### 数学网课代修|概率统计代写Probability and Statistics代考|MATH 200

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• 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

## 数学网课代修|概率统计代写Probability and Statistics代考|ALOHA Network

In this section, an example from computer networks is presented which, as with the bus ridership example, will be used at a number of points in this book. Probability analysis is used extensively in the development of new, faster types of networks.

We speak of nodes on a network. These might be computers, printers or other equipment. We will also speak of messages; for simplicity, let’s say a message consists of a single character. If a user at a computer hits the $\mathrm{N}$ key, say, in a connection with another computer, the user’s machine sends the ASCII code for that character onto the network. Of course, this was all transparent to the user, actions behind the scenes.

Today’s Ethernet evolved from an experimental network developed at the University of Hawaii, called ALOHA. A number of network nodes would occasionally try to use the same radio channel to communicate with a central computer. The nodees couldn’t hear éach otherr, dué to the obstruction of mountains between them. If only one of them made an attempt to send, it would be successful, and it would receive an acknowledgement message in response from the central computer. But if more than one node were to transmit, a collision would occur, garbling all the messages. The sending nodes would timeout after waiting for an acknowledgement that never came, and try sending again later. To avoid having too many collisions, nodes would engage in random backoff, meaning that they would refrain from sending for a while even though they had something to send.

## 数学网课代修|概率统计代写Probability and Statistics代考|ALOHA in the Notebook Context

Think of doing the ALOHA “experiment” many, many times. Let’s interpret the numbers we found above, e.g., $P\left(X_{1}=2\right)=0.52$, in the notebook context.

• Run the network for two epochs, starting with both nodes active, the first time, and write the outcome on the first line of the notebook.
• Run the network for two epochs, starting with both nodes active, the second time, and write the outcome on the second line of the notebook.
• Run the network for two epochs, starting with both nodes active, the third time, and write the outcome on the third line of the notebook.
• Run the network for two epochs, starting with both nodes active, the fourth time, and write the outcome on the fourth line of the notebook.
• Imagine you keep doing this, thousands of times, filling thousands of linés in thé notebbook.

Thẻ first seveen linés of thè notẻbook might look liké Táblè1.3. Wé seee that:

• Among those first seven lines in the notebook, 4/7 of them have $X_{1}=2$. After many, many lines, this fraction will be approximately $0.52$.
• Among those first seven lines in the notebook, $3 / 7$ of them have $X_{2}=2$. After many, many lines, this fraction will be approximately $0.47 .{ }^{7}$
• Among those first seven lines in the notebook, $2 / 7$ of them have $X_{1}=2$ and $X_{2}=2$. After many, many lines, this fraction will be approximately $0.27 .$
• Among the first seven lines in the notebook, four of them do not say NA in the $X_{2}=2 \mid X_{1}=2$ column. Among these four lines, two say Yes, a fraction of $2 / 4$. After many, many lines, this fraction will be approximately $0.52$.

## 数学网课代修|概率统计代写Probability and Statistics代考|ALOHA in the Notebook Context

• 将网络运行两个 epoch，第一次从两个节点都处于活动状态开始，并将结果写在笔记本的第一行。
• 将网络运行两个 epoch，第二次从两个节点都处于活动状态开始，并将结果写在笔记本的第二行。
• 运行网络两个 epoch，从两个节点开始，第三次，并将结果写在笔记本的第三行。
• 运行网络两个 epoch，从两个节点开始，第四次，并将结果写在笔记本的第四行。
• 想象一下，你不断地这样做，数千次，在笔记本中填满数千行。

thè notẻbook 的前七行可能看起来像 Táblè1.3。我们看到：

• 在笔记本的前七行中，有 4/7X1=2. 在很多很多行之后，这个分数将大约为0.52.
• 在笔记本的前七行中，3/7其中有X2=2. 在很多很多行之后，这个分数将大约为0.47.7
• 在笔记本的前七行中，2/7其中有X1=2和X2=2. 在很多很多行之后，这个分数将大约为0.27.
• 笔记本前七行中，有四行没有在X2=2∣X1=2柱子。在这四行中，有两行说是，一小部分2/4. 在很多很多行之后，这个分数将大约为0.52.

## 有限元方法代写

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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。