### 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).

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## 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。