### 统计代写|数据可视化作业代写data visualization代考|Defining the Goal of Your Data Visualization

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|Selecting an Appropriate Chart

How do you choose an appropriate chart? If the goal of your chart is to explain, then the answer to this question depends on the message you wish to convey to your audience. If you are exploring data, the best chart type depends on the question you are asking and hope

to answer from the data. Also, the type of data you have may influence your chart selection. A few of the more common goals for charts are to show the following:

• Composition-Composition is what makes up the whole of an entity under consideration. An example is the bar chart in Figure 2.2.
• Ranking-Ranking is the relative order of items. Figure $2.2$ is also an example of ranking, because we have sorted the categories by bar length, which is proportional to the amounts allocated.
• Correlation/Relationship-Correlation is how two variables are related to one another. An example of this is the relationship between average low temperature and average annual snowfall for various cities in the United States.
• Distribution-Distribution is how items are dispersed. An example of this is the number of calls received by a call center in a day, measured on an hourly basis.
The type of data you have should also influence your chart selection. For example, a bar or column chart is often an appropriate chart when we are summarizing data about categories. Students’ letter grades in a college course are categories. For summarizing the number of students earning each letter grade, a bar or column chart would be appropriate.
The relationship between two quantitative variables often makes a scatter chart an appropriate choice. Bar charts, scatter charts, and line charts with the horizontal axis being time, are often the best choice for time series data. If your data have a spatial component, a geographic map might be a good choice.

Creating great data visualizations is a skill that is best learned by doing. Therefore, before getting into more detail on the various types of charts and in what circumstances they are most appropriate, we provide detailed instructions on how to create and edit charts in Excel.

## 统计代写|数据可视化作业代写data visualization代考|Scatter Charts and Bubble Charts

When exploring data, we are often interested in the relationship between two quantitative variables. For example, we might be interested in the square footage of a house and the cost of the house, or the age of a car and its annual maintenance cost. A scatter chart is a graphical presentation of the relationship between two quantitative variables. One variable is shown on the horizontal axis and the other is shown on the vertical axis, and a symbol is used to plot ordered pairs of the quantitative variable values. A scatter chart is appropriate for better understanding the relationship between two quantitative variables. As we shall also see, a bubble chart is an appropriate chart when trying to show relationships with more than two quantitative variables.

The file Snow contains the average low temperature in degrees Fahrenheit and the average annual snowfall in inches for 51 major cities in the United States. A portion of the data are shown in Figure 2.6. These averages are based on thirty years of data. Suppose we are interested in the relationship between these two variables. Intuition tells us that the higher the average low temperature the lower the average snowfall, but what is the nature of this relationship?

The data are plotted in Figure 2.7. This scatter chart is created using the following steps.
Step 1. Select cells Cl:D52
Stẹp 2. Click the Insert tabb oñ the Ribbon
Step 3. Click the Insert Scatter (X,Y) or Bubble Chart button $\because \times$ in the Charts group
When the list chart subtypes appears, click the Scatter button $\angle \%$ Then edit the chart as outlined in Section 2-2.
Each point on the chart in Figure $2.7$ represents a pair of numbers. In this case, we have a pair of measurements for each of 51 cities. The measurements are average low temperature in degrees Fahrenheit and average annual amount of snowfall in inches. We can see from the chart that average annual amount of snowfall intuitively levels off at zero for warmweather cities.

Scatter charts are among the most useful charts for exploring pairs of quantitative data. But, what if you wish to explore the relationships between more than two quantitative variables? When exploring the relationships between three quantitative variables, a bubble chart may be useful.

## 统计代写|数据可视化作业代写data visualization代考|Bubble Charts

A bubble chart is a scatter chart that displays a third quantitative variable using different sized dots, which we refer to as bubbles.

The file AirportData contains data on a sample of 15 airports. These data are shown in Figure 2.8. For each airport, we have the following quantitative variables: average wait time in the non-priority Transportation Security Authority (TSA) queue measured in minutes, the cheapest on-site daily rate for parking at the airport measured in dollars, and the number of enplanements in a year (the number of passengers who board including transfers) measured in millions of passengers.

Step 3. Click the Insert Scatter (X,Y) or Bubble Chart button When the list of chart subtypes appears, click the Bubble button 88 Then edit the chart as outlined in Section 2-2.
We plot the TSA wait time along the horizontal axis and the parking rate along the vertical axis, and vary the size of each bubble to represent the number of enplanements. We see that airports with fewer passengers tend to have lower wait times than those with more passengers. There seems to be less of a relationship between parking rate and number of passengers. Airports with lower wait times do tend to have lower parking rates.

In a bubble chart, you might wish to change which variables correspond to the $x$ (horizontal) values, the $y$ (vertical) values, and the bubble sizes. Once the chart has been created in Excel, the following steps can be used to change these assignments.
Step 1. Right-click any bubble and choose Select Data…
Step 2. When the Select Data Source dialog box appears, click the Edit button under Legend Entries (Series)
Step 3. Enter the location of the data you want to correspond to the horizontal values in the Series X values: box (see Figure 2.10). Do not include column headers Step 4. Repeat Step 3 for Series Y Values: box and the Series bubble size: box Click OK.

## 统计代写|数据可视化作业代写data visualization代考|Selecting an Appropriate Chart

• Composition-Composition 构成了所考虑的实体的整体。一个例子是图 2.2 中的条形图。
• Ranking-Ranking是项目的相对顺序。数字2.2也是排名的一个例子，因为我们已经按照条形长度对类别进行了排序，条形长度与分配的数量成正比。
• 相关性/关系-相关性是两个变量相互关联的方式。这方面的一个例子是美国各个城市的平均低温和年平均降雪量之间的关系。
• Distribution-Distribution 是项目的分散方式。这方面的一个例子是呼叫中心在一天内接到的电话数量，按小时计算。
您拥有的数据类型也应该影响您的图表选择。例如，当我们汇总有关类别的数据时，条形图或柱形图通常是合适的图表。大学课程中学生的字母成绩属于类别。为了总结获得每个字母等级的学生人数，条形图或柱形图将是合适的。
两个定量变量之间的关系通常使散点图成为合适的选择。横轴为时间的条形图、散点图和折线图通常是时间序列数据的最佳选择。如果您的数据具有空间组件，则地图可能是一个不错的选择。

## 统计代写|数据可视化作业代写data visualization代考|Scatter Charts and Bubble Charts

Stẹp 2. 单击功能区上的插入选项卡

## 统计代写|数据可视化作业代写data visualization代考|Bubble Charts

Step 2. 当 Select Data Source 对话框出现时，单击 Legend Entries (Series) 下的 Edit 按钮
Step 3. 输入您想要对应的数据的位置Series X values: 框中的水平值（参见图 2.10）。不包括列标题 第 4 步。对 Y 系列值重复第 3 步：框和系列气泡大小：框单击确定。

## 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。