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assignmentutor-lab™ 为您的留学生涯保驾护航 在代写线性代数linear algebra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。我们的专家在代写线性代数linear algebra代写方面经验极为丰富，各种代写线性代数linear algebra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

## 数学代写|线性代数代写linear algebra代考|Descriptive and Inferential Statistics

It may seem odd to define “data,” something we all use and take for granted. But I think it needs to be done. Chances are if you asked any person what data is, they might answer to the effect of “you know… data! I’s… you know…information!” and not venture farther than that. Now it seems to be marketed as the be-all and end-all. The source of not just truth…but intelligence! It’s the fuel for artificial intelligence and it is believed that the more data you have, the more truth you have. Therefore, you can never have enough data. It will unlock the secrets needed to redefine your business strategy and maybe even create artificial general intelligence. But let me offer a pragmatic perspective on what data is. Data is not important in itself. It’s the analysis of data (and how it is produced) that is the driver of all these innovations and solutions.

Imagine you were provided a photo of a family. Can you glean this family’s story based on this one photo? What if you had 20 photos? 200 photos? 2,000 photos? How many photos do you need to know their story? Do you need photos of them in different situations? Alone and together? With relatives and friends? At home and at work?

Data is just like photographs; it provides snapshots of a story. The continuous reality and contexts are not fully captured, nor the infinite number of variables driving that story. As we will discuss, data may be biased. It can have gaps and be missing relevant variables. Ideally, we would love to have an infinite amount of data capturing an infinite number of variables, with so much detail we could virtually re-create reality and construct alternate ones! But is this possible? Currently, no. Not even the greatest supercomputers in the world combined can come close to capturing the entirety of the world as data.

## 数学代写|线性代数代写linear algebra代考|Descriptive Versus Inferential Statistics

What comes to mind when you hear the word “statistics”? Is it calculating mean, median, mode, charts, bell curves, and other tools to describe data? This is the most commonly understood part of statistics, called descriptive statistics, and we use it to summarize data. After all, is it more meaningful to scroll through a million records of data or have it summarized? We will cover this area of statistics first.

Inferential statistics tries to uncover attributes about a larger population, often based on a sample. It is often misunderstood and less intuitive than descriptive statistics. Often we are interested in studying a group that is too large to observe (e.g., average height of adolescents in North America) and we have to resort to using only a few members of that group to infer conclusions about them. As you can guess, this is not easy to get right. After all, we are trying to represent a population with a sample that may not be representative. We will explore these caveats along the way.

# 线性代数代考

## 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。

assignmentutor™您的专属作业导师
assignmentutor™您的专属作业导师