Statistics with R Capstone

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课程主页: https://www.coursera.org/archive/statistics-project

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课程简介

Duke University

课程大纲

Welcome to the capstone project! This week's content is an introduction to the project assignment and goals. The readings in this week will introduce the data set that you will be analyzing for your project and the specific questions you will answer using data analysis techniques we learned in the previous courses. It is important to understand what we will be doing in the course before jumping into the detailed analysis. So we encourage you to start with the first lecture to get the big picture, and then delve into the specifics of the analysis. Enjoy, and good luck! Remember, if you have questions, you can post them on the discussion forums.

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课程详情

The capstone project will be an analysis using R that answers a specific scientific/business question provided by the course team. A large and complex dataset will be provided to learners and the analysis will require the application of a variety of methods and techniques introduced in the previous courses, including exploratory data analysis through data visualization and numerical summaries, statistical inference, and modeling as well as interpretations of these results in the context of the data and the research question. The analysis will implement both frequentist and Bayesian techniques and discuss in context of the data how these two approaches are similar and different, and what these differences mean for conclusions that can be drawn from the data. A sampling of the final projects will be featured on the Duke Statistical Science department website. Note: Only learners who have passed the four previous courses in the specialization are eligible to take the Capstone.

使用R Capstone进行统计:最高项目将使用R进行分析,回答课程团队提供的特定科学/商业问题。将为学习者提供一个庞大而复杂的数据集,分析将需要应用先前课程中介绍的各种方法和技术,包括通过数据可视化和数值汇总进行探索性数据分析,统计推断,建模以及解释这些结果是在数据和研究问题的背景下得出的。该分析将同时使用常驻技术和贝叶斯技术,并在数据的上下文中讨论这两种方法如何相似和不同,以及这些不同意味着可以从数据中得出结论。   最终项目的样本将在Duke统计科学部门的网站上进行介绍。 注意:只有通过了本专业前四门课程的学习者才有资格参加Capstone。

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