issue184 [OB小组] 第16次作业 controversial researches

phillipsareaUID: 2318537

题目：ISSUE184 - "It is a grave mistake to theorize before one has data."
字数：552          用时：00:50:00          日期：2007-7-28 下午 09:49:47
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The author claims that it's a grave mistake to theorize before one has data. In my view, while I am firmly confirmed that practice is the best way to build up a theory, it's necessary for the scientist to make some experiments and then find the orderliness among the statistic result to build up a theory. However, compared with the data, the author begs the question by totally negating the value of theorizing.

To begin with, it's true that data has its special value when finding an orderliness to build a theory in experiment. For example, it's at present impossible for us to theorize the move of each planet. However, scientists make some records of how they move every month, every year even every decades in order to find the orderliness among its move. Since the testing year is long enough and our test result is based on its average move line, the result becomes credible. In addition, sometimes it's too difficult for people to build up a theory without the support of data. The statistic of population is just a case in point. Almost every decade the countries will make a statistic to analyse the possible tendency of the growing population. Only when we make a statistic first can we predict how it ranges, keep increasing or just decrease. Thus, in some situations, data has its special value to build up a theory.

However, there're things in some fields that cannot be quantitatively tested. For instance, when people are evaluating an art work, what data can they rely on? After a simple analysis, we consider it to be a Gothic one, but it's a result without any data to base on. Thus, unlike mathematics or economics, art is based on inspiration and practice. In this way, the theories are built without the help of data. Another case is the principle of relativity. At the time Einstein discover the orderliness in time and speed, the condition of experiments doesn't allow him to have a test to testify the correctness of his theory, however, he testified his theory theoretically, which people find it's true through a large number of experiments. Hence, when sometimes it's not possible for us to get the data of a experiment, it's necessary for us to make a theory without data.

Moreover, data is not always credible and correct as well. When we simply form a theory based on the data, it may lead to serious result. In some circumstance, the data may be less credible since we don't do enough amounts of experiments. In this way, we build up a wrong theory based on those inaccurate data, and when we use this theory practically, we may waste much money, time and manpower. Therefore, the data is not always correct and we should combine the data with the theory together.

All in all, from what has been discussed above, we can easily draw our conclusion that in most time, it's necessary for us to theorize before one has data. Meanwhile, sometimes we cannot experiment to get the data or the data is less credible, it's necessary for us to build up a theory without data. In final analysis, only when we combine the application of data and the process of theorizing together can we build up a correct theory.

[ 本帖最后由 phillipsarea 于 2007-7-28 21:59 编辑 ]

stonescjUID: 2359180

The author claims that it's a grave mistake to theorize before one has data. In my view, while I am firmly(很坚定的语气词，看下面怎么说明了) confirmed that practice is the best way to build up a theory, it's necessary for the scientist to make some experiments and then find the orderliness among the statistic result to build up a theory. (怎么感觉和下句接不上？)however, compared with the data, the author begs the question by totally negating the value of theorizing.

To begin with, it's true that data has its special value when finding an orderliness to build a theory in experiment. For example, it's at present impossible for us to theorize the move of each planet. However, scientists make some records of how they move every month, every year even every decades in order to find the orderliness among its move. Since the testing year is long enough and our test result is based on its average move line, the result becomes credible. (这个例子不是很明白，结论是不是有点牵强？)In addition, sometimes it's too difficult for people to build up a theory without the support of data. The statistic of population is just a case in point. Almost every decade the countries will make a statistic to analyse the possible tendency of the growing population. Only when we make a statistic first can we predict how it ranges, keep increasing or just decrease. Thus, in some situations, data has its special value to build up a theory.

However, there're things in some fields that cannot be quantitatively tested. For instance, when people are evaluating an art work, what data can they rely on? After a simple analysis, we consider it to be a Gothic one, but it's a result without any data to base on. Thus, unlike mathematics or economics, art is based on inspiration and practice. In this way, the theories are built without the help of data. Another case is the principle of relativity. At the time Einstein discover the orderliness in time and speed, the condition of experiments doesn't allow him to have a test to testify the correctness of his theory, however, he testified his theory theoretically, which people find it's true through a large number of experiments. Hence, when sometimes it's not possible for us to get the data of a experiment, it's necessary for us to make a theory without data.//这段论述不错，呵呵

Moreover, data is not always credible and correct as well. When we simply form a theory based on the data, it may lead to serious result. In some circumstance, the data may be less credible since we don't do enough amounts of experiments. In this way, we build up a wrong theory based on those inaccurate data, and when we use this theory practically, we may waste much money, time and manpower. Therefore, the data is not always correct and we should combine the data with the theory together.//角度也很好，补充说明了一下

All in all, from what has been discussed above, we can easily draw our conclusion that in most time, it's necessary for us to theorize before one has data. Meanwhile, sometimes we cannot experiment to get the data or the data is less credible, it's necessary for us to build up a theory without data. In final analysis, only when we combine the application of data and the process of theorizing together can we build up a correct theory.//句式可以变换下
总体结构很清晰，层次也还不错，呵呵

ldongxpUID: 2311083

The author claims that it's a grave mistake to theorize before one has data. In my view, while I am firmly confirmed that practice is the best way to build up a theory, it's necessary for the scientist to make some experiments and then find the orderliness among the statistic result to build up a theory. However, compared with the data, the author begs the question by totally negating the value of theorizing. [这个表达。。。]

To begin with, it's true that data has its special value when finding an orderliness to build a theory in experiment. For example, it's at present impossible for us to theorize the move of each planet. However, scientists make some records of how they move every month, every year even every decades in order to find the orderliness among its move. Since the testing year is long enough and our test result is based on its average move line, the result becomes credible. In addition, sometimes it's too difficult for people to build up a theory without the support of data. The statistic of population is just a case in point. Almost every decade the countries will make a statistic [census] to analyze the possible tendency of the growing population. Only when we make a statistic first can we predict how it ranges, keep increasing or just decrease. [跟theory是不是有点距离] Thus, in some situations, data has its special value to build up a theory.

However, there're things in some fields that cannot be quantitatively tested. For instance, when people are evaluating an art work, what data can they rely on? [观点蛮好] After a simple analysis, we consider it to be a Gothic one, but it's a result without any data to base on. Thus, unlike mathematics or economics, art is based on inspiration and practice. In this way, the theories are built without the help of data. Another case is the principle of relativity. At the time Einstein discover the orderliness [换个词，比如law什么的] in time and speed, the condition of experiments doesn't allow him to have a test to testify the correctness of his theory, however, he testified his theory theoretically, which people find it's true through a large number of experiments [later]. Hence, when sometimes it's not possible for us to get the data of a experiment, it's necessary for us to make a theory without data.

Moreover, data is not always credible and correct as well. When we simply form a theory based on the data, it may lead to serious result. In some circumstance, the data may be less credible since we don't do enough amounts of experiments. In this way, we build up a wrong theory based on those inaccurate data, and when we use this theory practically, we may waste much money, time and manpower. Therefore, the data is not always correct and we should combine the data with the theory together.
All in all, from what has been discussed above, we can easily draw our conclusion that in most time, it's necessary for us to theorize before one has data. Meanwhile, sometimes we cannot experiment to get the data or the data is less credible, it's necessary for us to build up a theory without data. In final analysis, only when we combine the application of data and the process of theorizing together can we build up a correct theory.