# 急需英文翻譯高手!!贈20點喔！

We show that social scientists often do not take full advantage of the information available in their statistical results and thus miss opportunities to present quantities that could shed the greatest light on their research questions. In this article we suggest an approach, built on the technique of statistical simulation, to extract the currently overlooked information and present it in a reader-friendly manner.

More specifically, we show how to convert the raw results of any statistical procedure into expressions that (1) convey numerically precise estimates of the quantities of greatest substantive interest, (2) include reasonable measures of uncertainty about those estimates, and (3) require little specialized knowledge to understand.

The following simple statement satisfies our criteria: Other things being equal, an additional year of education would increase your annual income by \$1,500 on average, plus or minus about \$500. Any smart high school student would understand that sentence, no matter how sophisticated the statistical model and powerful the computers used to produce it.

The sentence is substantively informative because it conveys a key quantity of interest in terms the reader wants to know. At the same time, the sentence indicates how uncertain the researcher is about the estimated quantity of interest. Inferences are never certain, so any honest presentation of statistical results must include some qualifier, such as plus or minus \$500

in the present example.

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我們顯示社會科學家時常不充分利用在他們的統計結果得到的資料而且如此錯過機會呈現量哪一可以流出在他們的研究疑問上的最好光。 在這一個文章中，我們建議方法，在統計模擬的技術上建造，在一個讀者中探取現在忽略的資料而且呈現它－友好的方法。

We show that social scientists often do not take full advantage of the information available in their statistical results and thus miss opportunities to present quantities that could shed the greatest light on their research questions. In this article we suggest an approach, built on the technique of statistical simulation, to extract the currently overlooked information and present it in a reader-friendly manner.

更明確，我們顯示該如何把任何統計的程序的生結果轉換成傳達最好的實質興趣 (2)的量的以數字表示精確估計，包括對不確定的合理衡量大約那些估計，而且 （3) 需要一點的被特殊化的知識了解的表達（1) 。

More specifically, we show how to convert the raw results of any statistical procedure into expressions that (1) convey numerically precise estimates of the quantities of greatest substantive interest, (2) include reasonable measures of uncertainty about those estimates, and (3) require little specialized knowledge to understand.

下列的簡單陳述滿足我們的標準： 身為對手，教育的另外年的其他事物將會一般說來增加你的年度收入＄1,500，正負大約＄500. 任何的聰明高中學生將會了解句子，沒有事件如何複雜的統計模型和有力的使用的電腦生產它。

The following simple statement satisfies our criteria: Other things being equal, an additional year of education would increase your annual income by \$1,500 on average, plus or minus about \$500. Any smart high school student would understand that sentence, no matter how sophisticated the statistical model and powerful the computers used to produce it.

因為它傳達對關鍵量的興趣的，所以句子實質情報稱讀者想要知道。 同時，句子指出如何不確定的研究人員關於重要被估計的量事。 推論從不是確定的，統計結果的如此任何誠實發表一定要包括一些給與資格的人，像是正負＄500目前例子。

The sentence is substantively informative because it conveys a key quantity of interest in terms the reader wants to know. At the same time, the sentence indicates how uncertain the researcher is about the estimated quantity of interest. Inferences are never certain, so any honest presentation of statistical results must include some qualifier, such as plus or minus \$500in the present example.

Source(s): 自己

我們表示, 社會學家經常不利用的有用的資料在他們的統計結果和因而不錯過機會提出能顯示最巨大的清楚他們的研究問題的數量。在這篇文章裡我們建議方法, 被建立在統計模仿技術, 提取當前被忽略的資訊和提出它以讀者友好的方式。更加具體地, 我們顯示怎麼轉換任一個統計做法的未加工的結果成(1) 數字上表達數量的精確估計最巨大的實質的利益的表示, (2) 包括不確定性合理的措施關於那些估計, 並且(3) 要求一點專業知識瞭解。以下簡單語句滿足我們的標準: 其它事是均等, 一另外的年教育會增加您的年收入\$1,500 平均, 加上或減大約\$500 。任一名聰明的高中學生會瞭解句子, 無論複雜統計模型和強有力電腦□去□常導致它。句子實質地是情報的因為它表達興趣的一個關鍵數量在讀者想要知道的期限上。同時, 句子表明多麼不定研究員是關於估計的數量利益。推斷從未肯定, 因此統計結果的所有誠實的介紹必須包括某些合格者, 譬如加號或減\$500 在當前例子。

Source(s): 自己