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# 商科代写|商业统计代考BUSINESS STATISTICS代考|ECON225 Looking at Scatterplots

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The Texas Transportation Institute (TTI), founded in 1950 , studies and develops solutions to challenges faced by all forms of transportation. Although the goal is to solve the transportation problems of 2025 , the TTI started collecting data on the relationship between freeway speed and the cost to society of freeway congestion as early as the year 2000 . Figure $4.2$ shows a scatterplot of the annual Congestion Cost Per Person of traffic delays (in dollars) in 65 cities in the United States against the Peak Period Freeway Speed (mph).

If you want to describe the scatterplot of Congestion Cost against Freeway Speed, you might first mention the direction of the association. As the peak freeway speed goes up, the cost of congestion goes down. A pattern that runs from the upper left to the lower right $\because$ : is said to be negative. A pattern running the other
way $\therefore^{\circ}$, as we saw for the price and size of houses, is called positive.
The second thing to look for in a scatterplot is its form. If there is a straight line relationship, it will appear as a cloud or swarm of points stretched out in a generally consistent, straight form. For example, the scatterplot of house prices (Figure 4.1) has an underlying linear form, although some points stray away from it.
Scatterplots can reveal many different kinds of patterns. Often they will not be straight, but straight line patterns are both the most common and the most useful for statistics.

If the relationship isn’t straight, but curves gently, while still increasing or we can often find ways to straighten it out by re-expressing one (or both) of the variables. But if it curves sharply-up and then down, for example,—then you’ll need more advanced methods.The third feature to look for in a scatterplot is the strength of the relationship.

## 商科代写|商业统计代考BUSINESS STATISTICS代考|Assigning Roles to Variables in Scatterplots

To make a scatterplot of two quantitative variables, assign one to the $y$-axis and the other to the $x$-axis. ${ }^{1}$ As with any graph, be sure to label the axes clearly, and indicate the scales of the axes with numbers. Scatterplots display quantitative variables. Each variable has units, and these should appear with the display-usually near each axis. Each point is placed on a scatterplot at a position that corresponds to values of these two variables. Its horizontal location is specified by its $x$-value, and its vertical location is specified by its $y$-value variable. Together, these are known as coordinates and written $(x, y)$.

Scatterplots made by computer programs (such as the two we’ve seen in this chapter) often do not-and usually should not-show the origin, the point at $x=0, y=0$ where the axes meet. If both variables have values near or on both sides of zero, then the origin will be part of the display. If the values are far from zero, though, there’s no reason to include the origin. In fact, it’s far better to focus on the part of the Cartesian plane that contains the data. In our example about house prices, none of the houses were free and all had some area so the computer drew the scatterplot in Figure $4.1$ with axes that don’t quite meet.

## 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。