Issue184[0906G文以载道三月四月小组]1月31日作业by luyaoxu

luyaoxuUID: 2588850

issue184 “It’s a grave mistake to theorize before one has data.”
[synopsis]
必要的数据是推理的基础，否则我们会倾向于主观臆想。
推理不是要等到搜集到所有的数据才可以，推理更需要推理者的细心观察和大胆想象。
判断理论的正确性不是作者认为的符合搜集到的数据，正确的理论可以预测新的未来的现象。

[writing]
Concerning about research methods which have a profound potential influence on the efficiency of breakthroughs in science and technology, whether should we collect as much data as possible before extrapolation, or should we theorize intrepidly first and seek for validation prudentially afterwards? Is it a “grave” mistake to theorize without data, as the speaker contends? I concede that sufficient data is needed before theorizing so as to avoid theorists' personal proneness and desires. However, the speaker obviously ignores the equally grave consequence of waiting to theorize until we obtain too much data. Most importantly, in a sence the speaker begs the question by overlooking the true santandard that is used to evaluate a theory.

In one important respect I agree with the speaker's contention. A theory conjured up with no benefit of data amounts to little more than the theorists' own hopes and desires-what he wants to be true or not. Accordingly, the theorist will incline to dig out the data and facts that support or lend credit to his theory and neglect the data which refutes it. One telling historical example is the center of the universe. Because of the human’s egotism and superiority complex, for a long time, th haman takes it for granted that the universe revolves around us. Early theories were presumed for this, and subsequent observation that ran contraray to this ego-driven theory were ignored,while the observers were scorned and even vilified.

Though data is the carrier of the theory, there is no need to postpone theorizing until too much data collected, let alone all data. Actually, the theorists' keen observation and bold conjecture are the key factors during the process to make discoveries. To illustrate the point, we need to look no further than De Brolie who became the first one who discovered the wave-particle dulity theory inspired by his historic logic. Despite before De Brolie, many scientists have found that light has the characteristic of both wave and particle on the basis of some experimental data,  only he dared to combine both attibutes creatively and  made a big breakthrough in physics. In short, if one gets no data, surely he will take high risk to theorize, but it's the wit and courage of the theorist that truly matter in the way to make great discoveries.

Finally, the speaker misaprehends the standard used to assess the validity of a theory as the data collected before theorizing. In fact, an effective way to evaluate a theory to predict new facts and data according to itself. Surfing in the scientific history of development, countless great theories go through this to become widely accepted such as time-space effect proposed by Albert Einstein or famous mechanical theory raised by Newton and so on.

In conclusion, data, in some extent, could imply the sucessful chance of a theory, but it seems to us that we should be more flexible and sapiential when adopting the approach to theorize according to the specific acadamic fields and situations. An adherence to the order between theorizing and data would pose detrimental influence on the science developments. Besides, the utimate justice is new facts.

waidswUID: 2256074

Concerning about research methods which have a profound potential influence on the efficiency of breakthroughs (what is efficiency of breakthrough, I think it might be correctness) in science and technology, whether should we collect as much data as possible before extrapolation, or should we theorize intrepidly first and seek for validation prudentially afterwards? Is it a “grave” mistake to theorize without data, as the speaker contends? I concede that sufficient data is needed before theorizing so as to avoid theorists' personal proneness and desires. However, the speaker obviously ignores the equally grave consequence of waiting to theorize until we obtain too much data. Most importantly, in a sense the speaker begs the question by overlooking the true standard that is used to evaluate a theory.(what is true standard? I think it is a little bit confusing here)

In one important respect I agree with the speaker's contention. A theory conjured up with no benefit of data amounts to little more than the theorists' own hopes and desires-what he wants to be true or not. Accordingly, the theorist will incline to dig out the data and facts that support or lend credit to his theory and neglect the data which refutes it. One telling historical example is the center of the universe. Because of the human’s egotism and superiority complex, for a long time, human takes it for granted that the universe revolves around us. Early theories were presumed for this, and subsequent observation that ran contrary to this ego-driven theory were ignored, while the observers were scorned and even vilified.

Though data is the carrier of the theory, there is no need to postpone theorizing until too much data collected, let alone all data. Actually, the theorists' keen observation and bold conjecture are the key factors during the process to make discoveries. To illustrate the point, we need to look no further than De Brolie who became the first one who discovered the wave-particle duality theory inspired by his historic logic. Despite before De Brolie, many scientists have found that light has the characteristic of both wave and particle on the basis of some experimental data,  only he dared to combine both attributes creatively and  made a big breakthrough in physics. In short, if one gets no data, surely he will take high risk to theorize, but it's the wit and courage of the theorist that truly matter in the way to make great discoveries.

Finally, the speaker misapprehends the standard used to assess the validity of a theory as the data collected before theorizing. In fact, an effective way to evaluate a theory to predict new facts and data according to itself. (what does this sentence mean?)Surfing in the scientific history of development, countless great theories go through this to become widely accepted such as time-space effect proposed by Albert Einstein or famous mechanical theory raised by Newton and so on. (it is kind of blurring, you should argue it more clearly that data is for verifying rather than a prerequisite. )

In conclusion, data, in some extent, could imply the sucessful chance ( correctness) of a theory, but it seems to us that we should be more flexible and sapiential when adopting the approach to theorize according to the specific academic fields and situations. An adherence to the order between theorizing and data would pose detrimental influence on the science developments. Besides, the utimate justice is new facts.(It might be better if you describe the last sentence more clear)

Generally it is a good issue. But I think you should have state your idea more clearly so that the grader could understand you better. And be careful for the minor spelling errors.