### 统计代写|数据可视化作业代写data visualization代考|Cross-Sectional and Time Series Data

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|数据可视化作业代写data visualization代考|Cross-Sectional and Time Series Data

We distinguish between cross-sectional data and times series data. Cross-sectional data are collected from several entities at the same or approximately the same point in time. The data in Table $1.3$ are cross-sectional because they describe the 30 companies that comprise the Dow at the same point in time (April 2020).
Time series data are data collected over several points in time (minutes, hours, days, months, years, etc.). Graphs of time series data are frequently found in business. economic, and science publications. Such graphs help analysts understand what happened in the past, identify trends over time, and project future levels for the time series.For example, the graph of the time series in Figure $1.4$ shows the DJI value from January 2010 to April 2020 . The graph shows the upward trend of the DJI value from 2010 to 2020 , when there was a steep decline in value due to the economic impact of the COVID-19 pandemic.

## 统计代写|数据可视化作业代写data visualization代考|Big Data

There is no universally accepted definition of big data. However, probably the most general definition of big data is any set of data that is too large or too complex to be handled by standard data-processing techniques using a typical desktop computer. People refer to the four Vs of big data:

• volume-the amount of data generated
• velocity – the speed at which the data are generated
• variety-the diversity in types and structures of data generated
• veracity-the reliability of the data generated
Volume and velocity can pose a challenge for processing analytics, including data visualization. Special data management software such as Hadoop and higher capacity hardware (increased server or cloud computing) may be required. The variety of the data is handled by converting video, voice, and text data to numerical data, to which we can then apply standard data visualization techniques.
In summary, the type of data you have will influence the type of graph you should use to convey your message. The zoo attendance data in Figure $1.1$ are time series data. We used a column chart in Figure $1.1$ because the numbers are the total attendance for each month, and we wanted to compare the attendance by month. The height of the columns allows us to easily compare attendance by month. Contrast Figure 1.1 with Figure 1.4, which is also time series data. Here we have the value of the Dow Jones Index. These data are a snapshot of the current value of the DJI on the first trading day of each month. They provide what is essentially a time path of the value, and so we use a line graph to emphasize the continuity of time.

## 统计代写|数据可视化作业代写data visualization代考|Data Visualization in Practice

Data visualization is used to explore and explain data and to guide decision making in all areas of business and science. Even the most analytically advanced companies such as Google, Uber, and Amazon rely heavily on data visualization. Consumer goods giant Procter \& Gamble (P\&G), the maker of household brands such as Tide, Pampers, Crest, and Swiffer, has invested heavily in analytics, including data visualization. $\mathrm{P} \& \mathrm{G}$ has built what it calls the Business Sphere ${ }^{\mathrm{M}}$ in more than 50 of its sites around the world. The Business Sphere is a conference room with technology for displaying data visualizations on its walls. The Business Sphere displays data and information P\&G executives and managers can use to make better-informed decisions. Let us briefly discuss some ways in which the functional areas of business, engineering, science, and sports use data visualization.

## 统计代写|数据可视化作业代写data visualization代考|Big Data

• volume——产生的数据量
• 速度——生成数据的速度
• 多样性——生成的数据类型和结构的多样性
• 准确性——生成的数据的可靠性
总之，您拥有的数据类型将影响您应该用来传达信息的图表类型。动物园出勤数据如图1.1是时间序列数据。我们在图中使用了柱形图1.1因为这些数字是每个月的总出勤率，我们想按月比较出勤率。列的高度使我们可以轻松地按月比较出勤率。对比图 1.1 和图 1.4，图 1.4 也是时间序列数据。这里我们有道琼斯指数的价值。这些数据是每个月第一个交易日 DJI 当前价值的快照。它们提供了本质上是价值的时间路径，因此我们使用折线图来强调时间的连续性。

## 广义线性模型代考

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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。