### 统计代写|数据可视化代写Data visualization代考|BISM3204

statistics-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

## 统计代写|数据可视化代写Data visualization代考|Connecting Data with Pictures

As we’ve seen, initial visualizations were of something concrete and specific in the world: a majestic auroch bull in motion, diagrams of wrestling moves, and maps of just a city or of the entire known world. But another branch of visualization was developing too, which depicted an abstract and theoretical world. A century before Descartes formalized his eponymous coordinates, Nicole Oresme in Padua illustrated some of the possible laws of motion in the book Tractus de latitudunus forarum, the “latitude of forms” (see Figure 2.2). Galileo and Newton would later make the study of motion precise, but Oresme had the idea to consider some alternatives and show them in a graph.

What was still lacking was a connection between empirical observationsnumbers-and pictures to convey them to the eye. Natural philosophy-how we learn about the world-had long had two distinct views, rationalism and empiricism, which date back at least to Plato and Aristotle. The philosophical debate has many branches, but the essential contrast was of the role of sensory experience: using observations and data in deriving knowledge, making decisions, and formulating natural laws.

Rationalists claimed that there were some innate or intuitive ideas (a point or line, the idea of language); larger ideas (a triangle or square, words for things versus words for actions) could be deduced by human intellect. For Descartes, one of the founders of seventeenth-century rationalism, the argument was captured in his famous proclamation, “I think, therefore I am.” Analytic geometry was the result of mathematical reasoning applied to geometry, but Descartes also applied this approach to the mind-body problem (determining what distinguishes the corporal self, composed of matter, from the ethereal mind and soul). The laws of the universe are fixed, and they can be discovered by reason. Observations and data were useful, but they only play a supporting role.

Empiricists claimed that knowledge and natural law had to be based fundamentally on empirical evidence, not authority or abstract reasoning. The idea of a scientific method based on observation stems from Roger Bacon [1214-1292], who observed that “reasoning draws a conclusion, but does not make the conclusion certain, unless the mind discovers it by the path of experience” (Bacon, Opus Majus c. 1267; translation from Robert Burke (2002) The Opus Majus of Roger Bacon Part 2. p. 583 ).

## 统计代写|数据可视化代写Data visualization代考|Seeing the Unexpected

Graphs that were in existence before 1800 , the time of William Playfair (see Chapter 5), largely grew out of the same rationalist tradition that yielded Descartes’s coordinate geometry-the plotting of curves on the basis of an a priori mathematical expression (e.g., Oresme’s “pipes,” shown in Figure 2.2).
The plotting of real data had a remarkable, and largely unanticipated, benefit. It often forced viewers to see what they hadn’t expected. The frequency with which this happened gave birth to the empirical modern approach to science which welcomes the plotting of observed data values with the goal of investigating suggestive patterns.

This was particularly true of Playfair’s graphs, most of which showed mundane economic data over time: balance of trade with other countries, the national debt, and so forth. But these had never been seen before in a way that could suggest patterns, trends, and explanations. In this period, the idea of a graph of numbers, supporting an argument based on evidence, was born.
This crucial change in view of the value of graphs in relation to evidence and explanations has a more nuanced history than we can tell here. However, the revolution seems to have begun in 1665 with the invention of the barometer and graphic recording devices, which used pens driven on paper by a measuring instrument. ${ }^{9}$ Readings from this instrument inspired the eponymous Robert Plot to record the barometric pressure in Oxford every day of 1684 and summarize his findings in a strikingly contemporary graph that he called a “History of the Weather” (Figure 1.4).

This graph is not a beautiful example of a data plot. It looks more like a recording of an old polygraph or cardiac ECG monitor-a bunch of squiggly lines on a dark gray background, with ruled lines that further obscure the data. But the visual insight he had from this, and what he could see as an eventual wider use of plots of the weather, was important. His idea of recording a history of weather made the phenomenon of barometric pressure subject to visual inspection and scientific thought.

## 统计代写|数据可视化代写Data visualization代考|Seeing the Unexpected

1800 年之前存在的图，即威廉·普莱费尔（William Playfair）时代（见第 5 章），很大程度上源于产生笛卡尔坐标几何的理性主义传统——基于先验数学表达式（例如，Oresme 的“管道”，如图 2.2 所示）。

Playfair 的图表尤其如此，其中大部分显示了随时间推移的普通经济数据：与其他国家的贸易平衡、国家债务等等。但这些以前从未以可以暗示模式、趋势和解释的方式出现。在这一时期，数字图表的想法诞生了，它支持基于证据的论点。

## 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。