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## 数据科学代写|数据可视化代写Data Visualization代考|Relative Frequency and Percent Frequency

A frequency distribution, such as the one in Figure $5.4$, shows the number (count) of items in each of several nonoverlapping bins. However, we are often interested in the proportion, or percentage, of items in each bin. The relative frequency of a bin equals the fraction or proportion of items belonging to a class. For a data set with $n$ observations, the relative frequency of each bin can be determined as follows:
$$\text { Relative frequency of a bin }=\frac{\text { Frequency of the bin }}{n}$$
Often a relative frequency is expressed as a percentage. The percent frequency of a bin is the relative frequency multiplied by 100 . To obtain a percent frequency distribution for the data in the Pop file, we continue from the PivotTable in Figure $5.4$ with the following steps:
Step 1. Select any cell in the Count of Soft Drink Purchase column of the PivotTable (any cell in range B3:B8)
Step 2. When the PivotTable Fields task pane appears:
In the Values area, select the triangle to the right of Count of Soft Drink
Purchase Count of Soft Drink Purchase
Select Value Field Settings… from the list of options.
Step 3. When the Value Field Settings dialog box appears:
Click the Show Values As tab and in the box below Show values as select $\%$ of Grand Total

Figure $5.6$ shows the result of the preceding steps. The percent frequency for Coca-Cola is $190 / 500=0.38=38 \%$, the percent frequency for Pepsi is $130 / 500=0.26=16 \%$, and so on. We can also note that $38 \%+26 \%+16 \%=80 \%$ of the purchases were the top three soft drinks.
A percent frequency distribution can be used to provide estimates of the relative likelihoods of different values for a random variable. So, by constructing a percent frequency distribution from observations of a random variable, we can estimate the probability distribution that characterizes its variability. For example, suppose that a concession stand has determined it will procure a total of 12,000 ounces of soft drinks for an upcoming concert, but it is uncertain how to divide this total over the individual soft drink types. However, if the data in the Pop file are representative of the concession stand’s customer population, the manager can use this information to determine appropriate volumes of each type of soft drink. For example, the data suggest that the manager should procure $12,000 \times 0.38=4,560$ ounces of Coca-Cola.

## 数据科学代写|数据可视化代写Data Visualization代考|Visualizing Distributions of Quantitative Data

As with categorical data, we can create frequency distributions for quantitative data, but we must be more careful in defining the nonoverlapping bins to be used in the frequency distribution. Recall that for categorical data, a frequency distribution’s bins are based on the different categories. For quantitative data, each bin in the frequency distribution is based on the range of values that the bin contains.

To create a frequency distribution for quantitative data, three features need to be defined:

1. The number of nonoverlapping bins
2. The width (numerical range) of each bin
3. The range spanned by the set of bins
Excel possesses functionality that automatically defines each of these features. To demonstrate, consider a data set that contains the age at death for 700 individuals. Figure $5.8$ displays a portion of this data, contained in the file Death. The following steps construct the histogram in Figure $5.9$ illustrating the distribution of the ages at death.
Step 1. Select cells A1:A701
Step 2. Click the Insert tab on the Ribbon
Step 3. Click the Insert Statistic Chart button $\mathbb{l l}^{\vee} \vee$ in the Charts group
When the list of statistic charts appears, select Histogram 1 Hh

## 数据科学代写数据可视化代写Data Visualization代考|Relative Frequency and Percent Frequency

Relative frequency of a bin $=\frac{\text { Frequency of the bin }}{n}$

$130 / 500=0.26=16 \%$ ，等等。我们还可以住意到 $38 \%+26 \%+16 \%=80 \%$ 购买量中排名前三的软饩料。

## 数据科学代写|数据可视化代写Data Visualization代考|Visualizing Distributions of Quantitative Data

1. 非重腚 bin 的数量
2. 每个 bin 的宽度（数值范围）
3. 由一组 bin 跨越的范围
Excel 具有自动定义这些特征中的每一个的功能。为了演示，考虑一个包含 700 个人的死亡年龄的数据集。数字 $5.8$ 显示该 数据的一部分，包含在文件 Death 中。下面的步骙构建了图中的直方图 $5.9$ 说明死亡年齡的分布。
步骤 1. 选择单元格 Al:A701
步骤 2. 单击功能区上的揷入选项卡
步骤 3. 单击揷入统计图表㧍铒 $\vee \vee \vee$ 在图表组
中出现统计图表列表时，选译直方图 $1 \mathrm{Hh}$

## 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。

Posted on Categories:Data visualization, R语言, 数据可视化, 统计代写

## 统计代写|数据可视化代考DATA VISUALIZATION代考|BAN271 Common Mistakes in Data Visualization Design

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## 统计代写|数据可视化代考DATA VISUALIZATION代考|Wrong Type of Visualization

The best type of chart or table to use for data visualization strongly depends on the audience that will view the visualization as well as the insights or story that is to be told through the visualization. Throughout this textbook, we provide best practices for designing effective data visualizations, but many of the decisions related to which chart to use and some aspects of the design will depend on the situation and goal of the visualization. In this section, we use the concepts presented in this chapter to discuss several situations for which one type of visualization is preferred over another. However, we must keep in mind that the most effective visualization depends on the needs of the audience and the message we are trying to convey.
If the goal of the visualization is to convey precise numerical values, then it is often preferable to use a table rather than a chart. Because it is more difficult for an audience to make relative comparisons on the preattentive attribute of shape than on the preattentive attribute of length, bar or column charts are generally preferred over pie charts. However, there are cases for which the most appropriate type of visualization depends on the goal of the visualization and is not always obvious.

## 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。