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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|Political Arithmetic

The first real inkling and widespread realization that data could be put to some larger and more general use occurred in 1662 when John Graunt [1620-1674], a London haberdasher by trade, published Natural and Political Observations Made upon the Bills of Mortality. Here, he laid out the first statistical estimates of the population of London, based on official birth and death records, and presented life tables giving survival numbers to each age. Together with his friend William Petty, he developed the idea that population numbers (later called demography) could be useful for a variety of purposes of the state, including taxation and how to raise an army, as well as for economic purposes, such as how to value annuities on a life or price insurance policies. The Bills of Mortality also gave rough categories of cause of death, so Graunt could show that deaths from chronic conditions outnumbered those from plague and other epidemics that caused great fear at this time.

We consider this event the birth of “data” as empirical evidence in our modern sense: numerical facts began to be viewed not as individual elements (that could be looked up, compared, and even calculated with) but rather as constituent members of an ensemble, an aggregate collection of similar numbers organized to support or refute claims for some larger purposes. This event was also the beginning of the study of “social numbers,” the numerical characteristics of individuals in human society regarded in the aggregate.

But it was William Petty [1623-1687] who fully appreciated the use to which such data could be put. From humble beginnings in a family of London clothiers, Petty become a professor of anatomy at Oxford University in 1650 , and a chief physician to Oliver Cromwell’s army in Ireland in 1652 , before being appointed a founding member of the Royal Society in 1660 and knighted a year later by Charles II.

## 统计代写|数据可视化代写Data visualization代考|The Human Sex Ratio

The Bills of Mortality led to some something larger and more general in the history of numbers as evidence for a proposition. Graunt’s data were based on parish records of christenings and deaths, recorded nearly weekly and with at least a modicum of uniformity. In 1710, John Arbuthnot [1667-1735], a Scottish minister and physician to Queen Anne, calculated the ratio of male to female births from these records for the period $1629-1710$. He was amazed to observe that the ratio was always greater than 1 (see Figure 3.2), even if only slightly. If male and female births were equally likely, this result would be like tossing 82 coins and obtaining all heads, which has a probability of $\left(\frac{1}{2}\right)^{82}=2 \times 10^{-25}$, a very small number.

Arbuthnot used this apparently lawful regularity to argue that Divine Providence, not chance, governs the human sex ratio. ${ }^{1}$ His argument was perhaps the first application of probability to social statistics; this can be considered the first formal significance test of a statistical hypothesis.

His conclusion was wrong because the larger number of males can now be at least partially attributed to higher female fetal mortality before birth, not to mention factors that might intervene between birth and christening. ${ }^{2}$ Yet, a set of numbers had finally been converted to evidence for an argument, and Arbuthnot provided an initial idea for how to measure the strength of evidence.

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

1662 年，伦敦商人约翰·格朗特 (John Graunt) [1620-1674] 发表了《根据死亡法案进行的自然和政治观察》，第一次真正意识到和广泛认识到数据可以用于更大和更普遍的用途。在这里，他根据官方出生和死亡记录列出了伦敦人口的第一个统计估计值，并展示了生命表，给出了每个年龄的生存数字。他与他的朋友威廉·佩蒂（William Petty）一起提出了这样一种观点，即人口数量（后来称为人口统计）可以用于国家的各种目的，包括税收和如何组建军队，以及用于经济目的，例如如何评估人寿或价格保险单上的年金。死亡法案还给出了大致的死因类别，

## 有限元方法代写

assignmentutor™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。

assignmentutor™您的专属作业导师
assignmentutor™您的专属作业导师