Winning customers for life with relationship marketing Essay

Winning customers for life with relationship marketing - Essay Example Marketing was quite interesting me due to the fact that relationship marketing is a technique that can increase the sales figures of a company. Many companies are able to generate first time sales, but retaining customers is the key to having a successful business model. It is said that 80% of your sales are generated by 20% of your customers. Finding and retaining good customers can help companies build a business that can succeed in the long run. The use of a relationship marketing plan can help companies identify customers that are valuable to the firm. When a firm can identify its best customers companies can create targeted marketing campaigns. An interesting finding from the article was the fact that marketing has become processized. Using technology can help marketers analyze information better which can help firms achieve greater results. Marketing automation can be used in order to analyze data faster and to obtain update data and information. This can help companies make be tter operating and strategic decisions. The ten steps require for executing relationship marketing automation are: build your database, segment your list, design your communication, build your microsite, include a survey, schedule and send your campaign, follow-up on leads, nurture prospects, analyze campaign results, and repeat the process (Vtrenz, 2007). The purpose of marketing is to is to satisfy the customers’ needs better than the competition. ... The ten steps require for executing relationship marketing automation are: build your database, segment your list, design your communication, build your microsite, include a survey, schedule and send your campaign, follow-up on leads, nurture prospects, analyze campaign results, and repeat the process (Vtrenz, 2007). Chapter Five Summary The purpose of marketing is to is to satisfy the customers’ needs better than the competition. Companies that are able to serve the needs of the customers are the ones that are achieve greater market penetration and a higher level of success. Customer behavior can be defined as the study of how individuals, groups, and organizations select, buy, sell, and dispose of goods, services, ideas, or experiences to satisfy their needs and desire. Customer behavior is influenced by a variety of factors. Both marketing and environmental stimuli enter into the buyer’s consciousness. Cultural factors are very influential in customer’s decisi ons. Culture is considered the fundamental determinant of a person’s wants and behavior. Cultures are composed of different subcultures that provide specific identification and socialization for their members. There are different social classes within the different societies across the world. They are relative homogenous and enduring divisions in society. There are seven ascending levels of social classes. The seven levels are: 1) lower lowers; 2) upper lowers; 3) working class; 4) middle class; 5) upper middles; 6) lower uppers; 7) upper uppers. People from the same social class tend to behave similarly then people from different social classes. Some of the things that differentiate social classes are dress, speech patterns, and recreational preferences.

Symbolism in the Short Story Research Paper Example | Topics and Well Written Essays - 250 words

Symbolism in the Short Story - Research Paper Example That is the main theme of the short story, talking versus communicating. Both parties eventually became frustrated with the direction their conversation is heading, which then leads both of them to put more walls between them, thus aggravating the situation. For example, the girl looked at the hills and mentioned they are lovely, but the man replied pertaining to getting another drink. Then the American said â€Å"The beer’s nice and cool,† to which the girl replied â€Å"It’s lovely.† (Clugston, 2010, p. 112). They were obviously talking about two separate things. This then leads the readers to the symbolism used in the story. The American wants to say anything to convince the girl to go through an abortion, a fact that is not directly mentioned in the story. This is linked to the story’s title Hills Like White Elephants. Hills is usually a symbolism of wanting to escape, while white elephants usually symbolizes something that an individual does not want; in this story, it is the unborn child. Afterwards, the girl takes back her statement and mentions that the hills do not really look like white elephants at all (Clugston, 2010, p. 112). It is a subtle hint that she might want to keep the baby despite the American’s encouragement to abort

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.

of mice and men Essay -- essays research papers

Does Steinbeck reflect a desperate society or does he offer some hope and optimism in his novel "Of Mice and Men" In Steinbeck's novel " Of Mice and Men" there are many different characters each expressing there own opinion on whether they are living in a desperate society or that there is indeed some hope and optimism in the world around them. At the time the book was set, which is in the 1930's great American depression, many people were unemployed and jobs were hard to come by. Steinbeck's novel centres around the exploits and happenings of a few men, and one women, at the time of this great depression. Steinbeck shows how the most unusual friendships can be created in the mist of this depression and sadness. Such as the strong friendship between Lennie and George. Which in the end, drove George to kill Lennie for his own good. Some characters such as Lennie show how many people at this time had dreams of owning there own piece of land and being able to retire in peace with no one to tell them what to do. This reflects the view of optimism and hope in the book. However some characte rs such as Crooks see the world around them as desperate and solitary. Crooks believes that no ones dream will come true and that nothing will ever get better, this is shown in the line, " Nobody ever gets to heaven, and nobody never gets no land." (page 106) He also says that Lennie's dream will always stay as a dream and will never come true. The novel " Of Mice and Men" on the whole gives many views of hope and optimism and many views of the characters in the book living in a desperate society. I believe that the book balances itself out and that there are equal amounts of each view. The book being as equally optimistic as it is pessimistic. I will discuss how Steinbeck shows these views through his selection of characters and scene settings over the next few paragraphs. At the time the book Of Mice and Men is set many people in America and other countries had a very pessimistic outlook on life. The book reflects this view in its character opinions and scene settings. From 1929 to 1939 there were failed businesses, harsh poverty and many people were in long term unemployment. Many people made the migration to California looking for work. Most travelled alone, however, in the case of Lennie and George t... ...9) Curley,Slim or Carlson do not seem to show any dreams in the book and this could be counted as optamistic and hopeful in nothing will ever get worse or it coould be counted as a symbol of a desperate society in that nothing will ever get better. Curley's wife has two dreams. These being that she wants to talk to otheres, most probably women as she has lacked talking to another woman for a long time, this is shown in the line, "passion of communication" (page ??). Curley's wifes other dream is to be a star in Hollywood. Her dreams are mainly optamistic in that she believes in themm fully. This is shown in the line, "Maybe I will" (page ??). This is when she is talking to Lennie about her dream of being a movie star and she says that maybe she will be a movie star yet. This shows great optamism and hope in Curley's wife's character. The surroundings in Of Mice and Men are constant throughout. This shows how although the characters change dramaticly throught the course of the book nature always stays the same. Many thing which are at the start of the book such as, " of mice and men Essay -- essays research papers Does Steinbeck reflect a desperate society or does he offer some hope and optimism in his novel "Of Mice and Men" In Steinbeck's novel " Of Mice and Men" there are many different characters each expressing there own opinion on whether they are living in a desperate society or that there is indeed some hope and optimism in the world around them. At the time the book was set, which is in the 1930's great American depression, many people were unemployed and jobs were hard to come by. Steinbeck's novel centres around the exploits and happenings of a few men, and one women, at the time of this great depression. Steinbeck shows how the most unusual friendships can be created in the mist of this depression and sadness. Such as the strong friendship between Lennie and George. Which in the end, drove George to kill Lennie for his own good. Some characters such as Lennie show how many people at this time had dreams of owning there own piece of land and being able to retire in peace with no one to tell them what to do. This reflects the view of optimism and hope in the book. However some characte rs such as Crooks see the world around them as desperate and solitary. Crooks believes that no ones dream will come true and that nothing will ever get better, this is shown in the line, " Nobody ever gets to heaven, and nobody never gets no land." (page 106) He also says that Lennie's dream will always stay as a dream and will never come true. The novel " Of Mice and Men" on the whole gives many views of hope and optimism and many views of the characters in the book living in a desperate society. I believe that the book balances itself out and that there are equal amounts of each view. The book being as equally optimistic as it is pessimistic. I will discuss how Steinbeck shows these views through his selection of characters and scene settings over the next few paragraphs. At the time the book Of Mice and Men is set many people in America and other countries had a very pessimistic outlook on life. The book reflects this view in its character opinions and scene settings. From 1929 to 1939 there were failed businesses, harsh poverty and many people were in long term unemployment. Many people made the migration to California looking for work. Most travelled alone, however, in the case of Lennie and George t... ...9) Curley,Slim or Carlson do not seem to show any dreams in the book and this could be counted as optamistic and hopeful in nothing will ever get worse or it coould be counted as a symbol of a desperate society in that nothing will ever get better. Curley's wife has two dreams. These being that she wants to talk to otheres, most probably women as she has lacked talking to another woman for a long time, this is shown in the line, "passion of communication" (page ??). Curley's wifes other dream is to be a star in Hollywood. Her dreams are mainly optamistic in that she believes in themm fully. This is shown in the line, "Maybe I will" (page ??). This is when she is talking to Lennie about her dream of being a movie star and she says that maybe she will be a movie star yet. This shows great optamism and hope in Curley's wife's character. The surroundings in Of Mice and Men are constant throughout. This shows how although the characters change dramaticly throught the course of the book nature always stays the same. Many thing which are at the start of the book such as, "

Are Wars Necessary?

Are Wars Necessary? I think, there are quite few people who actually believe that the war is something good, wholesome and useful. It is and has always been one of the worst and most disgusting, destructive events that can happen. But it is to the same degree wrong to accuse it of all the deadly sins existing in the world. Although war is always evil, sometimes it is the lesser evil, in some cases it is inevitable.I, of course, don’t support the idea that the war is necessary in socio-economical sense – there is such a point of view, stating that the war is the motive power of progress and effective method of keeping demographic situation stable. Of course, some inventions were first applied in military, but also because this research has always been better supplied. And, although a lot of people die in the course of wars, it is not enough to really influence demographics, especially nowadays.I am speaking about the war as the conflict of interests and state that yes, i n certain situations war is necessary and even turns out into a thing to be proud of. War may be offensive and defensive and, just like in the case of self-defense, in the event of armed attack from another country any kind of violence used in retaliation is acceptable, because any other course of action will mean suicide.Looking at the same analogy, there is no much difference between a country attacking another country from a mugger on the street. The fact that the offenders are numerous, wear uniforms and deliver speeches makes absolutely no difference. Read more: http://www. paperwritings. com/free-examples/essay-about-war. html#ixzz2DxD5bCkQ

Strong Centralized Government

There is no doubt that Iraq needs a strong centralized government. This assertion is based on the following factors: 1) the rise of radical Islam, 2) the heterogeneity of the Iraqi population (ethnic groups), and 3) resistance to the growing phenomenon of ‘hollowing of the state. ’ It may be misleading to assume that the existence of these factors would necessarily lead to the establishment of a strong centralized government. But in Iraq, this is the case.The rise of radical Islam engulfed the politics of Muslim countries in the Middle East. Muslim extremists used the name of Islam to destroy the basic institutions of health, education, and welfare; replacing them with institutions that outrightly promote political anarchy, social stratification, and international terrorism. Iraq was able to resist the waves of radical Islam because of its highly centralized government. The government’s grip on the local population prevented dissidents from fully articulating thei r radical ideology.According to Huntington, the suppression of radical Islam can only be achieved through the establishment of strong authoritarian institutions; institutions which overtly rejects the fallacies of Islamic extremism (Huntington, 429). Huntington held that Islamic extremism is, in general, a stumbling block to self-determination and development (Huntington, 431). Iraq’s war with Iran simply illustrates the former’s need to defend itself from the waves of radical Islam. Kuznetsov argued that the Iraq-Iran war was a contest between orthodox Islam and radical Islam (Kuznetsov, 219).This was not the case. Iran’s ambition to dominate the Middle East was based on two factors: the need to propagate radical Islam, and security. Iraq successfully contained the Iranian threat because of the authoritarian nature of the Iraqi government. Efficiency, effectiveness, and brutality were the main qualities that enabled Iraq to resist Iran. Glazer and Moynihan argu ed, â€Å"Whenever a democracy has a large number of ethnic groups, it is likely to fall into political anarchy† (Glazer and Moynihan, 374).This statement makes sense. In many democratic countries with heterogeneous populations, there is the constant threat of civil war and political instability. This is obvious. Ethnic groups vie for power through the electoral system to control other ethnic groups (as in the case of Yugoslavia). Ethnic groups who lost in elections had no choice but to confront the dominant group through armed struggle. In Communist and authoritarian states, this was not possible.Communist and authoritarian states disregarded ethnicity as a factor of solidarity. Iraq was able to contain its heterogeneous population through systematic government control on all aspects of the society. Political instability could not exist because the government served as the unifying factor of the country. The establishment of a strong central government in Iraq may be regarde d as a measure to ensure the dignity and integrity of the state. Today, the phenomenon of ‘hollowing of the state’ is apparent in many democracies.This phenomenon is characterized by the weakening of the state as an institution, reduced economic sovereignty, and group power politics (Toynbee, 728). Only a strong and highly centralized government could effectively preserve the power and sovereignty of the state. Works Cited Glazer, N and D. P. Moynihan. Race and Ethnicity. American Sociological Review, 43(17), Oct. 2001. Huntington, Samuel. The Clash of Civilizations and the Remaking of the World Order. New York: Macmillan Publishing Company. Toynbee, Arnold. A History of the World. London: London Publishing House, 1975.