## 统计代写|描述统计学代写Descriptive statistics代考|Structure and Nature of Socio-Economic Data: The Aggregates

statistics-lab™ 为您的留学生涯保驾护航 在代写描述统计学Descriptive statistics方面已经树立了自己的口碑, 保证靠谱, 高质且原创的统计Statistics代写服务。我们的专家在代写描述统计学Descriptive statistics代写方面经验极为丰富，各种代写描述统计学Descriptive statistics相关的作业也就用不着说。

• Statistical Inference 统计推断
• Statistical Computing 统计计算
• (Generalized) Linear Models 广义线性模型
• Statistical Machine Learning 统计机器学习
• Longitudinal Data Analysis 纵向数据分析
• Foundations of Data Science 数据科学基础

## 统计代写|描述统计学代写Descriptive statistics代考|Surveying the ‘Real-Life-Objects’

The process which transforms the ‘real-life-objects’ into ‘statistical-counting-units’ usually is the statistical survey. It can be a census, a sample, or some administrative listing that exists for other purposes but is made available to statistics.

Known is the population census. There are other, less known economic census operations: census of agriculture, of mining, manufacturing, whole-sale-retail establishments, and service industries. Even less known is the US census of governments, in which the local governments in the US are the real-life-objects. Because a census is a costly, major operation that requires a legal basis, a professional staff and big budget allocations, it is carried out only at 5 or 10 year intervals, and the different censuses are scheduled at different times because of the limited administrative capacity of census bureaus.

Another matter are the abundant sample surveys. Unless they are undertaken by a public or private professional sampling organization, they seldom serve a serious statistical purpose, but are used as a pretext to draw attention to a new product or some political cause.

Statistical theory has spent much thought and effort on improving the sample design in selecting the real-life-objects and managing the inevitable (mathematical) sampling error. As already mentioned, sampling theory and inference has dominated the discussion of statistics at the expense of nearly everything else.

This statistical process extracts from the rich reality of the existing ‘real-lifeobjects a simplified – and often distorted – sketch of it on a questionnaire or other means of recording. It is a reduction process that is not reversible: The real-life object, e.g. a human person, cannot be reconstructed from a questionnaire, regardless of how much detail it contains and how conscientiously it has been filled out. Furthermore, once recorded, each ‘statistical-counting-unit’ starts its own existence, separate from, and independent of that of the real-life object. Even if the latter should disappear completely, the ‘statistical-counting-unit’ remains, as a lasting testimony to the former’s existence. When tabulated, it survives even the destruction of the original record, on a questionnaire, punch-card, magnetic tape, CD or other device.

Statistical surveys record the real-life-objects in isolation from their socio-economic context. Usually real-life-objects of one kind are enumerated together, such as the dairy farms located in a country in a census of agriculture. Different types of real-life-objects are surveyed at different times, by different agencies, usually according to different criteria and definitions. No integral census has yet been accomplished that would report together human beings, factories, farms, mines, wholesale and retail establishments, banks and other service establishments, with their relevant characteristics. This inability to survey the entire society and its activities together, at the same time, results in discrepancies and variations in the data that have nothing to do with chance occurrences in the economy, but result from the truncation of socio-economic phenomena through the statistical process

## 统计代写|描述统计学代写Descriptive statistics代考|The ‘Statistical-Counting-Units’

It is interesting to consider the differences between “measurement” in the natural sciences and the corresponding statistical activity in the social sciences. In the natural sciences these measurements are the result of observations by objective especially trained observers, like in the bio sciences, so to speak from the outside of the thing to be measured. In the socio-economic setting the person providing the information e.g. in a population survey, really is the “object” to be observed. That selfreported information from many different informants of varying competence and intelligence is collected by survey takers, who themselves often are insufficiently prepared for that task, acting mostly as mail carriers, not like the observers in the natural sciences. The truthfulness and accuracy of such information depends on the cooperation of these interviewees, a matter that cannot be guaranteed, despite existing laws that require it. Neither their honesty nor the accuracy of their memory can be guaranteed. That is a fundamental, important difference between socio-economic statistical data and the measurement data in the natural sciences.

Statistical data have been variously classified. The distinction in ‘Punkt- and Streckenmassen’15 (point- and line masses), for example, is based on the length of life of the real-life-objects: some real-life-objects are perceived as being points in time, of short duration. Others last long, occupying a ‘Strecke’ that is, a considerable stretch of time. But every real-life-object has a certain duration. Considering its life span as point-like and short, or as long lasting, is a relative matter. Moreover, this distinction ignores the fact, that we do not deal with the real-life-objects themselves but with the ‘statistical-counting-units’ which are, by their nature, points in time and space, regardless of the length of life of the real-life object.

Another distinction in ‘Bestands- and Bewegungsmassen’ – inventories of a mass of stationary real-life-objects and masses of moving real-life-objects that are not stationary – is based on the spurious distinction between existence-units which are real-life objects that remain in their location without moving, and motion-units, that is, real-life objects that are on the move, without a fixed relation to a place in a geographic region. That obscures the fact, that every ‘statistical-counting-unit’ is a static record, fixed in a certain time and location, regardless of whether a real-lifeobject is static or dynamic. ${ }^{16}$

A distinction could be made between different types of ‘statistical-countingunits’ according to the occasion of their registration:

1. Real-life-objects are contacted by mail, telephone or personal visit by a concerted effort to record them, and approached at a certain point in time as in a census or sample survey, or
2. A government or private institution records the real-life object on the occasion of some event that triggers a registration, such as a beginning of something, a change of its characteristics, or its termination, carried out for other than statistical purposes. Typical is the registration of the birth of a child, the issue of a building permit for an addition to an existing building or for a new building, the registration of the bankruptcy of a firm (death), or the periodic re-registration of motor vehicles. In most of these instances the registration is requested by law,is carried out as a continuing operation, often for the purpose of taxation, not originally for statistical purposes.

## 统计代写|描述统计学代写Descriptive statistics代考|The Tri-Dimensional Frame of an Aggregate

Socio-economic phenomena deal not only with a subject-matter aspect but also with a time and a regional-geographic aspect. The real-life-objects, and their corresponding ‘statistical-counting-units’ that portray those phenomena, partake in those three aspects that can be conveniently visualized as the three perpendicular vectors or dimensions of a coordinate system. This means that every aggregate ${ }^{1}$ that deals with socio-economic phenomena can be understood as occupying a tri-dimensional space like in a Cartesian coordinate system (Fig. 3.1).

The subject-matter dimension can be presented on the vertical vector of a statistical aggregate, or on any other of the vectors, if so preferred. The sub-divisions of the subject-matter, e.g. the major groupings of the classification of economic activities, can be indicated in linear form by corresponding tick-marks. ${ }^{2}$

For the social sciences the development of phenomena over time is of great interest. Time, therefore, should be marked on the second vector of that – still empty – Cartesian space, facing the observer, using the customary subdivisions of the calendar (months, quarters, semesters).

On the third, geographic vector, the administrative regions are plotted as a onedimensional sequence. Regional districts, reduced to linear form, are projected on the geographic vector. Figure $3.2$ shows the tri-dimensional frame of a statistical aggregate before the ‘statistical-counting-units’ are placed into it. One could imagine this empty space framed by the three vectors to look like an empty fish tank with its three dimensions.

It is important to recognize that these three dimensions are present in all statistical data. This is easily overlooked, because data published in tabular form usually present only two of these three dimensions, either the subject-matter and time, or the subject-matter and geographic-territorial-dimension. This is true as much for aggregates as it is for other data-materials that are derived from aggregates.

When the time dimension is small, like in a census or inventory, the tri-dimensional character of a statistical aggregate shrinks to a seemingly two-dimensional sheet and is easily overlooked. Yet, like a sheet of paper that, regardless how thin it may be, still has a thickness that becomes evident when e.g. 500 sheets of such thin papers are packaged as a ream. In the case of a survey, the time dimension of the resulting data consists of those few hours or days – in a census of a big country that may be many months – needed to accomplish the field work, capturing a specific socio-economic phenomenon at that particular point in time. It may take that long to locate the respective ‘real-life-objects,’ to interview or canvass them and forward the result to a central location, an office, to produce the ‘statistical-counting-units’. The placement of the resulting aggregates on the time vector, Fig. 3.3, is important, because it allows to connect them to other statistical and non-statistical materials. ${ }^{3}$

## 统计代写|描述统计学代写Descriptive statistics代考|The ‘Statistical-Counting-Units’

“Bestands-and Bewegungsmassen”中的另一个区别——大量静止的现实生活对象和大量非静止的移动现实生活对象的清单——是基于现实生活中的存在单位之间的虚假区别保持在其位置而不移动的对象，以及运动单元，即移动中的真实对象，与地理区域中的位置没有固定关系。这掩盖了这样一个事实，即每个“统计计数单元”都是静态记录，固定在某个时间和地点，无论现实生活中的对象是静态的还是动态的。16

1. 现实生活中的对象通过邮件、电话或个人访问进行联系，共同努力记录它们，并在某个时间点（如在人口普查或抽样调查中）接近，或
2. 政府或私人机构在某些触发注册的事件之际记录现实生活中的对象，例如出于统计目的以外的目的进行的某事的开始、其特征的变化或终止。典型的例子是孩子的出生登记、为现有建筑物增建或新建建筑物的建筑许可证的签发、公司破产（死亡）的登记或汽车的定期重新登记汽车。在大多数情况下，注册是法律要求的，是作为持续经营进行的，通常是出于税收目的，而不是最初用于统计目的。

## 有限元方法代写

tatistics-lab作为专业的留学生服务机构，多年来已为美国、英国、加拿大、澳洲等留学热门地的学生提供专业的学术服务，包括但不限于Essay代写，Assignment代写，Dissertation代写，Report代写，小组作业代写，Proposal代写，Paper代写，Presentation代写，计算机作业代写，论文修改和润色，网课代做，exam代考等等。写作范围涵盖高中，本科，研究生等海外留学全阶段，辐射金融，经济学，会计学，审计学，管理学等全球99%专业科目。写作团队既有专业英语母语作者，也有海外名校硕博留学生，每位写作老师都拥有过硬的语言能力，专业的学科背景和学术写作经验。我们承诺100%原创，100%专业，100%准时，100%满意。

## MATLAB代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中，其中问题和解决方案以熟悉的数学符号表示。典型用途包括：数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发，包括图形用户界面构建MATLAB 是一个交互式系统，其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题，尤其是那些具有矩阵和向量公式的问题，而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问，这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展，得到了许多用户的投入。在大学环境中，它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域，MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要，工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数（M 文件）的综合集合，可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。

## 统计代写|描述统计学代写Descriptive statistics代考|Location, Extension and Mobility of ‘Real-Life-Objects’

statistics-lab™ 为您的留学生涯保驾护航 在代写描述统计学Descriptive statistics方面已经树立了自己的口碑, 保证靠谱, 高质且原创的统计Statistics代写服务。我们的专家在代写描述统计学Descriptive statistics代写方面经验极为丰富，各种代写描述统计学Descriptive statistics相关的作业也就用不着说。

• Statistical Inference 统计推断
• Statistical Computing 统计计算
• (Generalized) Linear Models 广义线性模型
• Statistical Machine Learning 统计机器学习
• Longitudinal Data Analysis 纵向数据分析
• Foundations of Data Science 数据科学基础

## 统计代写|描述统计学代写Descriptive statistics代考|Location, Extension and Mobility of ‘Real-Life-Objects’

Every ‘real-life-object’ has a definite relation to its location. Reference to it as the ‘geographic characteristic’ treats location as an intrinsic quality of an object, at a par with other characteristics. This assessment is inaccurate, however, and prevented statistical theory from dealing with the geographic dimension of socio-economic phenomena. Regional phenomena differ due to the special economic and environmental characteristics of each area, which are implied and summarily stated through a ‘real-life-objects’ geographic location. Even ‘real-life-objects’ with only a symbolic, minimal physical substance like the sale of a car or the issuance of a mortgage happen in a place on the map. The geographical location on which a sale takes place, though not an attribute of the ‘real-life-object’ ‘sale’ is, like the time at which it happened, important for grouping these objects into meaningful aggregates (more in Chap. 3).

Every object also has a geographic extension. A farm occupies a certain amount of land with certain surface and soil characteristics. So does a strike which takes place in some production plant. The plant’s physical and geographic extension is usually also the geographic extension of that ‘strike.’

Objects can be fixed or mobile with regard to their location. Most ‘real-life-objects’ are neither absolutely fixed, nor completely mobile. Even houses and large firms have been moved to different locations. It is the high mobility of some ‘real-life-objects’ that creates problems for statistics. Examples are the whereabouts of the rolling stock of a trucking firm or of a railroad company. These problems create uncertainty, not unlike the measuring problems in atomic physics.

## 统计代写|描述统计学代写Descriptive statistics代考|Attributes and Variables

These ‘real-life-objects’ project an economic phenomenon through their properties. The attributes – qualitative characteristics or non-measurable variables – of these real-life-objects describe pervasive, essential aspects of an object, through non-numeric, nominal description. They cannot be determined with accuracy or measured on an interval or ratio scale. Quantitative characteristics, on the other hand, expressing intensity or the magnitude of some feature, can be determined accurately, but contribute little to characterize the object. ${ }^{13}$ Both kinds of determining the characteristics of a ‘real-life-object’ are needed as mutual complements. ${ }^{14}$
Every property which characterizes a ‘real-life-object’ may be understood as a partial description of its nature. Behind the customary distinction in qualitative characteristics (attributes) and quantitative characteristics (variables) really is another distinction, according to the width of the segment of the integral nature of the ‘reallife-object’ which is provided by a given characteristic. Qualitative characteristics capture in literary form essential and pervasive aspects of the ‘real-life-object,’ but cannot be determined succinctly. The wider that slice out of the nature of a ‘reallife-object’, a specific attribute, the less precisely can it be determined. The so-called quantitative characteristics, on the other hand, refer to narrow segments of the nature of the ‘real-life-object’ which can be determined more accurately. The narrower this segment, the more precisely it can be captured (measured), but the less information is obtained concerning that ‘real-life-object’.

As a first approximation, a wide part of the nature of a ‘real-life-object’ is described through a qualitative characteristic. In consecutive, progressively finer determinations (descriptions) the nature of that initial segment of the ‘real-lifeobject’ is then further defined. At the end of such a wedge-like penetration into the nature of the ‘real-life-object’, quantitative, measurable characteristics can add the sharpness that was missing in the initial description by the attributes. The same holds for the tabulations made of such characteristics of the ‘real-life-objects.’

When the ‘real-life-object’ is an occurrence, it is also characterized by the ‘reallife-object’ to which it belongs, or on which it is happening. The characteristics of non-individualized ‘real-life-objects,’ e.g. raw materials, are summarily estimated. From the socio-economic point of view they usually are of little interest – although they may be of interest e.g. from a quality-control, that is, engineering point-of-view.
To summarize, the qualitative description alone is imprecise, e.g. a firm described only by the nature of its products. The quantitative description alone has little meaning, e.g. a firm described only by the number of its employees, or the size of last month’ sales, without an indication of its qualitative characteristics like the industry to which it belongs, the kind of products, form of ownership, capital structure, etc. The description of a ‘real-life-object’ by attributes does not need to be supplemented by quantitative characteristics – measurements – in order to be comprehensible.

## 统计代写|描述统计学代写Descriptive statistics代考|From ‘Real-Life-Object’ to ‘Statistical-Counting-Unit’

The printed socio-economic data do not directly deal with the ‘real-life-objects’ that were discussed, but with simplified statistical sketches of these, that I would like to call the ‘statistical-counting-units.’ It is these that are tabulated, not the ‘real-life-objects’ themselves. The user of statistical data knows only about those ‘real-life-objects’ of which questionnaires or computer accessible evidence – the ‘statistical-counting-units’ – exist. A clear distinction must be made between the ‘real-life-objects’ out there in reality, and the ‘statistical-counting-units, the sketches of these ‘real-life-objects’ in electronic or in other storable form. That seemingly subtle distinction, however, is important and must be kept in mind when interpreting socio-economic data (Fig. 2.1).

## 有限元方法代写

tatistics-lab作为专业的留学生服务机构，多年来已为美国、英国、加拿大、澳洲等留学热门地的学生提供专业的学术服务，包括但不限于Essay代写，Assignment代写，Dissertation代写，Report代写，小组作业代写，Proposal代写，Paper代写，Presentation代写，计算机作业代写，论文修改和润色，网课代做，exam代考等等。写作范围涵盖高中，本科，研究生等海外留学全阶段，辐射金融，经济学，会计学，审计学，管理学等全球99%专业科目。写作团队既有专业英语母语作者，也有海外名校硕博留学生，每位写作老师都拥有过硬的语言能力，专业的学科背景和学术写作经验。我们承诺100%原创，100%专业，100%准时，100%满意。

## MATLAB代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中，其中问题和解决方案以熟悉的数学符号表示。典型用途包括：数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发，包括图形用户界面构建MATLAB 是一个交互式系统，其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题，尤其是那些具有矩阵和向量公式的问题，而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问，这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展，得到了许多用户的投入。在大学环境中，它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域，MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要，工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数（M 文件）的综合集合，可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。

## 统计代写|描述统计学代写Descriptive statistics代考|Different Types of ‘Real-Life-Objects’

statistics-lab™ 为您的留学生涯保驾护航 在代写描述统计学Descriptive statistics方面已经树立了自己的口碑, 保证靠谱, 高质且原创的统计Statistics代写服务。我们的专家在代写描述统计学Descriptive statistics代写方面经验极为丰富，各种代写描述统计学Descriptive statistics相关的作业也就用不着说。

• Statistical Inference 统计推断
• Statistical Computing 统计计算
• (Generalized) Linear Models 广义线性模型
• Statistical Machine Learning 统计机器学习
• Longitudinal Data Analysis 纵向数据分析
• Foundations of Data Science 数据科学基础

## 统计代写|描述统计学代写Descriptive statistics代考|Different Types of ‘Real-Life-Objects’

Understanding those ‘real-life-objects’ is a first step of data interpretation. A great variety of such ‘real-life-objects’ exists, that act as projecting agents’ ${ }^{10}$ for socioeconomic phenomena. Human beings are the most important of the great variety of ‘real-life-objects’ that are of interest to society – no offense is meant when referring to human beings as ‘real-life-objects’ as a technical-statistical term. It can be an individual person, or a group of persons, like a ‘family’, a ‘household’ or other groups of people, e.g. in a mental institution, in hospitals, jails, or retirement homes.
These ‘real-life-objects’ can also be things related to socio-economic activities, such as mines, farms, retail establishments, production plants, railroad companies (with their rail network), corporations, but also machines, farm animals, and produced goods. Political-administrative districts can become ‘real-life-objects’, such as counties, metropolitan areas, census tracts, even plots of land cultivated with certain field crops. Other, quite different kinds of ‘real-life-objects’ can be legal documents like shares, mortgages, vehicle registrations, birth certificates, building permits and bonds.

The most frequent kind of ‘real-life-objects’, however, are neither people nor buildings or things. They are occurrences of social relevance, such as sales, strikes, accidents. Into this category of ‘real-life-objects’ belong events that are beginnings e.g. the birth of a person, foundation of a firm, issuance of a share, the issue of a construction permit or the creation of a new job, changes e.g. in the occupation of a person or in the line of production of a firm, and terminations e.g. the withdrawal of a person from the labor force or the conclusion of a debt through full payment, the completion of the construction of a dwelling unit or the bankruptcy filed by a business firm. These occurrences can become the ‘real-life-objects’ of interest, independently of the persons, things or events in which they occur. These beginnings, changes and endings are of interest independently of the ‘real-life-object’ in which they occur, though always in relation to it, whereby the description of the ‘real-life-object’ in (or on) which an occurrence takes place becomes one of its characteristics. An example would be the opening of a new supermarket, where the ‘real-life-object,’ the beginning of a firm, is characterized by the size and kind of business in which it occurs.

## 统计代写|描述统计学代写Descriptive statistics代考|Substance and Individuality of ‘Real-Life-Objects’

These ‘real-life-objects’ differ widely regarding their physical substance. On one extreme are those that consist predominantly of a physical mass like lumber, coal,

gasoline, cement, fuels and raw materials. These are needed to project socioeconomic phenomena such as importation, exportation, or as the input of certain raw materials in a production process. The problem with them is that they lack natural units that can be counted and measured.

On the other extreme are ‘real-life-objects’ that have only a symbolic substance: a mortgage, the piece of paper that represents that financial contract and is part of the important phenomenon ‘long-term investment.’ Occurrences usually have only a minimal physical substance: a birth certificate or a marriage license. Some occurrences have no physical substance at all such as a business transaction in which merchandise and money is exchanged informally, without a written record – the substance of the traded merchandise must not be confounded with the substance of the transaction itself, which is the ‘real-life-object’ properly speaking from a statistical point of view. Such lack of a physical substance in ‘real-life-objects’ causes the problem of under-reporting because of the difficulty in locating and recording them.

A different, though related matter, is the individuality of these ‘real-life-objects’. It refers to their appearance as something clearly distinct from their environment and from other ‘real-life-objects’. A ‘real-life-object’ may consist of one single piece or unit, such as a car. At times a ‘real-life-object’ may consist of various individual pieces, each of which could become a ‘real-life-object’ in its own right. A ‘Corporation,’ for example is a ‘real-life-object’ of one kind. Its various retail establishments or production plants can become separate ‘real-life-objects’ in which case they represent a different kind of economic phenomenon.

The delimitation of the individuality of an object often suggests itself naturally, such as in a motor vehicle, farm animals, or fruit trees. ${ }^{11}$ This is not the case in a variety of socio-economic ‘real-life-objects’ whose individuality must be defined by the social scientist, such as e.g. a business firm, an I.O.U., a work-accident or a strike. Raw materials, many semi-finished products, and fuels present problems in this regard. Bulk products like cement, cotton, chemicals, lumber, oil, coal, electricity or gas do not have naturally individualized pieces that one might use as ‘real-life-objects.’

Other materials do have individualized pieces, but the exact determination of their number and characteristics is not worth the trouble, such as metal screws, nails, apples, bricks, pencils or cigarettes to give a few examples. In such instances the weight, length, surface or volume of their physical bulk is substituted, such as tons, bushels, board feet, KWH, or certain forms of packaging, such as barrels (oil), sacks (potatoes), crates, bales, or even the ‘production of the day.’ These are not truly individualized objects but pseudo-objects. The number representing the measure of their weight or volume are scale units of measurement, not, as is sometimes mistakenly believed, individual objects. Such units-of-measurement, as stand-ins, are pseudo ‘real-life-objects’ that are treated as homogeneous, in contrast to individualized ‘real-life-objects’ that can be quite heterogeneous and require a correspondingly more sophisticated statistical approach.

## 统计代写|描述统计学代写Descriptive statistics代考|Life Span and Timing of ‘Real-life-Objects’

Every ‘real-life-object’ has a duration or life-span, no matter how short it may be. That life-span has a beginning, various phases of development, and an end. (e.g. see Fig. 7.1) No object really exists as just a point in time, even if for practical purposes it may be treated as such. Beginnings, changes and terminations themselves usually are complex occurrences. The establishment of a new business firm, for instance, may take months. It is a lengthy process which itself has a beginning, duration, and a termination. The onset of the beginning may be considered in even finer detail and further phases might be distinguished about it, such as a beginning e.g. the moment at which this beginning phase actually is initiated, a development of this early stage, and an ending, which is the point in time when this beginning stage is terminated. The possibility of such refinements has a certain importance for the precision with which real-life-objects can be recorded statistically, and to clarify some old problems in statistics like ‘the index-number-problem’. 12

The issue of when exactly a ‘real-life-object’ is captured statistically can be important. It allows to link-up each object with other ‘real-life-objects’ in a ‘historic landscape’. This matter is important because statistical survey procedures tend to isolate ‘real-life-objects’ from their actual surroundings, thereby tending to ignore potentially important information about their socio-economic context. More about this will be discussed in Chap. 5, Longitudinal Analysis-Part 1 – Looking to the Past.

## 有限元方法代写

tatistics-lab作为专业的留学生服务机构，多年来已为美国、英国、加拿大、澳洲等留学热门地的学生提供专业的学术服务，包括但不限于Essay代写，Assignment代写，Dissertation代写，Report代写，小组作业代写，Proposal代写，Paper代写，Presentation代写，计算机作业代写，论文修改和润色，网课代做，exam代考等等。写作范围涵盖高中，本科，研究生等海外留学全阶段，辐射金融，经济学，会计学，审计学，管理学等全球99%专业科目。写作团队既有专业英语母语作者，也有海外名校硕博留学生，每位写作老师都拥有过硬的语言能力，专业的学科背景和学术写作经验。我们承诺100%原创，100%专业，100%准时，100%满意。

## MATLAB代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中，其中问题和解决方案以熟悉的数学符号表示。典型用途包括：数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发，包括图形用户界面构建MATLAB 是一个交互式系统，其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题，尤其是那些具有矩阵和向量公式的问题，而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问，这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展，得到了许多用户的投入。在大学环境中，它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域，MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要，工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数（M 文件）的综合集合，可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。

## 统计代写|描述统计学代写Descriptive statistics代考|From the Facts in Society to Socio-Economic Data

statistics-lab™ 为您的留学生涯保驾护航 在代写描述统计学Descriptive statistics方面已经树立了自己的口碑, 保证靠谱, 高质且原创的统计Statistics代写服务。我们的专家在代写描述统计学Descriptive statistics代写方面经验极为丰富，各种代写描述统计学Descriptive statistics相关的作业也就用不着说。

• Statistical Inference 统计推断
• Statistical Computing 统计计算
• (Generalized) Linear Models 广义线性模型
• Statistical Machine Learning 统计机器学习
• Longitudinal Data Analysis 纵向数据分析
• Foundations of Data Science 数据科学基础

## 统计代写|描述统计学代写Descriptive statistics代考|Socio-Economic Phenomena

The intent of this chapter is to clarify the nature of socio-economic statistical data, and the role statistics is playing in capturing socio-economic phenomena. This role has been seldom discussed but is a fundamental issue concerning the nature of socioeconomic statistical data, ${ }^{1}$ and the manner in which they convey socio-economic reality. The following discourse may strike some readers as unnecessary, perhaps as not even belonging to statistics. Yet, a good understanding of this preliminary phase should provide the user of statistical data with an understanding of the data-creation process as an important first step of interpretation.

To properly interpret data, an understanding of the nature of the elementary building blocks, $^{2}$ the ‘statistical-counting-units’ and their role in portraying economic phenomena, is needed. A comparison suggests itself with the role that atoms and molecules are believed to play in the physical world. The ‘statistical-counting-units’ could be thought of as equivalents of the atoms in physics. The summation of these statistical-counting-units in statistical aggregates could be compared to molecules that are made up of such atoms. These molecules then make up the substance of objects, which then are somehow comparable to phenomena in the social sciences. Despite the appearance of simplicity and mathematical precision of statistical data presenting socio-economic phenomena, like ‘price level,’ ‘unemployment,’ or the GDP, these phenomena and the data portraying them, are more ambivalent and elusive than is commonly realized.

## 统计代写|描述统计学代写Descriptive statistics代考|The Socio-Economic Phenomena

Let me start with the beginning of any statistical investigation: defining the phenomenon to be studied, what it is, where and when it can be found, and how

it should be captured statistically. To repeat the obvious, the phenomena in society are quite different from phenomena in the natural sciences. They also differ in the manner in which ‘real-life-objects’ project the socio-economic phenomena. ${ }^{3}$ The temperature at which water reaches the boiling point, for example, should be expected to be the same in socialist China as in capitalist USA, in a stone age community in Australia’s outback as in a futuristic community in California. Aside from the influence of the barometric pressure – depending on the altitude above sea level – the boiling point of water was probably the same during the time of the French Revolution as during the Punic Wars of ancient Rome. Minor changes may have occurred in reaction to changes in our solar system and in the galaxy to which it belongs. It seems unlikely that a research grant would be available for studying differences in the boiling points of water between cultures, in different continents, or in different historical epochs. Compare this with research in the social sciences where the opposite assumption applies: nothing should be expected to remain the same from one social stratum to another, from one country or culture to another, or even from one month to the next. Social phenomena are known for their rapid change, their unpredictable evolution and their great variety. Statistical data must keep up with this dynamism, and statistical theory ought to be prepared to interpret the phenomena that underlie those data. It should not be a surprise that statisticians have been uncomfortable approaching this topic. They seem to consider a discussion of economic and social phenomena as lying outside the purview of statistics. $.^{4}$ Yet, a foothold in this foreign area must be obtained.

It appears that socio-economic phenomena can be abstracted from actual situations of society on at least three levels.

## 统计代写|描述统计学代写Descriptive statistics代考|The ‘Projecting Agents’ of Socio-Economic Phenomena

In sociology, economics, management, and other business areas, specific socioeconomic phenomena are portrayed or projected by specific items, events, buildings and all kinds of things such as e.g. cars and in general, ‘durable consumer-goods.’ These ‘projecting agents’ can also be contractual documents that seem to exist only as a piece of paper but are anchored in the laws and customs of society. All of these will be referred to in the following as ‘real-life-objects.’

Socio-economic phenomena, at all levels of abstraction, are projected by appropriate ‘real-life-objects’ as the ‘projecting agents’, somewhat like the invisible field of a magnet is projected by iron filings scattered on a sheet of paper placed on top of that magnet. The iron particles become projecting agents of the phenomenon ‘magnetism’ by their reaction to these polarizing forces that exert an effect on these particles. Quetelet’s example of a circle drawn with chalk on a blackboard comes to mind although he intended to illustrate with it the ‘Law of Large Numbers.’ When looking through a magnifying glass, he relates, the individual chalk particles can be seen, spread randomly over the rough surface of the blackboard. When looking at all those particles together, however, the shape of their array in a circle, which in this instance is the phenomenon, becomes evident. ${ }^{8}$

After the appropriate branches of the social sciences have defined a social or economic phenomenon to be investigated, it is the task of statistics to identify, locate and record those ‘real-life-objects’ that portray that phenomenon.

## 有限元方法代写

tatistics-lab作为专业的留学生服务机构，多年来已为美国、英国、加拿大、澳洲等留学热门地的学生提供专业的学术服务，包括但不限于Essay代写，Assignment代写，Dissertation代写，Report代写，小组作业代写，Proposal代写，Paper代写，Presentation代写，计算机作业代写，论文修改和润色，网课代做，exam代考等等。写作范围涵盖高中，本科，研究生等海外留学全阶段，辐射金融，经济学，会计学，审计学，管理学等全球99%专业科目。写作团队既有专业英语母语作者，也有海外名校硕博留学生，每位写作老师都拥有过硬的语言能力，专业的学科背景和学术写作经验。我们承诺100%原创，100%专业，100%准时，100%满意。

## MATLAB代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中，其中问题和解决方案以熟悉的数学符号表示。典型用途包括：数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发，包括图形用户界面构建MATLAB 是一个交互式系统，其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题，尤其是那些具有矩阵和向量公式的问题，而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问，这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展，得到了许多用户的投入。在大学环境中，它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域，MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要，工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数（M 文件）的综合集合，可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。

## 统计代写|描述统计学代写Descriptive statistics代考|Shifts in Emphasis

statistics-lab™ 为您的留学生涯保驾护航 在代写描述统计学Descriptive statistics方面已经树立了自己的口碑, 保证靠谱, 高质且原创的统计Statistics代写服务。我们的专家在代写描述统计学Descriptive statistics代写方面经验极为丰富，各种代写描述统计学Descriptive statistics相关的作业也就用不着说。

• Statistical Inference 统计推断
• Statistical Computing 统计计算
• (Generalized) Linear Models 广义线性模型
• Statistical Machine Learning 统计机器学习
• Longitudinal Data Analysis 纵向数据分析
• Foundations of Data Science 数据科学基础

## 统计代写|描述统计学代写Descriptive statistics代考|Shifts in Emphasis

A shift ought to take place, from the frequency distribution approach with the tempting mathematical treatment of numeric characteristics, that prevails in the data of the natural sciences, to the less tractable qualitative and geographic characteristics, the typical determinants of socio-economic data. These, though not as readily convertible to numbers, are the basic features of the data about economic and social phenomena. Returning to its two original functions of capturing and interpreting reality, statistics must deal with distributions by attributes and geographic regions.
The importance of formulating and testing hypotheses about situations in society for managers, business analysts, politicians and lawmakers must be questioned, despite its great interest for research in the natural sciences. Most of the hypotheses formulated in econometrics cannot be legitimately tested in the same way as e.g. hypotheses in the engineering problems of statistical quality control.

The discussion of price measurement needs to be expanded beyond the customary formalistic treatment. Basic issues need to be discussed such as, ‘What is price?’, ‘What is its nature?’, and ‘What is production?’ Price level changes should be discussed as part of time series, not as a separate oddity. The recent, more inclusive social indicators should become part of the wider discussion of economic indicators. All this should become part of a foundation for descriptive socio-economic statistics. 49

## 统计代写|描述统计学代写Descriptive statistics代考|Filling Voids

The classification systems which underlie the aggregates of socio-economic data are rarely discussed in textbooks on socio-economic statistics. They should also become part of statistical theory. The relation between the socio-economic phenomena and the statistical data aggregates will have to be clarified. In the interpretation of time series and in forecasting, such a comprehensive statistical theory must allow for the combination of the quantitative description of these unique, historic and geographic socio-economic situations with the tools of historiography, sociology, philosophy, management, and economics, not with probability theory except in those instances where it is truly warranted.

National accounting, as part of macroeconomics, also belongs in socio-economic statistics, but is not mentioned in textbooks, even though it is the descriptive framework that integrates all statistical efforts regarding the economy. W. Leontief’s input-output scheme, which captures the dynamics of the economy, also belongs in a course on socio-economic statistics. These two separate areas belong and ought to be discussed in courses and textbooks of statistics. The interpretation and prediction of regional, mostly non-experimental socio-economic data requires the re-thinking of their foundation. Just as economic and social phenomena are the point of departure and the final destination of any statistical enterprise, so also must the theory cover that entire process from beginning to end. This much broader theoretical basis should cover both statistical description and statistical inference, keeping in mind, however, that every statistical effort requires interpretation, but not necessarily inference. Such a broadened theoretical foundation should be capable of sharing its concerns with epistemology, sociology, geography, economic history, the science of management, accounting, social ethics, and of course, with economics. The calculus of probability, though, will be less prominent. Only little of what Leonard J. Savage had to say will be of use as a foundation for the theory of socio-economic statistics. ${ }^{50}$
Electronic computers, with their ever-increasing capacity for storing numbers, text and formulas, free statisticians from burdensome sorting and computing, indeed from the drudgery and tedium of what constituted the bulk of their work. This was reflected in the expression ‘Tabellenknechte’ (slaves of tabulations), coined to describe statisticians’ work before the arrival of computers. These should allow statisticians more time to think about the meaning of their results unless they allow the complexities of computer technology to take the place of the drudgery from which they have been recently liberated.

There is also another danger rooted in the ease with which readily available canned statistical procedures and models can be accessed. The F, t, chi- square, and other statistical tests, often routinely and inappropriately applied, can create the illusion that useful, even scientific analysis has been accomplished. Yet, too often the appropriate conditions for using these tests are not given, and fail to help to understand the socio-economic situation. Computers, however, can be very useful in the meaningful interpretation of socio-economic data by aggregation/dis-aggregation, which is discussed in greater depth in subsequent chapters.

## 统计代写|描述统计学代写Descriptive statistics代考|Toward a De-centralized Understanding of Data

The envisioned foundation of descriptive statistics requires a different attitude toward data about business, the economy and society: neither as the highly accurate measurements of natural science phenomena, in which the historic time and geographic place of the measurement is of minor importance, nor as random variables and random samples. On the contrary, in socio-economic data, their location, place in a historic context, and geographic region are of major interest, in realistically portraying these spatial-historical-institutional socio-economic phenomena (to be discussed in the next Chapter). This requires a very different approach to socio-economic statistical data ${ }^{51}$ than the present understanding that treats them as abstract mathematical quantities. As a consequence of this mis-understanding, essential areas have been excluded that really belong to socio-economic statistics.
The assumption that data are only random deviations from some ‘true value’ is a carry-over from the thinking developed in the natural sciences. For example, the scatter of data in a regression diagram is typically considered a deviation from that center represented by the mathematically-determined regression line. The leastsquares regression or trend line is held to be a valid approximation of the natural laws presumably underlying the behavior of chemical or physical processes. When dis-aggregating a socio-economic data set, however, the data in the sub-aggregates usually have regression lines with different parameters than the data in their aggregate. This indicates that there is no counterpart in society to the laws that govern physical phenomena, a matter that is further discussed in Chap. 9 .

American and other societies experience the pull toward greater economic and political autonomy and decentralization, ${ }^{52}$ while at the same time different forces work in the opposite direction, toward greater concentration. The present reduction in the functions and powers of Federal Agencies in the United States are a testimony to this trend toward decentralization The principle of subsidiarity recognizes the greater importance to citizens of what goes on in their immediate neighborhood and in the local district vis-à-vis matters affecting the country or the world as a whole. In statistical data about society an analogous situation should be expected. Averages and other values of centrality and trend values, representing those central values in society, lose their present preponderance that statistics has adopted from the natural sciences. In short, socio-economic data should be recognized as pieces of statistical evidence in their own right, not as deviations from some central value or trend.

This view of socio-economic data as not having a natural, necessary center from which they randomly deviate, is an important feature to be taken into account when interpreting data. This matter is followed-up in the next chapters. ${ }^{53}$ The thinking about socio-economic data ought to shift away from its present belief that they have a center relying on means, trends and the dispersion around them, toward an understanding of socio-economic data as amorphous structures that can be aggregated or de-aggregated by subject categories, regions and time periods, without having such a center.

## 有限元方法代写

tatistics-lab作为专业的留学生服务机构，多年来已为美国、英国、加拿大、澳洲等留学热门地的学生提供专业的学术服务，包括但不限于Essay代写，Assignment代写，Dissertation代写，Report代写，小组作业代写，Proposal代写，Paper代写，Presentation代写，计算机作业代写，论文修改和润色，网课代做，exam代考等等。写作范围涵盖高中，本科，研究生等海外留学全阶段，辐射金融，经济学，会计学，审计学，管理学等全球99%专业科目。写作团队既有专业英语母语作者，也有海外名校硕博留学生，每位写作老师都拥有过硬的语言能力，专业的学科背景和学术写作经验。我们承诺100%原创，100%专业，100%准时，100%满意。

## MATLAB代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中，其中问题和解决方案以熟悉的数学符号表示。典型用途包括：数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发，包括图形用户界面构建MATLAB 是一个交互式系统，其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题，尤其是那些具有矩阵和向量公式的问题，而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问，这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展，得到了许多用户的投入。在大学环境中，它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域，MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要，工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数（M 文件）的综合集合，可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。

## 统计代写|描述统计学代写Descriptive statistics代考|Misconceptions in Socio-Economic Statistics

statistics-lab™ 为您的留学生涯保驾护航 在代写描述统计学Descriptive statistics方面已经树立了自己的口碑, 保证靠谱, 高质且原创的统计Statistics代写服务。我们的专家在代写描述统计学Descriptive statistics代写方面经验极为丰富，各种代写描述统计学Descriptive statistics相关的作业也就用不着说。

• Statistical Inference 统计推断
• Statistical Computing 统计计算
• (Generalized) Linear Models 广义线性模型
• Statistical Machine Learning 统计机器学习
• Longitudinal Data Analysis 纵向数据分析
• Foundations of Data Science 数据科学基础

## 统计代写|描述统计学代写Descriptive statistics代考|Misconceptions in Socio-Economic Statistics

Statistics is often popularly characterized as measuring and counting. This uncritical transfer of concepts from the natural sciences to the social sciences is misleading. It is important to note that the data* in socio-economic statistics are of a different nature, ${ }^{27}$ to be further discussed in the next chapter. We are not helping matters by referring to the determination of a characteristic as a measurement. Whatever name we assign this process, measuring e.g. the weight of a piece of zinc oxide on an electronic scale, clearly is a different proposition than e.g. determining, through financial accounting, the net value of a business firm for a given time period. Both are referred to as measurements. Yet, the data in the social sciences are not the result of direct observations done by an objective, specially trained outside observer, like for example in microbiology. Most socio-economic statistical data are, in contrast, self-observed, intended to inform about facts that are on a questionnaire or verbally reported to a survey taker, who usually does not do the observation of facts him/herself. These observations properly speaking, are usually carried out by those who are to be observed, as self reporting. ${ }^{28}$ Very few statistical observations relating to economic facts or other aspects of society are made directly by an objective outside observer, like in the daily work of scientists. Instead, the accuracy and veracity of the information depends on the level of education, good will, disposition to cooperate, and the honesty and unfailing memory of the interviewed. This provides an

important difference with the data in the natural sciences. As the subsequent discussion will show, socio-economic data are aggregates that transmit the economic and social reality differently than is generally assumed. One must realize that economic facts, such as e.g. the employment and labor force participation status of persons is not determined or measured with a precision gauge or with an electronic scale.
Nor is counting what it appears to be. The economic entities, e.g. business firms, report their characteristics via questionnaires. It is these questionnaires, not the persons, business firms, etc. that are the things to be counted, as will be discussed in Chap. 2. These questionnaires will be aggregated and provide a stripped down, abstract picture of socio-economic reality, as discussed in Chap. 3. Statistics’ role is that of a reduction lens which condenses phenomena that are too far dispersed to be perceptible. ${ }^{29}$ These economic and social phenomena are too widely scattered, geographically, subject-mater-wise and over time, to be perceptible without the help of statistics. It acts as a macroscope, ${ }^{30}$ an instrument that allows for the perception of things that are too big or too widely scattered to be seen, the opposite of a microscope, which amplifies phenomena that are too small for the unaided eye. The individual cases themselves, represented by questionnaires, are of little interest. It is their distribution over regions, time and subject-matter categories that is the key to interpreting socio-economic phenomena.

## 统计代写|描述统计学代写Descriptive statistics代考|Symptomatic Omissions

The gaps and omissions found in the textbooks of business and economic statistics reveal the areas that are similarly missing from the theory of socio-economic statistics.

Statistical aggregates are neither discussed nor recognized in their actual geographical historical-institutional context. Population and other economic censuses are hardly ever mentioned in textbooks. Statistical theory rarely contributes to the understanding of categorical or qualitative characteristics. ${ }^{37}$ Yet, these categorical variables that cannot be determined with precision, prevail in socio-economic data, and are more important than the quantitative characteristics in describing socioeconomic reality. Because of its orientation toward measurable, quantitative characteristics of the natural science data, the theory in textbooks of business and economic statistics fails to discuss the important classifications of economic activities SIC and NAICS, of occupations, and of products. Similarly ignored are the important geographic or spatial distributions. Separate specialized treatments of these topics do exist ${ }^{38}$ but are not part of the theoretical foundation of statistics as applied to the social sciences. Nor is there a place for considerations of an international kind at a time when globalization requires the attention of leaders in business, politics and the economy. ${ }^{39}$

Most frequency distributions in socio-economic statistics are decidedly asymmetric. Yet, the orientation toward data in the natural sciences, where symmetrical distributions prevail, has not recognized this. As previously stated, the phenomena in the social sciences differ from those in the natural sciences and these typically highly asymmetric frequency distributions require special treatment with classes of unequal widths, a matter that is rarely mentioned, and whose interpretation, though important, is not on their agenda.

Related is the fact that the statistical perception of reality – disparagingly referred to as only descriptive statistics – is least valued. Publishers of textbooks have advertised, as an improvement in a new edition, that the space allotted to descriptive statistics has been further reduced, in favor of more statistical inference. That misses the point, however, that the original purposes for which business economic and social statistics are produced, is to scan society and its changes, and to report its findings. Statistical methods, most of them transferred from statistics in biology and other natural sciences, hardly take note of economic and social factors and do not present methods to study phenomena such as the extent and intensity of unemployment in different parts of the country, by age, gender, race, occupation, industrial activity, etc. By failing to acknowledge the subject matter-time-space dimensions of social phenomena, statistical theory has turned its back on socio-economic reality, limiting its concerns to concepts of random sample selection, random variable, inference from samples, least squares. and related sample-theoretical considerations. ${ }^{40}$ It is in vogue to construct and study models of reality, rather than to study that reality itself. It is questionable that much can be learned about a situation ${ }^{41}$ through simulation exercises $^{42}$ and testing of hypothetical models.

## 统计代写|描述统计学代写Descriptive statistics代考|Beyond Sampling and Inference

What should a future theory of business, economic and social statistics contain? Although sampling techniques and the inference from samples are important, socioeconomic statistics literally has been trapped for decades in it as its near-exclusive theory. The situation has not changed with the emergence of non-parametric methods of inference and multivariate analyses. Despite their limited scope, sampling,

inference and decisions based on it are treated as if they were The Theory of Statistics. It was precisely these limited concerns that have kept statistical theorists from returning to the interpretation of the situations described by socio-economic data, which really is the ultimate purpose of statistics. Historically there were similar episodes of the exclusive and limited concern with certain topics. At the turn of the $20^{\text {th }}$ century, for example, discussion centered on the measures of location, dispersion, and index numbers. Neither one of these developments contributed significantly to interpreting socio-economic data

The time has come to break out of the confinement of many decades of exclusive concern with sampling and inference ${ }^{47}$ and to re-orient statistics to interpret the phenomena of society through all kinds of data, not only those from samples. The entire process, from the early draft of the concept of what exactly is to be investigated, to the final presentation and the appropriate storage of results, must be part of a theoretical framework of data interpretation. 48

As statistical aggregates are the instruments through which reality is perceived, these aggregates, the data, ought to be the starting point of all statistical theorizing. Aggregation must be recognized as centrally important. Instead, statisticians have turned to probability to look for answers and by doing so, have further put off the real task of interpreting the situations in society as they are reflected in the data.

## 有限元方法代写

tatistics-lab作为专业的留学生服务机构，多年来已为美国、英国、加拿大、澳洲等留学热门地的学生提供专业的学术服务，包括但不限于Essay代写，Assignment代写，Dissertation代写，Report代写，小组作业代写，Proposal代写，Paper代写，Presentation代写，计算机作业代写，论文修改和润色，网课代做，exam代考等等。写作范围涵盖高中，本科，研究生等海外留学全阶段，辐射金融，经济学，会计学，审计学，管理学等全球99%专业科目。写作团队既有专业英语母语作者，也有海外名校硕博留学生，每位写作老师都拥有过硬的语言能力，专业的学科背景和学术写作经验。我们承诺100%原创，100%专业，100%准时，100%满意。

## MATLAB代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中，其中问题和解决方案以熟悉的数学符号表示。典型用途包括：数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发，包括图形用户界面构建MATLAB 是一个交互式系统，其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题，尤其是那些具有矩阵和向量公式的问题，而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问，这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展，得到了许多用户的投入。在大学环境中，它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域，MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要，工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数（M 文件）的综合集合，可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。

## 统计代写|描述统计学代写Descriptive statistics代考|Developments in Socio-Economic Statistics

statistics-lab™ 为您的留学生涯保驾护航 在代写描述统计学Descriptive statistics方面已经树立了自己的口碑, 保证靠谱, 高质且原创的统计Statistics代写服务。我们的专家在代写描述统计学Descriptive statistics代写方面经验极为丰富，各种代写描述统计学Descriptive statistics相关的作业也就用不着说。

• Statistical Inference 统计推断
• Statistical Computing 统计计算
• (Generalized) Linear Models 广义线性模型
• Statistical Machine Learning 统计机器学习
• Longitudinal Data Analysis 纵向数据分析
• Foundations of Data Science 数据科学基础

## 统计代写|描述统计学代写Descriptive statistics代考|Stating the Problem

Statisticians accept as a self evident principle that there is one general theory of statistics that applies equally to all fields, ${ }^{1}$ biology, economics, engineering, demography, environmental sciences, sociology, etc. (Fig. 1.1).

Yet, important applications in economics and the social sciences in general are not covered by what today is considered ‘the theory of statistics.’

This calls for a review of the situation, of methods that do not apply, and important aspects of socio-economic applications that are not supported by statistical theory. The peculiar nature of the data in socio-economic statistics requires a different basis than is available at present ${ }^{2}$ and makes it unlikely that a general ‘Theory of Statistics’ can satisfy the needs of this scientific field. Historically, the turn toward inference came from the discovery of random sampling, from experimentation in agriculture and other applications in the natural sciences. We proceed as if socioeconomic statistical data are like those in the sciences, ignoring that they differ in important ways. Because of this, the applications of social, business and economic statistics are not adequately supported by today’s statistical theory (Fig. 1.2).

## 统计代写|描述统计学代写Descriptive statistics代考|The Anglo-American Influence

The influence of the Anglo-Saxon bio-mathematicians came to dominate the development of statistical theory. The ideas of $\mathrm{K}$. and E. Pearson, R. Fisher, F. Yates, Wm. S. Gossett, M.M. Bartlett, J. Neyman, and other biometricians from the British school of thought found a fertile ground in the USA, partly due to the accessibility of their publications through the common language, and partly due to their common interest in the bio-sciences and engineering. The resulting development could be called the Anglo-American theory of statistics having entered business and economic statistics as ‘decision-making under uncertainty’ of value for business corporations and government. The Anglo-American statistical theory moved probability into a prominent position about which more is to be said in Chap. 10. Yet, the bulk of actual statistical work in the social sciences is directed primarily at the realistic perception of socio-economic phenomena such as price level movements,

demographic developments, industrial production, foreign trade or labor problems. The subsequent evaluation and interpretation of the data is the important aim of all statistical efforts. The present theory of Anglo-American statistics, however, is not directed at the interpretation of the economic and social situations described by these data, yet insisting that the available theory is appropriate and sufficient.

Authors of textbooks on business and economic statistics acknowledge their debt to the mathematicians and biologists R. Fisher, K. Pearson and ‘Student’, but do not acknowledge a greater debt to W. Leontief, R. Stone, S. Kuznets, J. Tinbergen, E. Laspeyres and others for their contributions to socio-economic statistics proper. The roots of this obvious mis-orientation go back to Adolphe Quetelet’s physique sociale, his idea of physical laws governing society like the laws in the physical sciences that were recent discoveries of his time. This idea, typical of his ‘Zeitgeist’ had a long-lasting influence. Quetelet popularized the idea that society could be treated as if it were a branch of the natural sciences. This idea was also accepted and developed by mathematical economists like Walras and Marshall, later leading into econometrics. All this consolidated the influence of these positivist ideas, ${ }^{3}$ particularly by econometricians like R. Frisch and T. Haavelmo. ${ }^{4}$

The other, related source of this mis-direction is the mistaken assumption, that socio-economic statistical data are point-like and objective like individual measurements in the natural sciences. The present theory, based on this, ignores the subjective and aggregative nature of our data.

## 统计代写|描述统计学代写Descriptive statistics代考|Socio-Economic Statistics and Decision Theory

In the late sixties, many universities in the USA began consolidating the courses on Business and Economic Statistics with courses on Decision Theories and Decision Making. The administrative convenience was evident. The real reason, however, was the obvious affinity between these two groups of courses: both were presented as based on a stochastic view of society and probability theory. Statistics was presented as an extension of making decisions under uncertainty. Such consolidation seemed only a question of time. Nevertheless, some serious objections had to be raised against it.

First, the conditions under which probability calculus, particularly the frequentist kind of probability that prevailed in courses of statistics, can predict the results of games of chance differ from those of actual business decisions. Their risk is of a different nature than that evident in games of chance. In the latter the rules of the game are fixed and known to the players in advance (the decision makers). All possible outcomes are known beforehand. Once the game begins, the rules cannot be changed. The outcomes can be predicted only for the long run, that is, when such a game is continued for many rounds. There are indeed few economic decisions of this invariant and repetitive nature ${ }^{17}$ in which the probability rules of games of chance can be applied meaningfully. ${ }^{18}$ Most business or economic decisions are made either as a compromise between the divergent views of the situation by the voting members of an executive committee, or by a corporate executive officer, without the tensions and benefits of a multidimensional perception of the situation. Economic decisions are judged by their success in the marketplace, and are based on a multiplicity of short and long range considerations, the most important of which often cannot even be quantified. Rarely can such decisions be made according to the rules of games of chance. 19 The study of such decisions is of great interest but

really belong in courses of management, finance or marketing, rather than in one of socio-economic statistics.

Second, it is important to understand how statistical input is brought to bear on business decisions. It provides the economic panorama for the decision, together with other non-statistical information. Typical were the weekly sessions of the directorate of the Du Pont de Namour corporation at which the updated, pertinent economic data series were presented and discussed. ${ }^{20}$ No immediate, concrete decisions followed from the knowledge of these data. Its high-level participants kept this statistical panorama, as it were, in the back of their minds, for the appropriate moment when a decision would be made. This is akin to a situation after a college examination when the instructor publishes the distribution of grades, and each student can assess his position among his peers. Those who ought to make changes in their study habits ${ }^{21}$ will not necessarily act ${ }^{22}$ based on such available information. ${ }^{23}$ If, however, they do decide to act, ${ }^{24}$ then they will use the given information as a guide ${ }^{25}$ in that decision-making process, but will not allow themselves to be forced to act in a specific way, like a cogwheel in a mechanical gear box. ${ }^{26}$ Nobody can object to a course in decision-making, but it should not take the place of business, economic and social statistics properly speaking.

## 有限元方法代写

tatistics-lab作为专业的留学生服务机构，多年来已为美国、英国、加拿大、澳洲等留学热门地的学生提供专业的学术服务，包括但不限于Essay代写，Assignment代写，Dissertation代写，Report代写，小组作业代写，Proposal代写，Paper代写，Presentation代写，计算机作业代写，论文修改和润色，网课代做，exam代考等等。写作范围涵盖高中，本科，研究生等海外留学全阶段，辐射金融，经济学，会计学，审计学，管理学等全球99%专业科目。写作团队既有专业英语母语作者，也有海外名校硕博留学生，每位写作老师都拥有过硬的语言能力，专业的学科背景和学术写作经验。我们承诺100%原创，100%专业，100%准时，100%满意。

## MATLAB代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中，其中问题和解决方案以熟悉的数学符号表示。典型用途包括：数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发，包括图形用户界面构建MATLAB 是一个交互式系统，其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题，尤其是那些具有矩阵和向量公式的问题，而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问，这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展，得到了许多用户的投入。在大学环境中，它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域，MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要，工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数（M 文件）的综合集合，可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。