大家留学在外，对于essay可谓是又爱又恨，爱的是essay基本写了不偏题，有自己的内容充实文本，合理的引用都能拿到不错的分数，恨的就是选题，选旨时，繁重的翻阅以及查阅资料。这里主要讲的是对于文章文体的把握，什么是argument essay，什么是narrative essay，这两者又有什么区别？碰到这类又应该如何去应对呢？
Argument essay，辩论文，议论文，相信大家并不陌生，不止是中国的初高中需要写，美国大学大一大二的英语课一样是写argument essay。当然，格式会有很大的不同，但是文章的类型是一样的，当然内容也是万变不离其宗，论点，论据，以及各种佐证来证明自己的论点或者观点的正确性。在美国大学的英语课中，教授一般会放出不同的论点让你选择一个，用一整个学期来完成一篇符合要求的议论文，当然其中每个礼拜会需要对不同的论点论据章节做出大量的研究以及查阅资料。比如，我的大一第一学习的论点就是：美国本土印第安人对于美国发展、经济水平和文化产生了如何巨大的影响。围绕这一个论点，我需要大量的资料来求证印第安人的起源，文化水平，以及现留存的印第安族群的生活习惯和特性。每一步都得按照详细的步骤来一步步的完成，首先第一步，引出自己的论点，譬如，我就用现如今的印第安人朋友的生活来引出大家对于印第安人的思考，其次再对他的习惯与资料中的做出对比，表示现如今会对美国文化产生什么样积极的影响。再者，印第安人族群地的经济状况和美国全国的经济水平做出对比，引出第二个论点。同样地，引出第三个论点，以及自己对于其他学者的引用。最后对所有的论点进行一个总结，必须精简而又不偏离主题，为自己的议论文画上一个完美的句号。
相对而言，narrative essay 就是叙事类散文，主要以叙事，描绘周边景色，以及人物的文章，大都讲究一个随意性，文体主要特色就是没有一个固定的中心思想，描写与感悟相辅相成，浑然一体，叙事散文又分为五类，一类叫写人状貌类叙事散文，一类叫叙述情节类叙事散文，一类叫阐发道理类叙事散文，一种是咏物类叙事散文，一种是心理历程类叙事散文。写人状貌类叙事散文主要目的是塑造人物形象，与现代小说类似。叙述情节类叙事散文重在情节的细节，与记叙文不同，不讲究情节一波三折，但重视结构。阐发道理类叙事散文借叙事来说明某个道理，但叙事依然是主要目的。咏物类叙事散文专写一种物品与自己发生的故事，或自况某物，来歌颂美好人性，达到叙事目的。心理历程类叙事散文顾名思义主要写自己的心路历程，多描写多个事情，时间跨度大，感情不一，但服务于同一主旨，多写自己感情的变化，来达到叙事目的。
议论文范文如下：
Statistics is a substantial social science, both of the objective laws of social life, has examined the statistical method statistical basis of inheritance and development of the theory of statistical results, adhere to the statistical nature of the social sciences, so close to statistical theory actual statistical work, and social development in the country has been widely used so-called statistical thinking, that is, the actual work in statistics, statistical theory, applied research, we must follow the basic philosophy and guiding principle.
First, the statistics of several common statistical ideas in statistical ideas include: mean thought, thinking of variation, estimated ideas, related ideas, thought fit to test ideas. Statistical thinking is not a natural formation, to go through statistical concepts, statistical sense , statistical concepts phases Statistical thinking is based on changes in human society needs to carry out various statistical practice, research and general statistical theory, in order to gradually form a system of statistical thinking as an applied statistics, it is to learn from the new school of mathematical statistics nutrition, and more widely used mathematical methods, more and more closely linked, but the idea reflected in the statistics on the school, compared with the general, as well as their own special its basic characteristics: (1) statistical thinking emphasis on methodological and application of the uniform; (2) statistical thinking emphasizes the unity of science and art; (3) statistical thinking emphasizes the unity of objectivity and subjectivity; (4) statistical analysis of the ideological emphasis on qualitative and quantitative analysis of the uniform.
1 means thinking. Mean the study is to be concise and important representatives mean the concept of almost all statistical theory, the basic idea is statistical. Mean thinking also requires the whole problem, but asked to observe the general development tendency to avoid the interference of the individual by chance, it also reflects the overall concept.
2 variation ideas Statistical Research similar general characteristics of the phenomenon, its premise are that the overall characteristics of each unit there is a difference of statistical methods is to understand the difference in the number of things. Statistics reflect the variation of the more basic concept is the variance, is that "variation" and "average" the concept of average and variation are the same things on the abstract features and macroscopic measurements.
3 estimated ideology is estimated to speculate that the overall sample, is the same type of things getting from here to understand method using estimation methods have a default: the same sample with the overall nature of the sample can be representative of the population but representative sample of Sex accidental factors, the theory of confidence in estimating the degree of measurement is a necessary step to maintain rigorous logic.
4 related ideas. Things are generally linked to the change, some things go hand in hand were often changed or attendant circumstances were present overall in turn, composed of many individual firms, these individual things are interrelated, and we studied things overall homogeneity is based on the formation and thus, between individuals in general, the overall total and the other is always between interrelated.
5. Fitting idea. Fit is the relationship between different types of things in the abstract representation. Any single relationship must rely on other relationships exist, all real things, relationships were very complex, this approach is the law or trend fitting. The results of fitting the model, reflecting the general trend is the trend expression "changes things and relations as reflected in the number of process models and based on this indicate the possibility."
6 test ideas. Statistical methods always inductive, the conclusion is always with a certain degree of probability, based on local characteristics and laws of the promotion cannot be completely out to determine the credibility, the inspection process is to use actual data to test samples Some characteristics of the overall number of prior assumptions are credible.
1 To change the current existence of some incorrect thinking. British biologist, statistician Galton once said: "Statistics has the extraordinary ability to deal with complex issues, when scientific explorers in the process of advancing set in the way of thorns, the only statistics that can help them open a channel.”But that is not so simple, because the reality we face the problem may be much more complex than imagined. In addition, some people think that way more complex, more Science in the actual analysis of the study, like a simple problem complicated, it seems that in order to show its scientific content. In fact, the real science is to simplify complex issues rather than the pursuit of complexity. Associated with this is that some people statistical inference is that only science, describes the statistics is not science, and extend the expansion to only mathematical statistics is a scientific, social and economic statistics is not science this understanding. This understanding is extremely wrong, at least for the ignorance of the socio-economic statistics in Belgium Kittler only to study probability theory mathematician, and focus on the statistics used in human things, trying to create a statistical improvement of society as a tool of economics and demographics in some modern concepts such as GNP, population growth rate, etc., are the legacy of Kettler and his disciples.
2 To continue to develop statistical thinking. Statistics based on inductive reasoning or the logic of inductive thinking as the main way we all know, there are two main methods of logical reasoning: inductive reasoning and deductive reasoning inductive reasoning is based on the observed data (especially incomplete or poor quality information) to generate new knowledge or to validate a hypothesis, namely to the available data based on general characteristics of induction to arrive at a conclusion. Inductive reasoning is based on information in the data chance to discover through necessity. Deductive reasoning is the ability to deepen understanding of statistics, especially in the necessity to study and understanding based on chance, the great role. |
