sample median. c. what is the mode? Answers a. Average [pic] [pic][pic] |1 |220 | |2 |216 | |3 |220 | |4 |205 | |5 |210 | |6 |240 | |7 |195 | |8 |235 | |9 |204 | |10 |205 | | | | | |2,150 | | | [pic] b. MEDIAN 195 204 205 205 210 216 220 220 235 240 [pic] c. MODE205 and 220 (bimodal) 6. A sample of 25 families was asked how many pets they owned. Their responses were summarized in the following table: |Number of Pets |0 |1 |2 |3 |4 |5 | |Number of Families |3 |10 |5 |4 |2 |1 | Determine the mean, median and the mode of the number of pets owned per family. ANSWERS a. MEAN[pic] [pic][pic][pic][pic] 0 |3 |0 | |1 |10 |10 | |2 |5 |10 | |3 |4 |12 | |4 |2 |8 | |5 |1 |5 | | | | | | |25 |45 | [pic] b. MEDIAN1 median is 13th observation. c. MODE 1 most families have 1 pet. 7.The following data represent the ages in years of a sample of 25 employees from a government department: 31,43,56,23,49,42,33,61,44,28,48,38,44,35,40,64,52,42,47,39,53,27,36,35 and 20. Construct a relative frequency distribution for the data, using five class intervals and the value 20 as the lower limit of the first class. |20 | | | |23 | | | |27 | | | |28 | |4 | |31 | | | |33 | | | |35 | | | 35 | | | |36 | | | |38 | | | |39 | |7 | |40 | | | |42 | | | |42 | | | |43 | | | |44 | | | |44 | | | |47 | | | |48 | | | |49 | |9 | |52 | | | 53 | | | |56 | |3 | |61 | | | |64 | |2 | |Class Limits |Frequency |Relative Frequency | | | | | |20 upto 30 |4 |0. 16 | |30 upto 40 |7 |0. 28 | |40 upto 50 |9 |0. 36 | |50 upto 60 |3 |0. 12 | |60 upto 70 |2 |0. 8 | | | | | | |25 |1. 00 | 8. How many hours a day do college students spend studying? That question was asked to 100 college students, and the data are p resented in the table below. Hours per DayFrequency 0-225 2-448 4-615 6-89 8-103 a. compute the range b. compute the average hours per day spent studying. c. compute the variance of the number of hours per day spent studying d. find the median e. find the mode Answers a. The range is 10-0 = 10 b. Average[pic] [pic][pic][pic][pic][pic] 1 |0-2 |25 |1 |25 | |2 |2-4 |48 |3 |144 | |3 |4-6 |15 |5 |75 | |4 |6-8 |9 |7 |63 | |5 |8-10 |3 |9 |27 | | | | | | | | | |100 | |334 | [pic] c. compute the variance of the number of hours per day spent studying [pic] note that [pic] [pic][pic][pic][pic][pic][pic][pic] |1 |0-2 |25 |1 |-2. 34 |5. 4756 |136. 89 | |2 |2-4 |48 |3 |-0. 34 |0. 1156 |5. 488 | |3 |4-6 |15 |5 |1. 66 |2. 7556 |41. 334 | |4 |6-8 |9 |7 |3. 66 |13. 3956 |120. 5604 | |5 |8-10 |3 |9 |5. 66 |32. 0356 |96. 1068 | | | | | | | | | | | |100 | | |53. 7780 |400. 4400 | [pic] Method 2 [pic] [pic][pic][pic][pic][pic][pic] 1 |0-2 |25 |1 |25 |25 | |2 |2-4 |48 |3 |144 |432 | |3 |4-6 |15 |5 |75 |37 5 | |4 |6-8 |9 |7 |63 |441 | |5 |8-10 |3 |9 |27 |243 | | | | | | | | | | |100 | |334 |1516 | [pic] d. Find the MEDIAN3 e. Find the MODE3 9. The following data is for the daily room rate in $, for staying at various hotels in downtown LA Hotels Offering RateDaily room rate 130 50 1470 690 3110 4130 1150 1170a. Compute the range b. Compute the average daily room rate. c. Compute the variance of the room rate. d. Find the median. e. Find the mode. Answers a. Range 170-30 =140 b. Average[pic]where [pic] [pic][pic][pic][pic] | 1 |1 |30 |30 | |2 |7 |50 |350 | |3 |14 |70 |980 | |4 |6 |90 |540 | |5 |3 |110 |330 | |6 |4 |130 |520 | |7 |1 |150 |150 | 8 |1 |170 |170 | | | | | | | |37 | |3070 | [pic] c. Variance of the room rate [pic] [pic][pic][pic][pic][pic][pic] |1 |1 |30 |-52. 9730 |2806. 1359 |2806. 1359 | |2 |7 |50 |-32. 9730 |1087. 2169 |7610. 5186 | |3 |14 |70 |-12. 9730 |168. 2980 |2356. 1724 | |4 |6 |90 |7. 0270 |49. 3791 |296. 747 | |5 |3 |110 |27. 0270 |730. 4602 |2191. 3806 | |6 |4 |130 |47. 0270 |2211. 5413 |8846. 1651 | |7 |1 |150 |67. 0270 |4492. 6224 |4492. 6224 | |8 |1 |170 |87. 0270 |7573. 7034 |7573. 7034 | | | | | | | | | |37 | |136. 2162 | |36172. 9730 | [pic]Method 2 [pic] [pic][pic][pic][pic][pic] |1 |1 |30 |30 |900 | |2 |7 |50 |350 |17500 | |3 |14 |70 |980 |68600 | |4 |6 |90 |540 |48600 | |5 |3 |110 |330 |36300 | |6 |4 |130 |520 |67600 | |7 |1 |150 |150 |22500 | |8 |1 |170 |170 |28900 | | | | | | | | |37 | |3,070 |290,900 | [pic] d. Find the MEDIAN70 e. Find the mode70

Cause and Consequences of urbanization in Scotland Essay

This essay will explore relevant cause and consequences of urbanisation in Scotland from 1700-1860. A dictionary-defined term would be â€Å"the social process whereby cities grow and societies become more urban.†(1. 30/08/2005). Scotland went through huge political and economical changes from the 1700’s onwards. The country went from being a rural, agricultural society with an estimated population of 1.2 million in 1755, to being urbanised, with the population rising to over 2.6 million in 1841(Lenman, p281, 2001). This figure is what makes the urbanisation of Scotland so interesting. What were the main factors that caused the population to grow so rapidly? The expansion of population over such a short period and the social changes that occurred with this. The great Agrarian and Industrial revolutions had a major part’s to play in the urbanisation of Scotland and this essay will show some enlightenment on why it was so profoundly noticeable in Scotland. Another point that will be investigated is the consequences of urbanisation, how the country ultimately became a modern capitalised country from its rural beginnings. Before and up until 1750, Scotland was very much a feudalistic country. Lords rented tenants enough land for them to produce food to survive. In return, the tenant would have to labour the Lord’s land as well as his own. The Landlord would reap the benefits, the tenant would survive, and as the majority of the people depended on the land as their lively-hood, it was a means to survival. As Devine states,_† In 1750 only one Scot in eight lived in a town (population of 4000 or over) and there was only four towns with more than 10000 inhabitants†_ (Devine, 1999, p125). This shows the enormity of Scots who were living in rural communities, with the main labour being in agriculture, weaving and fishing. The changes to agriculture began with those known as the improvers, whose main outlook was to modernise the way the land was cultivated. As the population of the country began to accelerate quickly, the improvers were looking to produce mass food instead of the old way of cultivation. During the period between 1790-1840 new farming equipment was introduced and the land that was formally cultivated  using the â€Å"infield-outfield and rug and furrow method† was improved by enclosing the land into fields making it more productive for crops and for livestock Crop rotations were also introduced which was making use of the land at all times. The introduction of single tenant farming as opposed to ferm-touns meant the beginning of the clearances, as well as agricultural tools becoming more efficient. The introduction of threshing machines reduced manual labour and â€Å"the Small’s plough – a two horse plough replaced the Scot’s plough which required a team of oxen and horses† (Devine, 1998, p138). These new ideas did create more food but they also left people homeless and jobless, as there was less labour needed, which left people no choice but to move on into the towns and cities where industry had began creating jobs. The growth of the towns and cities were intricately linked with the agrarian revolution as the mass population relied on the land for the food it produced. The other main point that Devine makes is that as the agricultural market started to accelerate, the need for exchange centres that provided legal, commerce and financial facilities for the rural communities became more prominent, so several towns including Perth, Ayr and Dumfries became the provider of these services. This again contributed to expansion of towns, as people were required to work and live in the towns to facilitate these positions (Devine 1998, p32) Therefore, we can gather that three major changes occurred at the same time and they contributed towards urbanisation in Scotland: The agrarian revolution along with the population growth, and the expansion of the manufacturing industry. As T.M Devine States, _Urbanisation could not have taken place without a substantial increase in food production to sustain the needs of those who did not cultivate their own food supplies. At the same time, agrarian productivity had to improve in order to release a growing proportion of the population for non-agricultural tasks in towns and cities._ (Devine, 1998, p32) Along with theses changes the manufacturing industry began to grow rapidly. Scotland was a major player in the transatlantic trading industry and due to its geographical position, it was booming in the tobacco trade and it would go on to prosper in cotton and linen too. Scotland’s Geographical position at this time was very important as it is situated between the Atlantic and Europe, which meant trading from one to the other, was very successful. The two major factor’s of the Industrial Revolution were, the textile industry and the productivity of the steam engine, which was revolutionised by James Watt in 1769 (Watt James online, 2005). Textiles factories and coalmines could produce more goods and they did not need to be near a water source in order to run. Due to this, the larger towns and cities began to grow rapidly. _Greenock in 1700 had a population of 2000 and by 1831 it had rose to 27500._ _Glasgow went from 31700 to 147000._ _Paisley went from 6800 to 47000._ _Kilmarnock went from 4400 to 12700_ _Falkirk went from 3900 to 11500. All within the time period from 1740-1850 (Devine 1998, p35)_ The population growth over the short period is the most significant point here as this is what made urbanisation in Scotland different. There are many different factors that affected the population growth but some are more significant than others are. Irish Immigration was very prominent and the migration of people from the rural areas had a major impact. For example:_† The majority of the migrants were young adults more concentrated in the marriageable and childbearing age groups than were the native inhabitants. High Migration because of its age composition was therefore likely to fuel natural increase in the urban areas_†.(Devine 1998,p41) At the same time the  highlanders were leaving the land either through force as the lord’s applied the new cultivation techniques to the land or through choice. The majority chose to immigrate to America; this did not affect the population growth as many Irish migrants were coming to Scotland looking for employment in the bo oming industries. â€Å"_Urbanisation meant more jobs, a wider diversity of social contacts and infinitely greater colour and excitement in the lives of the masses_† (Devine 1998 p43) Mortality rates demonstrate their huge impact on population growth too. It has been suggested that lower death rates, through natural immunity to disease highly contributed to urbanisation, as in the early 1800’s the death rate had fallen to 25 per 1000. This suggests that natural immunity and high levels of unemployment accelerated the population growth (Devine, 1998, p48). The effect of industrialisation was economically good for the country, but with it came poverty. The majority of the working class lived in overcrowded housing areas known as slums with no sanitation, and were rife with disease. As Devine argues, during periods of industrial recession when employment had slumped, there were also periods of disease epidemic. These began in 1817-1820(Typhoid), 1826-27(Typhoid) and in 1830-1832, a cholera epidemic that wiped out 10000 people. Periods of recession run parallel, the first being 1816-1818, 1825 and then 1836 (Devine, 1999, p168). In 1839, Death rates rose to 29 per 1000. People were forced to live in abominable living conditions with huge sanitations problems, the towns and cities could not cope with the urban growth and disease was the outcome. Overcrowded, sub-divided housing was a problematic issue in all the major Towns and Cities, especially in Glasgow. _†I did not believe until I visited Glasgow, that so large an amount of filt h, crime, misery and disease existed in one spot in any one civilised country† (_Butt J, 1987 p41-42). People were customised to living in filthy dark, damp squalid conditions amongst disease. As the periods of recession were leaving thousands out of work in a state of poverty, the poor law amendment act was passed in 1845, which replaced the old poor relief laws of the parishes taking responsibly for the  poor. The new law allowed a claim to be made under supervision of a board of examiners, it came in the form of indoor relief, which would be admission to a poorhouse if subject had lost the ability to work, and outdoor relief, which was for short-term illness, and this may have been in the form of payment or medicine. It could be argued that the industrial revolution was the birth of the working class and capitalism in this country. Those who owned the factories and docks made a great profit and a middle class lifestyle was adopted. This could be said to be the division of the classes, with the help of the industrial revolution, people developed a â€Å"working† class or â €Å"middle† class attitude, In conclusion, the evidence points out that several major factors occurred that accelerated the urban growth of the nation. The Agrarian revolution started the mass migrating and the industrial revolution provided the work force in order for capitalism to evolve. The consequences of urbanisation were overwhelming, yes the economy did thrive, but at what cost to the working class people, death, disease and misery.