assignmentutor-lab™ 为您的留学生涯保驾护航 在代写贝叶斯分析Bayesian Analysis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。我们的专家在代写贝叶斯分析Bayesian Analysis代写方面经验极为丰富，各种代写贝叶斯分析Bayesian Analysis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|贝叶斯分析代写Bayesian Analysis代考|Why Relying on Data Alone Is Insufficient for Risk Assessment

The last decade has seen an explosion of interest in “big data” and sophisticated algorithms for analysing such data. The popular belief is Athat, with sufficiently “big” data and increasingly powerful “machine learning” algorithms it should be possible, by using purely automated methods applied to the data, to discover all of the properties and relationships of interest for both improved prediction and decision-making. For example, such methods have been applied to large databases of supermarket customers to understand and predict the buying patterns of customers and to determine the optimal time to release new products. In areas such as healthcare the hope is that, given large patient databases, such methods can be used to understand both the causes of particular diseases and the optimum treatments. Unfortunately, in most areas of critical decision making there is limited relevant data (e.g. in medicine doctors do not always record what they do), while in other areas even very large databases will never provide the required answers. Nor does “big data” necessarily mean good quality data.

For example, a popular and important area for such machine learning is the use of “credit scoring” by banks to determine the risk associated with making loans to customers. The kind of database used by banks for this purpose is shown in Table 2.16, where each record (i.e. row) corresponds to a customer who was previously granted a loan.

Since too many people “default” on loans, the bank wants to use machine learning techniques on this database to help decide whether or not to offer credit to new applicants. In other words they expect to “learn” when to refuse loans on the basis that the customer profile is too “risky.”

统计代写|贝叶斯分析代写Bayesian Analysis代考|Uncertain Information

Consider the following assertions:

1. Oliver Cromwell spoke more than 3,000 words on 23 April $1654 .$
2. O.J. Simpson murdered his wife.
3. You (the reader) have an as-yet undiagnosed form of cancer.
4. England will win the next World Cup.
The events in assertions 1 and 2 either happened or did not. Nobody currently knows whether the assertion in statement 1 happened. Only O.J. Simpson knows for certain whether assertion 2 happened. Assertion 3 describes a fact that is either true or false. Assertion 4 is different because it describes the outcome of an event that has not yet happened.

While all four assertions are very different what that all have in common is that our knowledge about them is uncertain (unless we happen to be O.J. Simpson). In this book the way we reason about such uncertainty is the same whether the events have happened or not and whether they are unknown or not. Unfortunately, many influential people do not accept the validity of this approach. We have an obligation to demonstrate why those influential people are wrong. To do this we will consider the simple scenario in Box $2.5$ that captures the key differences between uncertain information and incomplete information.

贝叶斯分析代考

统计代写|贝叶斯分析代写Bayesian Analysis代考|Uncertain Information

1. 奥利弗·克伦威尔在 4 月 23 日发表了超过 3,000 字的演讲1654.
2. OJ辛普森谋杀了他的妻子。
3. 您（读者）患有一种尚未确诊的癌症。
4. 英格兰将赢得下一届世界杯。
断言 1 和 2 中的事件要么发生，要么没有。目前没有人知道声明 1 中的断言是否发生。只有 OJ Simpson 确切地知道断言 2 是否发生。断言 3 描述了一个对或错的事实。断言 4 不同，因为它描述了尚未发生的事件的结果。

有限元方法代写

assignmentutor™作为专业的留学生服务机构，多年来已为美国、英国、加拿大、澳洲等留学热门地的学生提供专业的学术服务，包括但不限于Essay代写，Assignment代写，Dissertation代写，Report代写，小组作业代写，Proposal代写，Paper代写，Presentation代写，计算机作业代写，论文修改和润色，网课代做，exam代考等等。写作范围涵盖高中，本科，研究生等海外留学全阶段，辐射金融，经济学，会计学，审计学，管理学等全球99%专业科目。写作团队既有专业英语母语作者，也有海外名校硕博留学生，每位写作老师都拥有过硬的语言能力，专业的学科背景和学术写作经验。我们承诺100%原创，100%专业，100%准时，100%满意。

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。

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