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Forecasting of Statistics

Nearly two thousand years have passed since a census decreed by Caesar Augustus become part of the greatest story ever told. Many things have changed in the intervening years. The hotel industry worries more about overbuilding than overcrowding, and if they had to meet an unexpected influx, few inns would have a manager to accommodate the weary guests. Now it is the census taker that does the traveling in the fond hope that a highly mobile population will stay long enough to get a good sampling. Methods of gathering, recording, and evaluating information have presumably been improved a great deal. And where then it was the modest purpose of Rome to obtain a simple head count as an adequate basis for levying taxes, now batteries of complicated statistical series furnished by governmental agencies and private organizations are eagerly scanned and interpreted by sages and seers to get a clue to future events. The Bible does not tell us how the Roman census takers made out, and as regards our more immediate concern, the reliability of present day economic forecasting, there are considerable differences of opinion. They were aired at the celebration of the 125th anniversary of the American Statistical Association. There was the thought that business forecasting might well be on its way from an art to a science, and some speakers talked about newfangled computers and high-falutin mathematical system in terms of excitement and endearment which we, at least in our younger years when these things mattered, would have associated more readily with the description of a fair maiden. But others pointed to the deplorable record of highly esteemed forecasts and forecasters with a batting average below that of the Mets, and the President-elect of the Association cautioned that “high powered statistical methods are usually in order where the facts are crude and inadequate, the exact contrary of what crude and inadequate statisticians assume.” We left his birthday party somewhere between hope and despair and with the conviction, not really newly acquired, that proper statistical methods applied to ascertainable facts have their merits in economic forecasting as long as neither forecaster nor public is deluded into mistaking the delineation of probabilities and trends for a prediction of certainties of mathematical exactitude.

1. Taxation in Roman days apparently was based on

[A]. wealth. [B]. mobility.

[C]. population. [D]. census takers.

2. The American Statistical Association

[A]. is converting statistical study from an art to a science.

[B]. has an excellent record in business forecasting.

[C]. is neither hopeful nor pessimistic.

[D]. speaks with mathematical exactitude.

3. The message the author wishes the reader to get is

[A]. statisticians have not advanced since the days of the Roman.

[B]. statistics is not as yet a science.

[C]. statisticians love their machine.

[D].computer is hopeful.

4. The “greatest story ever told” referred to in the passage is the story of

[A]. Christmas. [B]. The Mets.

[C]. Moses. [D]. Roman Census Takers.

参考答案

1. C. 人口。答案在第六句，“那时罗马计算人头作为征税的适当基础，目的很简单。” A. 财富。 B. 流动性。 C. 人口调查员。

2. A. 正把统计研究从文科转变成理科。这是从第六句开始讲的一种观点。“现在，政府机构和私人组织的一系列复杂的统计数字，由智者和先知人物殷切地浏览和解释以取得预先外未来事件的线索。圣经并没有告诉我们罗马的人口调查员是怎么调查统计的。至于我们当前更加关心的问题：目前经济预测的可靠性，意见分歧很大。美国统计协会125周年庆祝活动上，人们在大肆宣扬这些不同观点。有一种说法是经济预测可能正从文科转向科学(理科)发展。有些人兴高采烈大谈新型计算机和非常高级数学系统。”作者虽然没有明说，明眼人一看便知，艺术向科学转变正是美国统计协会在把统计学从文科转向理科。所以A. 对。 B. 在商业预测方面具有杰出的记录。不对。实际上“平均成功率还低于the Mets” C. 既没有希望也不乐观。文内没有提及。只提作者他们半喜半忧离开协会。 D. 以数学的精 确性来说话。见下道题解释。协会部分人却有此看法“数学精 确性。”

3. B. 统计学（到现在为止）还不是一门科学（理科）。文章最后几句话。“连统计协会的主席也告戒说高能统计法在实际材料原始和不允许的地方一般发挥正常。这跟低级的，不合适的统计员所假定的正好相反。我们怀着忧“希”掺半的心情离开周年庆祝宴会，怀着确实不是新近才有的信念，相信应用于确切材料上恰当的统计法在经济预测中有它的贡献，只要预测人员和公众不受蒙蔽，误呆板所述概率和趋势当作数学精 确无比的预测就行。” A. 统计员从罗马时代起就没向前进步过。 C. 统计员爱计算机。这两项文内没有提到。 D. 计算机前程远大。文内只讲了有些人怀着兴高采烈的心情大讲新型计算机和非常高级数学“系统”，暗示了计算机大有希望。但不是所有人都这样认为的。最重要的计算机的应用并不能改变这个事实：统计学不是立刻，而是文科。所以B. 对。

4. A. 基督，圣诞节，指基督的诞生。圣经中的一个故事。 B. the Mets. 圣经中率领希伯莱人出埃及的领 袖，也作放债的犹太人讲。 C. 摩西。 D. 罗马人口调查员。