收錄英語現(xiàn)代文優(yōu)秀作品,語言優(yōu)美地道,風(fēng)格簡(jiǎn)潔明快,文體應(yīng)用廣泛,適合背誦與模仿。
涉及社會(huì)生活、人文科學(xué)、自然科學(xué)等領(lǐng)域眾多題材,
四六級(jí)、托福、雅思、GRE考試??荚掝}盡數(shù)涵蓋。
開始我們的聽力背誦之旅吧~~
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 government units (states 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.
Describing collections 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 of problems characteristically involves 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 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.
統(tǒng)計(jì)方法的早期發(fā)展受到兩種截然不同的影響。統(tǒng)計(jì)學(xué)有一個(gè)"母親",她致力于井井有條地記錄政府機(jī)構(gòu)的文件(國家和統(tǒng)計(jì)學(xué)這兩個(gè)詞源于同一個(gè)拉丁語詞 根,status),還有一個(gè)有紳士般的賭博"父親",他依靠數(shù)學(xué)來提高賭技,以便在幾率的游戲中取勝。"母親"對(duì)其子女統(tǒng)計(jì)學(xué)的影響表現(xiàn)在計(jì)數(shù)、測(cè)量、 描述、制表、歸類和人口普查。所有這些導(dǎo)致了現(xiàn)代描述統(tǒng)計(jì)學(xué)的誕生。由于"父親"的影響則產(chǎn)生了完全基于概率論原理的現(xiàn)代推理統(tǒng)計(jì)學(xué)。
描述統(tǒng)計(jì)學(xué)涉及對(duì)所收集數(shù)據(jù)的制表、制圖和描述。這些數(shù)據(jù)可以是數(shù)量性的數(shù)據(jù),如高度、智商、或者是層級(jí)性的數(shù)據(jù)--具有連續(xù)性的變量--或數(shù)據(jù)也可以代 表性質(zhì)變量,如性別、大學(xué)專業(yè)或性格類型等等。數(shù)量龐大的數(shù)據(jù)通常必須經(jīng)過概括或刪減的程序才能為人所理解。描述統(tǒng)計(jì)學(xué)就是這樣一個(gè)工具,它對(duì)極其龐雜的 數(shù)據(jù)進(jìn)行描述、概括或刪減,使其變成能為人理解的東西。
推理統(tǒng)計(jì)學(xué)是一套已定形了的方法體系,它解決的是光憑人腦極難解決的另一類問題。這類問題的顯著特點(diǎn)是試圖通過取樣調(diào)查來作出預(yù)測(cè)。例如,有一位教育督察 想知道在一個(gè)龐大的學(xué)校系統(tǒng)中,不吃早飯就上學(xué)的學(xué)生、已經(jīng)做過防感冒免疫的學(xué)生,或其它任何類型的學(xué)生占多大比例。若具備一些統(tǒng)計(jì)學(xué)的知識(shí),這位督察應(yīng) 明白,詢問每個(gè)孩子是沒有必要而且沒有效率的,只要用100個(gè)孩子為樣本,他就可以相當(dāng)精確地得出這些孩子占整個(gè)學(xué)區(qū)的比例了。因此,推理統(tǒng)計(jì)學(xué)的目的就 是通過了解一個(gè)群體中一些樣本的特性,從而對(duì)整個(gè)群體的特性進(jìn)行推測(cè)和估算。