## 统计代写|数据可视化代写Data visualization代考|EDS240

2022年9月24日

couryes-lab™ 为您的留学生涯保驾护航 在代写数据可视化Data visualization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。我们的专家在代写数据可视化Data visualization代写方面经验极为丰富，各种代写数据可视化Data visualization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
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## 统计代写|数据可视化代写Data visualization代考|The Graphic Vision of Charles Joseph Minard

The dominant principle which characterizes my graphic tables and my figurative maps is to make immediately appreciable to the eye, as much as possible, the proportions of numeric results… Not only do my maps speak, but even more, they count, they calculate by the eye.
-MINARD (1862b)
Charles Joseph Minard [1781-1870] is most widely known for his compelling portrayal of the terrible losses suffered by Napoleon’s Grand Army in the 1812 campaign on Moscow. Edward Tufte (1983) called it “the best statistical graphic ever produced” (p. 10). However, Minard’s wider work serves to illustrate the rise of visual thinking and visual explanation that began in the early nineteenth century and came to fruition in the Golden Age.

Minard was trained as an engineer at the École Nationale des Ponts et Chaussées (ENPC), the prestigious French National School of Bridges and Roads. He had two distinct careers there: he first served (1810-1842) as a civil engineer, designing plans for construction of canals and railways, and afterward (1813-1869) he worked as what can be called a visual engineer for the modern French state.

Figure $7.4$ shows an example of visual thinking and visual explanation from his early career. In 1840, Minard was sent to Bourg-Saint-Andèol to report on the collapse of a suspension bridge across the Rhône, constructed only ten years before and therefore a major embarrassment for the LNPC. Minard’s findings consisted essentially of this self-explaining before-and-after diagram. The visual message was immediate and transparent: apparently, the riverbed beneath the supports on the upstream side had eroded, leaving the bridge unsupported over a good portion of its width. His 1856 pamphlet contains other similar engineering visual explanations.

Minard produced sixty-three known graphic works in the 1843-1869 period. ${ }^8$ These included tableaux graphiques (charts and statistical diagrams) and cartes figuratives (thematic maps). Before his retirement in 1851 his “bread-and-butter” topics concerned matters of trade, commerce, and transportation: Where to build railroads and canals? How to charge for transport of goods and passengers? How to visualize changes over time and differences over space? Most of his thematic maps were flow maps, which he developed to a near art form. His choice of the term carte figurative signals that the primary goal was to represent the data; the map was often secondary.

## 统计代写|数据可视化代写Data visualization代考|Francis Galton’s Greatest Graphical Discovery

In Chapter 6, we learned of Galton’s justly famous 1886 discovery of the idea of regression and the concentric ellipses that characterize the bivariate correlation. However, Galton had achieved an even more notable graphic discovery twenty-five years earlier, in 1863-uncovering the relation between barometric pressure and wind direction that now forms the basis of modern understanding of weather. Most notably, this is a shining example of a scientific discovery achieved almost entirely through graphical means, “something that was totally unexpected, and purely the product of his high-dimensional graphs.” 11

Galton, a true polymath, developed an interest in meteorology around 1858 , after he was appointed a director of the observatory at Kew. This work suggested many scientific questions related to geodesy, astronomy, and meteorology; but in his mind, any answers depended first on systematic and reliable data, and second on the ability to find coherent patterns in the data that could contribute to a general understanding of the forces at play.

In 1861 Galton began a crowd-sourced campaign to gather meteorological data from weather stations, lighthouses, and observatories across Europe, enlisting the aid of over 300 observers. His instructions included a data collection form (Tigure 7.7) to be filled out at $9 \mathrm{AM}, 3 \mathrm{PM}$, and $9 \mathrm{PM}$, for the entire month of December 1861, recording barometric pressure, temperature, wind direction and speed, and so forth. From the returns, he began a process of graphical abstraction, which was eventually published in 1863 as Meterographica. Altogether, he made over 600 maps and diagrams, using lithography and photography in the process. In his program Galton had a collection of standardized data across all of Europe to make the recordings of these seven variables comparable; a keen appreciation of the power of graphical methods to reveal systematic patterns; and an ability to invent or adapt visual symbols for his purpose.

In the first stage, Galton constructed ninety-three maps (three per day, for each of thirty-one days) on which he recorded multivariate glyphs using stamps or templates he had devised to show rain, cloud cover, and the direction and force of the wind, as shown in Plate $11 .{ }^{12}$ He explained that these visual symbols were just as precise as the letters N, NNW, NW, and so on to express wind direction, but the icons “have the advantage of telling their tale directly to the eye” (p. 4).

# 数据可视化代考

## 统计代写|数据可视化代写数据可视化代考|弗朗西斯高尔顿的最伟大的图形发现

. .

1861年高尔顿开始了一项群众活动，从欧洲各地的气象站、灯塔和天文台收集气象数据，征集了300多名观测员的帮助。他的指示包括一张1861年12月的数据收集表(Tigure 7.7)，要在$9 \mathrm{AM}, 3 \mathrm{PM}$和$9 \mathrm{PM}$上填写，记录气压、温度、风向和风速等数据。从这些报单开始，他开始了一个图形抽象的过程，最终在1863年出版了《Meterographica》。他在制作过程中使用光刻和摄影技术，总共制作了600多幅地图和图表。高尔顿在他的程序中收集了全欧洲的标准化数据，以便对这七个变量的记录进行比较;对图形方法揭示系统模式的能力有敏锐的鉴赏力;以及为自己的目的而发明或改编视觉符号的能力

## 有限元方法代写

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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。