解放军文职招聘考试Statistics

 Statistics

There were two widely divergent influences on the early development of

statistical methods. Statistics had a mother who was dedicated to keeping

orderly records of governmental units (state and statistics come from the

same Latin   root status) and a  gentlemanly gambling father who relied on

mathematics to increase his skill at playing the odds    in games of chance.

The influence of the  mother on the offspring, statistics, is represented 

by counting, measuring, describing, tabulating,  ordering,  and  the 

taking  of  censuses  --  all  of  which  led  to  modern  descriptive

statistics. From the influence of  the father came  modern  inferential

statistics,  which  is based squarely on    theories of probability.

Descriptive statistics involves tabulating, depicting and describing

collections of data. These data may be      quantitative such as measures of

height, intelligence or grade level -- variables that are characterized by

an   underlying continuum -- or the data may represent qualitative variables,

such as sex, college major or personality  type. Large masses of data must

generally undergo a process of summarization or reduction before they are

comprehensible. Descriptive statistics is a tool for  describing  or

summarizing or reducing to  comprehensible  form   the properties of an

otherwise unwieldy mass of data.

Inferential statistics is a formalized body of methods for solving another

class of problems that  present  great    difficulties  for  the  unaided 

human  mind.  This  general  class  of  problems characteristically 

involve  attempts  to  make  predictions  using  a  sample  of 

observations.  For example, a school superintendent wishes to determine the

proportion of children in a large school system who come to school without

breakfast, have been vaccinated for flu, or whatever. Having a  little 

knowledge  of  statistics,  the  superintendent  would  know  that  it  is 

unnecessary  and inefficient to question each child: the proportion for the

entire district could be estimated fairly

accurately    from a sample of as few as 100 children. Thus, the purpose of

inferential statistics is to predict or estimate    characteristics of a

population from a knowledge of the characteristics of only a sample of the

population.

统计学

统计方法的早期发展受到两种截然不同的影响。  统计学有一个"母亲"，她致力于井井

有条地记录政府机构的文件(国家和统计学这两个词源于同一个拉丁语词根，status)，还有一

个有绅士般的赌博"父亲"，他依靠数学来提高赌技，以便在几率的游戏中取胜。  "母亲"对

其子女统计学的影响表现在计数、测量、描述、制表、归类和人口普查。  所有这些导致了 现代描述统计学的诞生。 

由于"父亲"的影响则产生了完全基于概率论原理的现代推理统计 学。  描述统计学涉及对所收集数据的制表、制图和描述。  这些数据可以是数量性的数据，

如高度、智商、或者是层级性的数据--具有连续性的变量--或数据也可以代表性质变量，如 性别、大学专业或性格类型等等。 

数量庞大的数据通常必须经过概括或删减的程序才能为 人所理解。  描述统计学就是这样一个工具，它对极其庞杂的数据进行描述、概括或删减，

使其变成能为人理解的东西。  推理统计学是一套已定形了的方法体系，它解决的是光凭人 脑极难解决的另一类问题。 

这类问题的显著特点是试图通过取样调查来作出预测。  例如， 有一位教育督察想知道在一个庞大的学校系统中，不吃早饭就上学的学生、已经做过防感冒

免疫的学生，或其它任何类型的学生占多大比例。  若具备一些统计学的知识，这位督察应 明白，询问每个孩子是没有必要而且没有效率的，只要用 100

个孩子为样本，他就可以相当 精确地得出这些孩子占整个学区的比例了。  因此，推理统计学的目的就是通过了解一个群

体中一些样本的特性，从而对整个群体的特性进行推测和估算。