Evolution And Evolution Of Evolution - 1154 Words

EVOLUTION Evolution is a scientific theory that was first introduced in the mid 1800’s and it refers to the biological changes that take place within a population of a specific species over the course of many generations. This theory was one of the most scientifically groundbreaking discoveries of our time, and since its discovery, scientists have been working hard to find more and more evidence on the subject. Although there is much controversy on the subject of evolution, it is hard to ignore the facts and observations that strongly support it. In the first chapter of Science, Evolution and Creationism by the National Academy of Scientists, it explores different scientific discoveries and observations which even further confirm the†¦show more content†¦This specific island contained sedimentary rock that had apparently been there for approximately 375 million years. Why is this number important? Because it was predicted that around 375 million years ago shallow wate r fishes were slowly evolving into land creatures with four legs. The team of scientists believed that it was possible they found evidence of this hypothesis and they were not at all disappointed. What they found was the fossil of a Tiktaalik. A tiktaalik is a fish that had several characteristics of tetrapods, or a four-legged creature. The fossil showed that the fish had four fins on the front and back which contained bones that would allow the creature to prop itself up. This fossil is an example of what scientists call a transitional fossil. A transition fossil is a fossil which gives us evidence of a transition from one species to another. It is a fossil that is in between point A and point B. The tiktaalik is a superb example of this because it has characteristics of both a fish and a four-legged land creature, suggesting that over time the tiktaalik probably actually became a species of the land after several generations of them growing leg-like appendages. The tiktaalik woul d likely achieve evolving into a land creature through sexual reproduction. Reproduction plays a key role in biological evolution. When two creatures of the same species reproduce, the offspring receives DNA that belonged to both

Working Paper Free Essays

The term module means that the questionnaire can be used as part of a larger Research experience has shown that the answers to the 24 content questions are influenced by the nationality of the respondents. This is not to say that every respondent of nationality A gives one answer and everyone of a nationality B another, but one can expect systematic differences between the average answers from a sample with nationality A and a comparable sample from nationality B (in statistical terms, an analysis of variance on the answer scores shows a significant country effect). As the relationship is statistical, the samples per country should be of sufficient size. We will write a custom essay sample on Working Paper or any similar topic only for you Order Now An ideal size for a homogeneous sample is 50 respondents. Sample sizes smaller than 20 should not be used, as outlying answers by single respondents will unduly affect the results. If samples are heterogeneous (composed of unequal sub-samples) these numbers apply to the sub-samples. Next to nationality, answers to the 24 content questions will also reflect other characteristics of the respondents, such as their gender, age, level of education, occupation, kind of work and the point in time when they answered the questions. Therefore comparisons of countries should be based on samples of respondents who re matched on all criteria other than nationality that could systematically affect the answers. The content questions attributed to a dimension were selected because in comparisons of matched samples from ten or more countries, the mean country scores on the four questions belonging to the same dimension usually vary together (if one is high, the other is high, or low if it is a reversely formulated question; if one is low, the other is low, etc. ). In statistical terms, the mean country scores are significantly correlated. The mean country scores on questions belonging to different emissions usually do not vary together (are uncorrelated). Therefore, the 24 questions form 6 clusters of 4 questions each. As mentioned above, the dimensions measured by the VS.. Are based on country- level correlations, between mean scores of country samples. For the same two questions, country-level correlations can be very different from individual-level correlations, between the answers by the individuals within the country samples (for a clear explanation see e. G. Klein, Danseuses Hall, 1994). Individual-level correlations produce dimensions of personality; country-level correlations produce emissions of national culture. For research results about the relationship between personality and culture see Hefted McCrae (2004). The study of national culture dimensions belongs to anthropology, the study of individual personality belongs to psychology. The first is to the second as studying forests is to studying trees. Forests cannot be described with the same dimensions as trees, nor can they be understood as bunches of trees. What should be added to the animals, organisms and climate factors, together described by the term epitome. In reverse, trees cannot be described with the same dimensions as forests. At best one can ask in what kind of forest this tree would be most likely found, and how well it would do there. A common misunderstanding about dimensions of national culture is that they are personality types. People want to score themselves on a dimension, or worse, try to score someone else. This is called stereotyping, which is not what the dimensions are for. They do not refer to individuals, but to national societies. What a person can do is find out how the values prevailing in his or her national society differ from those in another society. As an individual, a person can express how he or she feels about the values in a particular national society, but that would still be a function of his/her personality and not necessarily show his or her national culture. Because of this, the VS.. 2013 cannot be scored at the individual level. It is not a psychological test. The tendency to ask for individual scoring of the VS.. Is stronger in some national cultures than in others. Especially in very individualist cultures, the request for individual scoring is frequent: the concept of my society (a forest) is weaker that the concept of me myself (a tree). The VS.. Should only be used by researchers who subscribe to the concept of a society differing from other societies. The six dimensions on which the VS.. 2013 is based were found in research across more than 40 countries. In a research project across 20 different organizations within the same two countries, answers to the questions that made up the cross-national dimensions did not correlate in the same way (Hefted, Enquire, Omaha’ Sanders, 1990 and Hefted, Hefted Moving, 2010: 341-368). So the cross-national dimensions do not apply to organizational (or corporate) cultures. The answers to the VS.. Questions (dealing with values and sentiments) varied less across organizations within a country than across countries. Instead, organizational cultures differed primarily on the basis of perceptions of practices, and the organizations in the study could be compared on six dimensions of perceived practices. While the study of national culture dimensions belongs to anthropology and the study of individual personality belongs to psychology, the study of organizational cultures belongs to sociology. The dimensions of perceived practices in the Hefted et al. 1990) study relate to known distinctions from organizational sociology. A similar concern prohibits the use of the VS.. Dimensions for comparing occupations (Hefted, Hefted Moving, 2010: 368-369). In some cases, VS.. Dimension scores can be meaningfully computed and compared for the genders (female versus male) and for successive generations (grandparents country or across countries, but in this case we recommend extending the questionnaire with locally relevant items (Hefted, Garibaldi, Melville, Tenure evokes, 2010). 4. VS.. 2013 scores are not comparable to published scores Some enthusiastic amateurs have used the VS.. With a sample of respondents from one country and tried to draw conclusions comparing the scores they found with those in Hypotheses books (1980, 1991 , 2001 , 2005, 2010). But essential to the use of the VS.. Is that comparisons should be based on matched samples of respondents: people similar on all criteria other than nationality that could systematically affect the answers. All scores in the first two Hefted books were based on carefully matched IBM subsidiary populations. A new sample, to be comparable to these, should be a attach for the original IBM populations on all relevant criteria. Such a match is virtually impossible to make, if only because the IBM studies were done around 1970 and the point in time of the survey is one of the matching characteristics. Hypotheses books since 2001 contain scores for a number of countries not in the original IBM set, based on extensions of the research outside MOM, or in a few cases on informed estimates. Extensions of the research to countries and regions not in the original set have to be based, like any VS.. Application, on matched samples across two or more countries. These should always include one or, if possible, more of the countries from the IBM set, so that the new data can be anchored to the existing framework. Anchoring’ means that the scores from the extension research should be shifted by the difference of the old and new scores for the common country (or by the mean difference in the case of more common countries). The main problem of extension research is finding matched samples across new and old countries. Examples of successful extensions are described in Hefted (2001:464-465). The VS.. 2013 has been designed for research purposes. In the classroom it has poor ace validity, as it is based on the logic of national cultures which differs from the logic of individual students. Cultures are not king-size individuals: They are wholes, and their internal logic cannot be understood in the terms used for the personality dynamics of individuals. Echo-logic differs from individual logic† (Hefted, 2001 :17; the term ecological in cross-cultural studies is used for any analysis at the societal level; it does not only refer to the natural environment). To students or audiences without a professional training in anthropology or cross-cultural research the VS.. Is to the proper tool for explaining the essence of the dimensions. In this case trainers should rather develop teaching tools using the tables of differences between societies scoring high and low on each dimension, which are based on significant Hefted Moving, 2010: Chapters 3-8). The twenty-four content questions allow index scores to be calculated on six dimensions of national value systems as components of national cultures: Power Distance (large vs†¦ Small), Individualism vs†¦ Collectivism, Masculinity vs†¦ Femininity, Uncertainty Avoidance (strong vs†¦ Weak), Long- vs†¦ Short-Term Orientation, and Indulgence vs†¦ Restraint. All content questions are scored on five-point scales (1-2-3-4-5). Any standard statistical computer program will calculate mean scores on five-point scales, but the calculation can also be done simply by hand. For example, suppose a group of 57 respondents from Country C produces the following scores on question 04 (importance of security of employment): 10 x answer 24 x answer 2 14 x answer 3 5 x answer 4 1 x answer 5 42 20 54 valid answers totaling 125 Three of the 57 respondents gave an invalid answer: either blank (no answer) or multiple (more than one answer). Invalid answers should be excluded from the calculation (treated as missing). The mean score in our case is: 125/54 = 2. 31. Mean scores on five-point scales should preferably be presented in two decimals. More accuracy is unrealistic (survey data are imprecise measures). Power Distance Index (PDP) Power Distance is defined as the extent to which the less powerful members of institutions and organizations within a society expect and accept that power is distributed unequally. The index formula is PDP = 35(mom – mom) + 25(mom – mom) + QPS) in which mom is the mean score for question 02, etc. The index normally has a range of about 100 points between very small Power Distance and very large Power Distance countries. C(PDP) is a constant (positive or negative) that depends on the nature of the samples; it does not affect the comparison between countries. It can be chosen by the user to shift her/his PDP scores to values between O and 100. Individualism Index (DIVIDE) Individualism is the opposite of Collectivism. Individualism stands for a society in which the ties between individuals are loose: a person is expected to look after himself or herself and his or her immediate family only. Collectivism stands for a roofs, which continue to protect them throughout their lifetime in exchange for unquestioning loyalty. DIVIDE = 35(mom – mol) + 35(mom – mom) + C(ICC) in which mol is the mean score for question 01, etc. The index normally has a range of about 100 points between strongly collectivist and strongly individualist countries. C(ICC) is a constant (positive or negative) that depends on the nature of the samples; it does not affect the comparison between countries. It can be chosen by the user to shift his/her DIVIDE scores to values between O and 100. Masculinity Index (MASS) Masculinity is the opposite of Femininity. Masculinity stands for a society in which social gender roles are clearly distinct: men are supposed to be assertive, tough, and focused on material success; women are supposed to be more modest, tender, and concerned with the quality of life. Femininity stands for a society in which social gender roles overlap: both men and women are supposed to be modest, tender, and concerned with the quality of life. MASS = 35(mom – mom) + 35(mom – mom) + corn) in which mom is the mean score for question 05, etc. The index normally has a range of about 100 points between strongly feminine and strongly masculine countries. C(MFC) is a constant (positive or negative) that depends can be chosen by the user to shift her/his MASS scores to values between O and 100. Uncertainty Avoidance Index (AJAX) Uncertainty Avoidance is defined as the extent to which the members of institutions and organizations within a society feel threatened by uncertain, unknown, ambiguous, or unstructured situations. AU’ = 4001118 – mom)+ 25(mom – mom) + qua) in which mom is the mean score for question 18, etc. The index normally has a range of about 100 points between weak Uncertainty Avoidance and strong Uncertainty Avoidance countries. C(AU) is a constant (positive r negative) that depends on the nature of the samples; it does not affect the comparison between countries. It can be chosen by the user to shift his/her I-JAG scores to values between O and 100. Long Term Orientation is the opposite of Short Term Orientation. Long Term Orientation stands for a society which fosters virtues oriented towards future rewards, in particular adaptation, perseverance and thrift. Short Term orientation stands for a society which fosters virtues related to the past and present, in particular respect for tradition, preservation of â€Å"face†, and fulfilling social obligations. LTO = – mom) + 25(mom – mom) + C(IS) n which mom is the mean score for question 13, etc. The index normally has a range of about 100 points between very short term oriented and very long term oriented countries. C(l’s) is a constant (positive or negative) that depends on the nature of the samples; it does not affect the comparison between countries. It can be chosen by the user to shift her/his L TO scores to values between O and 100. Indulgence versus Restraint Index (IVR) Indulgence stands for a society which allows relatively free gratification of some desires and feelings, especially those that have to do with leisure, merrymaking with rinds, spending, consumption and sex. Its opposite pole, Restraint, stands for a society which controls such gratification, and where people feel less able to enjoy their lives. The index formula is IVR = – ml 1) + – mom) + COO in which ml is the mean score for question 11, etc. The index normally has a range of about 100 points between high indulgence and high restraint. C(IR) is a constant (positive or negative) that depends on the nature of the samples; it does not affect the comparison between countries. It can be chosen by the user to shift her/his IVR scores to values between O and 100. As country-level correlations differ from individual-level correlations, answers on questions used to measure a country-level dimension do not necessarily correlate across individuals. A reliability test like Cockroach’s alpha should in this case not be based on individual scores but on country mean scores. Obviously this presupposes data from a sufficient number of countries, in practice at least ten. For comparison across fewer countries the reliability of the VS.. At the country level has to be taken for granted; it can indirectly be shown through the validity of the scores in predicting dependent variables. The IBM database (Hefted, 1980) allows to compute Cockroach alphas for the first four dimensions across 40 countries (39 for AAU, 33 for PDP because of missing data). Power Distance Index (3 items): Alpha = . 842 Individualism Index (6 items): Alpha = . 770 Masculinity Index (8 items): Alpha = . 760 Uncertainty Avoidance Index (3 items) Alpha = . 15 The rule of thumb for test reliability is a value over . 700. The new items in the new version were chosen because of their similarity to items in reliable other studies, but the reliability of the new dimension scores cannot be proven a prior’. The VS.. 2013 is copyrighted, but may be freely used for academic research projects. Consultants who want to use the VS.. 2013 periodically should pay a license fee based on the nu mber of copies administered per year. The same holds for use by companies in employee surveys. Information on rates is available from the copyright holder (rights@geerthofstede. L) 9. History of the VS.. 2013 The original questions from the 1966-1973 Hermes (MOM) attitude survey questionnaires used for the international comparison of work-related values were listed in Hefted (1980, Appendix 1). Appendix 4 of the same book presented the iris Values Survey Module for future cross-cultural studies. It contained 27 content questions and 6 demographic questions. This VS.. 80 was a selection from the IBM questionnaires, with a few questions added from other sources about issues missing in the IBM list and Judged by the author to be of potential importance. In the 1984 abridged paperback edition of Hefted (1980) the original IBM questions were not included, but the VS.. 80 was. A weakness of the VS.. 80 was its dependence on the more or less accidental set of questions used in the IBM surveys. The IBM survey questionnaire had not really been imposed for the purpose of reflecting international differences in value patterns. However, the IBM questions could only be replaced by other questions after these had been validated across countries; and to be validated, they had to be used in a large number of countries first. Therefore in 1981 Hefted through the newly- founded Institute for Research on Intercultural Cooperation (IIRC) issued an experimental extended version of the VS.. (VS.. 81). On the basis of an analysis of its first results, a new version was issued in 1982, the VS.. 82. This was widely used for the next twelve years. 3 of the questions were needed to compute scores on the four dimensions identified by Hefted. The other questions were included for experimental use. Some questions in the VS.. 82 were only applicable to employed respondents. Thus the instrument could not be used for entrepreneurs, students, and respondents without a paid Job. The number of replications using the VS.. 82 in Iris’s files increased, but, unfortunately, it turned out that the samples from different researchers were insufficiently matched for producing a reliable new VS†¦ This changed when Michael Hope published his Ph. D. Hess on a survey study of elites (Syllabus Seminar Alumni) from 19 countries, using among other instruments the VS.. 82 (Hope, 1990). Eighteen of these countries were part of the IBM set, but besides USA all of them were from Europe. Hope’s data base was therefore extended by adding results from replications in six countries in Africa, Asia and Latin America that could be considered somewhat matched with the Hope set. In the meantime, the research of Michael Harris Bond from Hong Kong, using the Chinese Value Survey (Chinese Culture Connection, 1987), had led to the identification f a fifth dimension: Long-Term versus Short-Term Orientation (Hefted Bond, 1988; Hefted, 2001: Chapter 7). In the new version of the VS.. Published in 1994 (the VS.. 94), this dimension appeared for the first time together with the other four. The questionnaire was also adapted to respondents without a paid Job. Accumulated experience with the use of the VS.. 94 in the next 14 years led to the publication of an updated VS.. 08. In the meantime, many new sources of cross- cultural survey information became available. One was an unpublished Master’s Thesis (Van Bug, 2006) reporting on the Internet administration of the VS.. 94 among active members of the student association EASIES in 41 countries, collecting some 2,200 valid answers, a response rate of 24%. We also looked for questions correlated with the IBM dimensions in the newly available sources, including the huge World Values Survey database freely accessible on Internet (Ingather and associates, 1998, 2004, 2007). In 2007, Michael Moving published a book integrating all available old and new databases, and we invited him to Join the VS.. Team. Moving (2007) proposed three new dimensions: Exclusion versus Universalism, Indulgence versus Restraint, and Monumentality versus Flexibility (flexibility plus nullity). From these, Exclusion versus Universalism across 41 countries was strongly correlated with Power Distance and Collectivism (both r = . 74), so we did not treat it as a new dimension. Indulgence versus Restraint was uncorrelated with any of the five dimensions in the VS.. 94 and it added new insights into national cultural differences, so we accepted it as a new and sixth dimension. Monumentality versus Flexibility was significantly correlated with Short Term Orientation (r = . 68 across 16 overlapping countries) and less strongly with Power How to cite Working Paper, Papers

Impact of School Closure for Case Study of Kingston Community

Question: Write about theImpact of School Closure for Case Study of Kingston Community. Answer: Introduction Decision making is a process which put across all the stakeholders to avoid issues such as vested interests and biases. Avoiding to involve all the stakeholders and especially the main ones, the decision might be resisted, which might result to violence and communal conflicts. In this paper, we will analyse a case study of closure of Kingston school. The community have complained that they were not involved on making such as critical decision which affects their community. According to the residents, it has been rumoured to sometime that the school was to be closed due to reduced admission levels which has been led to the reduction of the Kingstons population. Although these might have been concrete reasons to close the school, the main concerns of the community members is failure to consult them while they were making the decision. I addition, the school has existed for a century and they feel it is not an honourable action to close a school which contributed so much to the growth o f the community. Nevertheless, the student will have to be bussed to another school every day - which translates to more time and money for the families to cater. Scientifically, this study is conducted to check whether there would be a difference in perceptions between the time before and after the school closure. The data is collected using a questionnaire, before and after the school closure and entered into SPSS system for analysis. Within the questionnaire, there is a community survey attitude measure too which is the key section to recode before and after values. Each question within the community attitude survey tool is in form of a Likert scale with 5 options from strongly agree through strongly disagree. After compiling the data, the values are added to get the pre and post totals, hence generating the two variables for effective comparison. The measurements are collected from the same individuals for the pre and post measurements, hence generating paired data. The other section of the questionnaire includes the demographic information which is collected once and can be used for further analysis. All the variables are coded in SPSS, h ence transforming them into categorical variables. In this paper, the test hypothesis will be stated, the possible research method highlighted and the data analysed after reviewing the validity of the questionnaire(Trochim, 2006). Hypothesis The hypothesis will be based on the pre-post measurements of community attitudes. I believe that before the closure the parents are very bitter about the decision but after the decision is officially announced, most of them will feel that there is not more to be done for the purpose of reversing the decision. Null hypothesis: There is no difference in community attitudes between pre and post measurements. Alternative hypothesis: The community attitudes will significantly difference between pre and post-test on the community attitudes Research Methodology The research design used in this study is an experimental design with a pre and post measurements. The official communication from the authorities on the closure of the school acts as the treatment. This study will focus to check the impact of the declaration about the school closure to the opinions and attitudes of the community. This can also be referred as a quasi-experimental study because the study situations are not controlled. However, there are several ways in which the study results can be improved by improving its procedures. These methods might include randomization and stratification which might be used to reduce biases by controlling for possible confounders. Randomization Randomization criteria give every individual in the population an equal chance to be chosen in the sample. In this case, the information gathered from the target population is believed to have a minimal bias which might emerge by selecting a sample with individuals having similar characteristics. For example, Sarah put posters in public areas to allow the interested parties join the study. The selected individuals might end up to be those who are directly affected which is not the main focus for scientific studies. It is important to get a view from every individual from the target population and this might only be achieved by randomisation because in most instances it is not easy to include every individual in the study. Therefore, Sarah could have developed a better way of selecting the study participants other than putting posters for self-recruitment. Else, the study sampling would be purposive by only including individuals who are easily accessing and only those who see the post ers. Since Kingston is a small town, Sarah could have requested for the administration register, hence selecting the individuals randomly and contacting them to request the fro participation. In this manner, the study would be more scientific and the results obtained would perceive better evidence about Kingstons view and perceptions(Manly, 2010). Stratification Stratification is another effective method of reducing biases in scientific studies. Population characteristics such as gender distribution among other key factors can be used to stratify a target population for better results. For instance, the perceptions and opinions closure might differ based on different factors within the society such as gender and age, For example, parents within student in the school who are being affected directly might be more bitter compared to those who do not have children within school leaving age bracket. Also, mothers might have different views because they are more caring and concerned about the welfare of their children. Considering such characteristics, Sarah could have settled on an effective way of stratifying the population to get better results, which are more representative(Bhatia et al., 2016). Examining the Questionnaire The questionnaire is well developed to measure the characteristics of interest in the research. However, Sarah might not have captured all the demographic information of interests such as the age and gender of the respondent. These are among the most significant factors which can be used to predict and define correlations. Sarah could have included two question to recode the age and gender of the respondent. Therefore, this could have been useful in the analysis state to conduct stratified analysis, which might bright out some important characterises of the population(Lessler et al., 2014). For instance, there might be the difference in the pre and post measurements based on gender. Therefore, the other question could have followed these ones, hence making the questionnaire more concrete. Further, the mode of collecting information could have been improved by employing several research assistants to help her in collecting the data from the field. It would be better to meet the respon dents in person and avoid sending the information to the post office. According to the identified issues identified in the questionnaire, I would state that the information collected is not sufficient to measure and analyse the views of Kingstons community(Hox and Boeije, 2005). Data Analysis Descriptive Statistics Table 1: Frequency distribution Count Percent Parent to secondary school age next year Yes 60 57.7% No 44 42.3% Distance from home to Kingston School 0 - 1 km 28 26.9% 2 - 4 km 16 15.4% 5 - 20 km 24 23.1% 20 km 36 34.6% Distance from home to High school at Beganup 0 - 20 km 12 11.5% 21 - 40 km 20 19.2% 41 - 60 km 44 42.3% 60 km 28 26.9% Youngest family member age 0 - 5 years 12 11.5% 6 - 12 years 28 26.9% 13 - 18 years 24 23.1% 18 years 40 38.5% Number of years residing at Kingston 0 - 1 years 20 19.2% 2 - 4 years 16 15.4% 5 - 10 years 20 19.2% 10 years 48 46.2% Occupation of a family member with the highest salary Farmer 52 50.0% Government employee 36 34.6% Business 16 15.4% Unemployed 0 0.0% Residential/Boarding high school at Kingston after Kingston Closure Yes 40 38.5% No 64 61.5% What is the standard education of 8 - 10-year-olds at Kingston Low 28 26.9% Medium 48 46.2% High 28 26.9% According to the frequency table above, the proportion of the parents with students who would be proceeding to a secondary school in the next year were 57.7%(Trochim, 2006). Fifty percent of the respondents were farmers as anticipated because most of the residents in Kingston depend on farming. There were no unemployed respondents in the study which might mean that almost all the residents in Kingston town are employed(Eurostat, 2016). Table 2: Summary statistics by categories Pretest total Posttest total Mean Median Standard Deviation Mean Median Standard Deviation Parent to secondary school age next year Yes 31 31 8 21 21 5 No 39 41 5 28 22 9 Distance from home to Kingston School 0 - 1 km 33 31 8 20 20 5 2 - 4 km 36 37 4 23 22 7 5 - 20 km 36 37 3 23 22 3 20 km 34 38 11 27 21 10 Distance from home to High school at Beganup 0 - 20 km 42 41 4 28 22 9 21 - 40 km 40 39 4 27 25 8 41 - 60 km 33 32 7 22 21 6 60 km 29 31 9 22 19 8 Youngest family member age 0 - 5 years 30 29 6 23 21 6 6 - 12 years 29 31 9 20 19 4 13 - 18 years 33 34 6 21 21 6 18 years 40 41 5 28 24 9 Number of years residing at Kingston 0 - 1 years 38 39 5 26 23 7 2 - 4 years 27 29 5 18 18 4 5 - 10 years 33 36 7 20 19 5 10 years 35 37 9 26 22 8 Occupation of a family member with the highest salary Farmer 34 37 9 26 22 8 Government employee 36 38 5 23 22 6 Business 30 29 9 18 18 4 Unemployed . . . . . . Residential/Boarding high school at Kingston after Kingston Closure Yes 41 41 4 27 22 8 No 30 31 7 22 21 7 What is the standard education of 8 - 10-year-olds at Kingston Low 42 42 4 27 22 8 Medium 36 37 4 23 22 6 High 24 24 5 22 19 9 (Ibm, 2012; Field, 2013) On average, the pre-test scores seem to have been greater than the post-test, hence the conclusion that the attitudes of the residents of Kingston about the closure of the high school changed significantly after the official announcement(Devore, 2006). Table 3: Overall descriptive statistics for pre and post tests N Minimum Maximum Mean Std. Deviation Pre-test total 104 13 48 34.27 8.017 Post-test total 104 13 43 23.68 7.669 Hypothesis Test Table 4: Correlation between pre and post-tests Paired Samples Correlations N Correlation Sig. Pre-test total Post-test total 104 .355 .000 Table 5: Paired t-test output Paired Samples Test Paired Differences t df Sig. (2-tailed) Mean Std. Deviation Std. Error Mean 95% Confidence Interval of the Difference Lower Upper Pre-test total - Post-test total 10.587 8.916 .874 8.853 12.320 12.109 103 .000 (Kent State University, 2016) Conclusion According to the paired t-test results in the table above, the p-value is less than the significance level, hence rejecting the null hypothesis and conclude that the average community attitudes for pre-test are significantly different compared to the post-test(Winter, 2013). Based on the descriptive statistics in tables 2 and 3, we can conclude that the average level of community attitudes towards the closure of the Kingston school is lower after the official communication of the closure compared to the time before. Therefore, the community acted more passionately before the administration communicated and they significantly changed their mentality immediately after the department of education confirmed the closure. Although the policies will affect the community they have no much to do after the department of education have made up their mind on the decision. However, there might be errors in data collection and study design which have led to wrong findings, which creates validity q uestions of the research. References Bhatia, G. et al. (2016) Correcting subtle stratification in summary association statistics, bioRxiv, p. 76133. doi: 10.1101/076133. Devore, J. (2006) Statistics for Business and Economics, The American Statistician, 60(4), pp. 342343. doi: 10.1198/tas.2006.s59. Eurostat (2016) Business demography statistics, Statistics Explained, 2015(November), pp. 19. Field, A. (2013) Discovering Statistics using IBM SPSS Statistics, Discovering Statistics using IBM SPSS Statistics, pp. 297321. doi: 10.1016/B978-012691360-6/50012-4. Hox, J. J. and Boeije, H. R. (2005) Data Collection, Primary vs. Secondary, in Encyclopedia of Social Measurement, pp. 593599. doi: 10.1016/B0-12-369398-5/00041-4. Ibm, A. (2012) IBM SPSS Statistics 21 Brief Guide, Ibm Spss. Kent State University (2016) SPSS Tutorials: Paired Samples t Test, University Libraries. Lessler, J. et al. (2014) Seven challenges for model-driven data collection in experimental and observational studies, Epidemics, 10, pp. 7882. doi: 10.1016/j.epidem.2014.12.002. Manly, B. F. J. (2010) Randomization, Wiley Interdisciplinary Reviews: Computational Statistics, 2(3), pp. 383386. doi: 10.1002/wics.91. Trochim, W. M. K. (2006) Descriptive Statistics, Research Methods, pp. 27. doi: 10.1016/B978-0-12-384864-2.00005-6. Winter, J. (2013) Using the Student s t -test with extremely small sample sizes, Practcial Assessment, Research Evalutaion, 18(10), pp. 112. doi: Retrieved from https://pareonline.net.