Identifying Problems When Obtaining Population Parameters

Identifying Problems When Obtaining Population Parameters We estimate population parameters, such as the mean, based on the sample statistics. It is difficult to get a precise value or point estimation of these figures. A more practical and informative approach is to find a range of values in which we expect the population parameters will fall. Such a range of values is called a confidence interval. 1. CONFIDENCE INTERVAL Definition The confidence interval is a range of values constructed from sample data so that the population parameter is likely to occur within that range at a specified probability. The specified probability is called the level of confidence. The shape of the probability distribution of the sample mean allows us to specify an interval of specific probability that the population mean,  µ, will fall into. 1.1 Large Sample Or Standard Deviation Is Known Case 1: The standard deviation à Ã†â€™ is known; or It is a large sample (i.e. at least 30 observations). The Central Limit Theorem states that the sampling distribution of the sample means is approximately normal. We can use the tables in the Appendix to find the appropriate Z value. Key Points The standard normal distribution allows us to draw the following conclusions: 68% of the sample means will be within 1 standard deviations of the population mean,  µ. 95% of the sample means will be within 1.96 standard deviations of the population mean,  µ. 99% of the sample means will lie within 2.58 standard deviations of the population mean. These intervals are called the confidence interval. The standard deviation above (i.e. the standard error) is referring to the standard deviation of the sampling distribution of the sample mean. Locating 0.475 in the body of the table, read the corresponding row and column values, the value is 1.96. Thus, the probability of finding a Z value between 0 and 1.96 is 0.475. Likewise, the probability of being in the interval between -1.96 and 0 is also 0.475. When we combine these two, the probability of being in the interval of -1.96 to 1.96 is therefore 0.95. 1.1.1 How do you compute a 95% confidence interval? Assume our research involves the annual starting salary of business graduates in a local university. The sample mean is $39,000, while the standard deviation of the sample mean is $250. Assume our sample contains more than 30 observations. The 95% confidence interval is between $38,510 and $39,490. Found by $39,000 +/- 1.96($250) In most situations, the population standard deviation is not available, so we estimate it as follows: (Standard Error) Conclusions: 95% confidence interval 99% confidence interval Confidence interval for the population mean (n > 30) Z depends on confidence level Example 1 The Hong Kong Tourist Association wishes to have information on the mean annual income of tour guides. A random sample of 150 tour guides reveals a sample mean of $45,420. The standard deviation of this sample is $2,050. The association would like answers to the following questions: (a) What is the population mean? The best estimate of the unknown population value is the corresponding sample statistic. The sample mean of $45,420 is a point estimate of the unknown population mean. (b) What is a reasonable range of values for population mean? The Association decides to use the 95% level of confidence. To determine the corresponding confidence interval, we use the formula: The endpoints would be $45,169 and $45,671 and they are called confidence limits. We could expect about 95% of these confidence intervals contain the population mean. About 5% of the intervals would not contain the population mean annual income, i.e. the  µ. Figure 2 Probability distribution of population mean 1.2 Small Sample Or Standard Deviation Is Unknown Case 2: The sample is small (i.e. less than 30 observations) or, the population standard deviation is not known. The correct statistical procedure is to replace the standard normal distribution with the t distribution. The t distribution is a continuous distribution with many similarities to the standard normal distribution. 1.2.1 Standard normal distribution versus t distribution Figure 3 Z distribution versus t distribution The t distribution is flatter and more spread out than the standard normal distribution. The standard deviation of the t distribution is larger than the normal distribution. Confidence interval for a sample with unknown population mean, à Ã†â€™. The confidence interval is Assume the sample is from a normal population. Estimate the population standard deviation (à Ã†â€™) with the sample standard deviation (s). Use t distribution rather than the Z distribution. Example 2 A shoe maker wants to investigate the useful life of his products. A sample of 10 pairs of shoes that had been walked for 50,000 km showed a sample mean of 0.32 inch of sole remaining with a standard deviation of 0.09 cm. Constructing a 95% confidence interval for the population mean, would it be reasonable for the manufacturer to conclude that after 50,000 km the population mean amount of sole remaining is 0.3 cm? Assume the population distribution is normal. The sample standard deviation is 0.09 cm. There are only 10 observations and hence, we use t distribution Estimation: = 0.32, s = 0.09, and n = 10. Step 1: Locate t by moving across the row for the level of confidence required (i.e. 95%). Step 2: The column on the left margin is identified as df. This refers to the number of degrees of freedom. The number of degree of freedom is the number of observations in the sample minus the number of samples, written n-1.(i.e. 10-1=9). Step 3: Confidence Interval = The endpoints of the confidence interval are 0.256 and 0.384. Step 4: Interpretation the manufacturer can be reasonably sure (95% confident) that the mean remaining tread depth is between 0.256 and 0.384 cm. Because 0.3 is in this interval, it is possible that the mean of the population is 0.3. 2. CHOOSING AN APPROPRIATE SAMPLE SIZE The necessary sample size depends on three factors: Level of confidence wanted: To increase level of confidence, increase n. Margin of error the researcher will tolerate: To reduce allowable error, increase n. Variability in the population being studied: For a more widely dispersed sample, increase n. We can express the interaction among these three factors and the sample size in the following formula: Sample size for estimating the population mean, Note: n: Sample size Z: Standard normal value S: Estimate of population standard deviation E: Maximum allowable error Example 3 An accounting student wants to know the mean amount that independent directors of small companies earn per month as remuneration for being a director. The error in estimating the mean is to be less than $100 with a 95% level of confidence. The student found a report by the government that estimated the standard deviation to be $1000. What is the required sample size? Maximum allowable error, E, is $100. Value of Z for a 95% level of confidence is 1.96, and the estimate of the standard deviation is $1000. Substitute into , we get n = [ (1.96) (1000) ] 2 = 19.62 = 384.16 100 The sample of 385 is required to meet the requirements. If the students want to increase the level of confidence, e.g. 99%, this requires a larger sample. Z = 2.58, so n = [ (2.58) (1000) ] 2 = 25.82 = 665.64 100 Sample = 666 3. WHAT IS A HYPOTHESIS? Definitions Hypothesis is a statement about a population parameter developed for the purpose of testing. Hypothesis testing is a procedure based on sample evidence and probability theory to determine whether the hypothesis is a reasonable statement. In statistical analysis, we always make a claim about the population parameters, i.e. a hypothesis. We collect data and then use the data to test the assertion. 4.1 Five-Step Procedure For Testing A Hypothesis Figure 4 How to test a hypothesis 4.1.1 Step 1: State null hypothesis (H0) and alternative hypothesis (H1) The first step is to state the hypothesis being tested. It is called the null hypothesis. We either reject or fail to reject the null hypothesis. Failing to reject the null hypothesis does not prove that H0 is true. The null hypothesis is a statement that is not rejected unless our sample data provide convincing evidence that it is false. The alternative hypothesis is a statement that is accepted if the sample data provide sufficient evidence that the null hypothesis is false. Example 4 A journal has disclosed that the mean age of commercial helicopters is 15 years. A statistical test of this statement would first need to determine the null and the alternate hypotheses. The null hypothesis represents the current or reported condition. It is written H0:  µ = 15. The alternate hypothesis is that the statement is not true, i.e. H1:  µ à ¢Ã¢â‚¬ °Ã‚   15. 4.1.2 Step 2: Select a level of significance The level of significance is the probability of rejecting the null hypothesis when it is true. A decision is made to use the 5% level, 1% level, 10% level or any other level between 0 and 1. We must decide on the level of significance before formulating a decision rule and collecting sample data. Type I error: Rejecting the null hypothesis, H0, when it is true. Type II error: Accepting the null hypothesis when it is false. Example 5 Suppose AA Watch Ltd has informed bracelet suppliers to bid for contract on the supply of a large amount of bracelets. Suppliers with the lowest bid will be awarded a sizable contract. Suppose the contract specifies that the watch producers quality-assurance department will take samples of the shipment. H0: The shipment of bracelet contains 6% or less substandard bracelets. H1: More than 6% of the boards are defective. A sample of 50 bracelets received August 2 from BB Metals Ltd revealed that four bracelets, or 8%, were substandard. The shipment was rejected because it exceeded the maximum of 6% substandard bracelets. If the shipment was actually substandard, the decision to return the bracelets to the supplier was correct. However, suppose the four substandard bracelets selected in the sample of 50 were the only substandard bracelets in the shipment of 4,000 bracelets. Then only 1/10 of 1% were defective (4/4000 = 0.001). In that case, less than 6% of the entire shipment was substandard and rejecting the shipment was an error. We may have rejected the null hypothesis that the shipment was not substandard when we should have accepted the null hypothesis. By rejecting a true null hypothesis, we committed a Type I error. AA Watch Ltd would commit a Type II error if, unknown to the company an incoming shipment of bracelet from BB Metals Ltd contained 15% substandard bracelets, yet the shipment was accepted. How could this happen? Suppose two out of the 50 bracelets in the sample (4%) tested were substandard, and 48 out of the 50 were good bracelets. As the sample contained less than 6% substandard bracelets, the shipment was accepted but it could be purely by chance that the 48 good bracelets selected in the sample were the only acceptable ones in the entire shipment. In conclusion: Null Hypothesis Accepts H0 Rejects H0 H0 is true Correct decision Type I error H0 is false Type II error Correct decision 4.1.3 Step 3: Select the test statistics There are many test statistics. In this chapter, we use both Z and t as the test statistic. Definition A test statistic is a value, determined from sample information, used to determine whether to reject the null hypothesis. In hypothesis testing for the mean ( µ) when à Ã†â€™ is known or the sample size is large, the test statistic Z is computed by: The Z value is based on the sampling distribution of , which follows the normal distribution when the sample is reasonably large with a mean () equal to  µ, and a standard deviation , which is equal to . We can thus determine whether the difference between and  µ is statistically significant by finding the number of standard deviations is from  µ, using the formula above. 4.1.4 Step 4: Formulate the decision rule Definition A decision rule is a statement of the specific conditions under which the null hypothesis is rejected and the conditions under which it is not rejected. The region or area of rejection defines the location of all those values that are so large or so small that the probability of their occurrence under a true null hypothesis is rather remote. The area where the null hypothesis is not rejected is to the left of 1.65. The area of rejection is to the right of 1.65. A one-tailed test is being applied. The 0.05 level of significance was chosen. The sampling distribution of the statistic Z is normally distributed. The value 1.65 separates the regions where the null hypothesis is rejected and where it is not rejected. The value 1.65 is the critical value. The critical value is the dividing point between the region where the null hypothesis is rejected and the region where it is not rejected. Figure 5 Area of rejection for the null hypothesis 4.1.5 Step 5: Make a decision The final step in hypothesis testing is computing the test statistic, comparing it to the critical value, and making a decision to reject or not to reject the null hypothesis. Based on the information, Z is computed to be 2.34, the null hypothesis is rejected at the 0.05 level of significance. The decision to reject H0 was made because 2.34 lies in the region of rejection, i.e. beyond 1.65. We would reject the null hypothesis, reasoning that it is highly improbable that a computed Z value this large is due to sampling variation. Had the computed value been 1.65 or less, say 0.71, the null hypothesis would not be rejected. It would be reasoned that such a small computed value could be attributed to chance. Example 6 A large car leasing company wants to buy tires that average about 60,000 km of wear under normal usage. The company will, therefore, reject a shipment of tires if tests reveal that the life of the tires is significantly below 60,000 km on the average. The company would be glad to accept a shipment if the mean life is greater than 60,000 km. However, it is more concerned that it will have sample evidence to conclude that the tires will average less than 60,000 km of useful life. Thus, the test is set up to satisfy the concern of the car leasers that the mean life of the tires is less than 60,000 km. The null and alternate hypotheses in this case are written H0:  µ à ¢Ã¢â‚¬ °Ã‚ ¥ 60,000 and H1:  µ In this problem, the rejection region is pointing to the left, and is therefore in the left tail. Summary: If H1 states a direction, we use a one-tailed test. If no direction is specified in the alternate hypothesis, we use a two-tailed test. Figure 6 One-tailed test 5. TESTING FOR POPULATION MEAN WITH KNOWN POPULATION STANDARD DEVIATION 5.1 Two-tailed Test ABC Watch Ltd manufactures luxury watches at several plants in Europe. The weekly output of the Model A33 watch at the Swiss Plant is normally distributed, with a mean of 200 and a standard deviation of 16. Recently, because of market expansion, mechanisation has been introduced and employees laid off. The CEO would like to investigate whether there has been a change in the weekly production of the Model A33 watch. To put it another way, is the mean output at Swiss Plant different from 200 at the 0.01 significant levels? 5.1.1 Step 1: State null hypothesis and alternate hypothesis The null hypothesis is The population mean is 200. H0:  µ = 200. The alternate hypothesis is The mean is different from 200. H1:  µ à ¢Ã¢â‚¬ °Ã‚   200. 5.1.2 Step 2: Select the level of significance The 0.01 level of significance is used. This is ÃŽÂ ±, the probability of committing a Type I error, and it is the probability of rejecting a true null hypothesis. 5.1.3 Step 3: Select the test statistic The test statistic for the mean of a large sample is Z. Figure 7 Normalise the standard deviation 5.1.4 Step 4: Formulate the decision rule The decision rule is formulated by finding the critical values of Z from Appendix D. Since this is a two-tailed test, half of 0.01, or 0.005, is placed in each tail. The area where H0 is not rejected, i.e. area between the two tails, is 0.99. Appendix D is based on half of the area under the curve, or 0.5. Then 0.5 0.005 is 0.495, so 0.495 is the area between 0 and the critical value. The value nearest to 0.495 is 0.4951. Then read the critical value in the row and column corresponding to 0.4951. It is 2.58. Decision rule: Reject H0 if the computed Z value is not between -2.58 and +2.58. Do not reject H0 if Z falls between -2.58 and +2.58. Figure 8 Two-tailed test 5.1.5 Make a decision and interpret the result Compute Z and apply the decision rule to decide whether to reject H0. The mean number of watches produced weekly for last year is 203.5. The standard deviation of the population is 16 watches. Because 1.55 does not fall in the rejection region, H0 is not rejected. We conclude that the population mean is not different from 200. So we would report to the CEO that the sample evidence does not show that the production rate at the Swiss plant has changed from 200 per week. The difference of 3.5 units between the historical weekly production rate and the mean number of watches produced weekly for last year can reasonably be attributed to sampling error. Figure 9 Rejection regions for the two-tailed test So did we prove that production rate is still 200 per week? No! Failing to disprove the hypothesis that the population mean is 200 is not the same thing as proving it to be true. 5.2 P-value In Hypothesis Testing Definition P-value is the probability of observing a sample value as extreme as, or more extreme than, the value observed, given that the null hypothesis is true. How confident are we in rejecting the null hypothesis? This approach reports the probability of getting a value of the test statistic at least as extreme as the value actually obtained. This process compares the probability called the P-value, with the significant level. If the P-value If the P-value > significant level, H0 is not rejected. A very small P-value, such as 0.0001, indicates that there is little likelihood the H0 is true. If a P-value of 0.2033 means that H0 is not rejected, there is little likelihood that it is false. Figure 10 P-value P-value Interpretation Less than 0.1 Some evidence that H0 is not true Less than 0.05 Strong evidence that H0 is not true Less than 0.01 Very strong evidence that H0 is not true Less than 0.001 Extremely strong evidence that H0 is not true The probability of finding a Z value of 1.55 or more is 0.0606, found by 0.5 0.4394. The probability of obtaining an greater than 203.5 if  µ = 200 is 0.0606. To compute the P-value, we need to be concerned with the region less than -1.55 as well as the values greater than 1.55. The two-tailed P-value is 0.1212, found by 2(0.0606). The P-value of 0.1212 is greater than the significance level of 0.01, so H0 is not rejected. Chapter Review The Central Limit Theorem states that the sampling distribution of the sample means is approximately normal. The standard error refers to the standard deviation of the sampling distribution of the sample mean. We use t distribution when the sample is less than 30 observations and the population standard deviation is not known. The necessary sample size depends on 1) level of confidence wanted ; 2) margin of error the researcher will tolerate; 3)variability in the population.   By rejecting a true null hypothesis, we committed a Type I error. We would reject the null hypothesis when it is highly improbable that a computed Z value this large is due to sampling variation. What You Need To Know Confidence interval: A range of values constructed from sample data so that the population parameter is likely to occur within that range at a specified probability. Hypothesis: A statement about a population parameter developed for the purpose of testing. Hypothesis testing: A procedure based on sample evidence and probability theory to determine whether the hypothesis is a reasonable statement. Critical value: The dividing point between the region where the null hypothesis is rejected and the region where it is not rejected. P-value: The probability of observing a sample value as extreme as, or more extreme than, the value observed, given that the null hypothesis is true. Work Them Out 1. The average number of days in outdoors assignments per year for salespeople employed by an electronic wholesaler needs to be estimated with a 0.90 degree of confidence. In a small sample, the mean was 150 days and the standard deviation was 14 days. If the population mean is estimated within two days, how many salespeople should be interviewed? A 134 B 152 C 111 D 120 2. A random sample of 85 staff of managerial grade revealed that a person spent an average of 6.5 years on the job before being promoted. The standard deviation of the sample was 1.7 years. Using the 0.95 degree of confidence, what is the confidence interval for the population mean? A 6.19 and 6.99 B 6.15 and 7.15 C 6.14 and 6.86 D 6.19 and 7.19 3. The mean weight of lorries travelling on a particular highway is not known. A state highway authority needs an estimate of the mean. A random sample of 49 lorries was selected and finds the mean is 15.8 tons, with a standard deviation of 3.8 tons. What is the 95 per cent interval for the population mean? A 14.7 and 16.9 B 14.2 and 16.6 C 14.0 and 18.0 D 16.1 and 18.1 4. A bank wants to estimate the mean balances owed by platinum Visa card holders. The population standard deviation is estimated to be $300. If a 98% confidence interval is used and an interval of $75 is desired, how many platinum cardholders should be taken into sample? A 84 B 82 C 62 D 87 5. A sample of 20 is selected from the population. To determine the appropriate critical t-value, what number of degrees of freedom should be used? A 20 B 19 C 23 D 27 6. If the null hypothesis that two means are equal is true, where will 97% of the computed z-values lie between? A  ± 2.58 B  ± 2.38 C  ± 2.17 D  ± 1.68 7. Suppose we are testing the difference between two proportions at the 0.05 level of significance. If the computed z is -1.57, what is our decision? A Reject the null hypothesis B Do not reject the null hypothesis C Review the sample D Own judgment 8. The net weights of a sample of bottles filled by a machine manufactured by Dame, and the net weights of a sample filled by a similar machine manufactured by Putne Inc, are (in grams): Dame: 5, 8, 7, 6, 9 and 7 Putne: 8, 10, 7, 11, 9, 12, 14 and 9 Testing the claim at the 0.05 level that the mean weight of the bottles filled by the Putne machine is greater than the mean weight of the bottles filled by the Dame machine, what is the critical value? A 2.215 B 2.175 C 1.782 D 1.682 9. Which of the following conditions must be met to conduct a test for the difference in two sample means? A Data must be of interval scale B Normal distribution for the two populations C Same variances in the two populations D All the above are correct 10. Take two independent samples from two populations in order to determine if a statistical difference on the mean exists. The number for the first sample and the number in the second sample are 15 and 12 respectively. What is the degree of freedom associated with the critical value? A 24 B 25 C 26 D 27 SHORT QUESTIONS A consumer group would like to estimate the mean monthly water charge for a single family house in June within $5 using a 99% level of confidence. Similar research has found that the standard deviation is estimated to be $25.00. What would be the sample size? The manager of the Kingsway Mall wants to estimate the mean amount spent per shopping visit by customers. A sample of 20 customers reveals the following amounts spent. $48 $42 $46 $51 $23 $41 $54 $37 $52 $48 $50 $46 $61 $61 $49 $61 $51 $52 $58 $43 What is the best estimate of the population mean? Determine a 99 per cent confidence interval. Interpret the result. Would it be reasonable to conclude that the population mean is $50? What about $60? ESSAY QUESTION 1. ABC Film Ltd knows that a certain favourite movie ran an average of 84 days, and the corresponding standard deviation was 10 days. The manager of New Westminster district was interested in comparing the movies popularity in his region with that in all of Canadas other theatres. He randomly selected 70 theatres in his region and found that they showed the movie for an average of 82 days. (a) State appropriate hypotheses for testing whether there was a significant difference in the length of the pictures run between theatres in the New Westminster district and all of Canadas other theatres. (b) Test these hypotheses at a 1% significance level.

Ethical Systems Essay

Ethical systems form the basis of moral beliefs; they are the moral philosophies that order moral principles systematically. (Thomson and WardSworth, 2005) Ethical systems can be broadly classified into deontological and teleological ethical systems. A deontological system concerns itself with the nature of an act that is under judgment, if an act is good but results in bad consequences than if it still considered a good act. Teleological systems judge consequences of an act, if an act is bad but results in beneficial consequences then it is considered moral. Ethical formulism judges the intent of the author thus, it is a deontological system. If a person performs an action from goodwill and it results in bad consequences, it is a moral action. This system also uses predetermined principles to judge goodness: that people should not be used as a means to an end, that behavior is moral when it is freely chosen and autonomous (someone worked to do a good thing is not really moral. ) and that actions should be based on behavior being universal. Utilitarianism is a teleological system whose goal is judged by consequences of an action. In this case when an action contributes much to the good of majority it is moral, regardless of the individual or minority who may have suffered because of the action. Following this system, Winston Churchill by allowing Coventry to be bombed in World War II so the Germans would not know the Allies had cracked their military code did a moral thing even though hundreds of English people were killed, when they might have been saved had they been warned. A smaller group was sacrificed for the sake of the greater good in this case, ending the war earlier and saving thousands more. Religion is a frequently used ethic system based on a willful a rational God. For believers there is no reason to question the authority of God’s will. The controversial issue is the interpretation of God’s will. According to Barry when is a dilemma; God’s will can be found in 3 ways; if one feels uncomfortable about a certain action, it is probably wrong. Religious authorities can provide guidance on right and wrong and thirdly the scripture provides answers to moral dilemmas. (Thomson and Wadsworth, 2005) The natural law ethical system proposes that ‘what is good is natural and what is natural is good’. These are innate instincts for example self-preservation is inborn, natural and basic and all actions related to it such as self-defense, prohibition of murder are moral acts. The basic problem with this system is where it is difficult to identify what is consistent and congruent with human nature. Focus on basic inclinations make this a teleological system because an action like killing may be wrong but if it is done in self-defense then it is considered a moral act since it is line with the self-preservation instinct. The ethics of virtue is a system that focuses on defining a good person as opposed to a ‘good action’. Here reason cannot be used to find out what is good. This system is teleological as it conserved with achieving a good end and more specifically happiness. One does good because of one’s character, if one has a bad character they will usually choose the immoral path. For example, a person who is broke and sees a stranger drop money without realizing calls the strangers back and gives him his money, he has performed a moral act because he has a habit of integrity. Someone else would steal because it is in his or her character to do so. The ethics of care system emphasizes human relationships and needs. It has been referred to as a feminine morality as it is founded on the natural human response to care for unborn child, ill and hurt. Some Eastern religious like, reject a rule-based form of ethics preferring instead to lead an individual in caring for needs. Braswell et al, 2002). The ethic behind rehabilitation is another illustration of ethics of care system. (Thomson and Wardsworth, 2005) This system is in line with teleological system of ethics because it does not simply classify action as wrong or right, rather it is concerned with the needs of others and effects of the actions on them, which learns more towards judging consequences corporations rather than the actions themselves. Egoism proposes that what is moral is what is good for one’s survival and personal happiness. This premise in its extreme directs that people should do whatever is beneficial to them. This disregards other people, using them as means to ensure happiness and in effect it means they have no meaning or rights (Thomson and Wadsworth, 2005) Egoism, sees an individual who performs a completely selfish act as immoral even impossible as it is not in line with true nature of human beings who like all other species have instincts for survival, self preservation and self in trust which is merely part of this natural instinct. This position is neither logical nor flexible single it would be in support of exploitation of the weak by the strong, which by all other systems is wrong. The system that closely matches my own beliefs is the religious ethical system. This is because the basis for ethics provided is rational since it can be identified wit a perfect God-figure. In addition, the similarity of the principles of these ethics in most of the religious are an indicator that they are acceptable to a wide majority hence they cover the needs of most of mankind adequately. In addition, scripture provides answers to ethical problems in all circumstances, something that most other ethical systems do not. The issue of say the birth contradicting only comes up when there is failure to understand the context of scripture. Belief in a God means that we do not have the responsibility of determining what is right, or wrong, since an unquestionable authority has determined them already.

Belonging to Culture

People feel a strong sense of belonging to their culture. This is seen in the film ‘Bend It Like Beckham’ by Gurinder Chadha. The main scenes that portray this statement are the engagement scene, pre-wedding scene and the wedding scene. This statement is also shown in the related text ‘Integrated’ by Sylvia Kantaris. In the film, various techniques are used such as long shots, full shots and panning. In the related text the techniques used are a metaphor, listing, contrast and emotive words. In the film ‘Bend It Like Beckham’ the engagement scene starts off with a long shot of the outside of Jessminder’s house.The house is decorated with lights and lighting is a technique used to make the house stand out. After that there is a high angle/close up shot of the food. The foods are colourful and bright. Bright colours are festive and symbolises happy occasions. Costume is another technique. Everyone is wearing the same sort of clothing and th ey are colourful. This shows that they belong to the Indian culture. The full/long shot of the room and the people sitting next to each other shows sense of belonging to their culture. This scene also explores gender roles.The males were sitting down, eating and talking to others whilst Jess was walking around offering food to the guests. A woman tells Jess â€Å"it will be your turn soon. † This means that she is expected to marry an Indian man just like every other Indian woman. These values and traditions are aspects of their Sikh Indian culture and Jess is expected to follow them. People feel a strong sense of belonging to their culture. We also see this in the pre-wedding preparation scene. In this scene we see everyone sitting together again. Gender roles are explored in this scene as well.All the women are sitting next to each other around a table making samosas. A full shot is a technique used in this scene. This shows belonging to their culture because they are all c elebrating harmoniously. There are alternations used between the Indian and British culture to show contrast between the two cultures. There is an overhead shot of the Bhamra’s backyard and their neighbours backyard. The Bhamra’s backyard is colourful, active and bright while their neighbours backyard is quiet, dull and empty. There are alternations used between Jess preparing for the wedding and her team training for the finals.This shows that she is caught between two cultures. Music is a technique used. The music is sad and so is Jess. Her facial expressions show us that she is not interested in what’s going on around her. She takes down her David Beckham poster and this shows that she is giving up on soccer. People feel a strong belonging to their culture however some people can feel caught between two cultures. Another text that that shows people feel a strong sense of belonging to their culture is the poem ‘Integrated’ by Sylvia Kantaris. This poem is about a Greek woman who moves into Australia but does not want to integrate.The metaphor â€Å"she brought her country with her in packing cases† tells us that she has brought ornaments of her country with her because she feels strongly about her culture. She does not want to integrate because she is scared of losing her own culture. At her home in Australia, she listens to Greek music, speaks Greek with her granddaughter and this shows she feels strongly about her culture. Another technique used in this poem is listing. First there is a listing of all the Greek items and then there is a listing of Australian items.This shows contrast between two cultures. Her granddaughter listens to western music, speaks English and eats Australian food. â€Å"Her grandchild†¦has eaten corned-beef, cornflakes†¦another tongue, her future. † This quote tells us her granddaughter has found it quite easy to integrate whereas â€Å"the land gave way, she arranged it to her liking,† shows the grandmother got her way. The use of emotive words such as â€Å"fierce† and â€Å"confrontation† shows that there was a battle between the grandmother and her new environment and she won because she did not integrate. Australia is more malleable than she,† tell us Australia was manipulated because the grandmother did not give up. She kept to her culture. Not only do people feel a strong sense of belonging to their culture but they can experience cultural clash. In conclusion people feel a strong sense of belonging to their culture. This is seen in the film ‘Bend It Like Beckham’ and the poem ‘Integrated. ’ Both of these texts show us people feel strongly about their culture. However they also show us that cultural clashes can arise as well when people feel trapped between two cultures.

Pennsylvania Musical Arts - 1421 Words

Central Pennsylvania, and specifically, the Harrisburg area, is full of many potentially bright minds who unfortunately can’t always find the right place with people who will nurture and encourage them. Plagued with the common national problem of an overpopulation of students paired with an understaffing of teachers, many of these minds go by without anyone to guide them in the right direction. As a result, intelligence that could be used to better the world around us is directed toward darker things such as crime and violence. Fortunately, there are groups in the area that are making an effort to enrich misguided young people, groups such as the Harrisburg Symphony Orchestra, the Pennsylvania Academy of Fine Arts, Pennsylvania Ballet, and†¦show more content†¦In addition to partnering with schools in the area, they also have international partnerships in countries such as Hungary, and China. Through these partnerships, PAM has spread their love of music and dedicatio n to helping children reach a higher level of education through their musical talents. Since 2009, PAM has also been able to offer a high school diploma, making it so its students could graduate, and consequently go onto some of the most renowned musical colleges in the world. The Pennsylvania Academy of Music is a lot like the Pennsylvania Academy of the Fine Arts in that they both aspire to make readily available music and the arts to whoever seeks them. They are also similar in that they educate on the subjects. However, they do differ in that PAM offers a high school diploma, while PAFA’s school is a secondary education school. Also, because it is older, PAFA holds more prestige over PAM, and, organization wise is more developed and has had more influence and made more of an impact than PAM because of its age and resources. The last of the charities covered in this paper is Pennsylvania Ballet. 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