R Programming

所在平台: Coursera

课程主页: https://www.coursera.org/learn/r-programming

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课程简介

课程名称：R编程 课程概述：在这门课程中，您将学习如何使用R进行编程和有效的数据分析。您将学会安装和配置统计编程环境所需的软件，理解通用编程语言概念在高层统计语言中的实现。课程内容涵盖统计计算中的实际问题，包括R编程、数据导入、访问R包、编写R函数、调试、代码性能分析以及组织和注释R代码。统计数据分析中的主题将提供实际案例供您参考。 课程大纲： 第1周：背景、入门及基本内容 描述：这一周将涵盖R的基础知识。背景资料部分包含有关课程机制的信息和R安装的视频。第1周视频介绍了R和S的历史，基本数据类型，以及读取和写入数据的函数。推荐按顺序观看视频，但顺序不影响理解。 第2周：使用R编程 描述：欢迎来到R编程的第2周。本周，我们将深入讲解控制结构和函数等关键主题。此外，我们还将介绍课程的第一个编程作业，作业需在周末前提交。 第3周：循环函数和调试 描述：现在进入R编程的第3周，这也是课程的中期。此次课程讲解循环函数和R中的调试工具。这些功能使R适用于互动式工作与编写长代码，因此在实际应用中非常常见。 第4周：模拟与性能分析 描述：本周将介绍如何在R中模拟数据，这是进行模拟研究的基础。我们还将讨论R中的分析器，它可以收集关于R函数运行的详细信息，并识别可以改进的瓶颈。分析器是优化程序的重要工具。另外，我们将介绍我个人认为是R中最有用的函数——str函数。

课程大纲

Name:Week 1: Background, Getting Started, and Nuts & Bolts

Description:This week covers the basics to get you started up with R. The Background Materials lesson contains information about course mechanics and some videos on installing R. The Week 1 videos cover the history of R and S, go over the basic data types in R, and describe the functions for reading and writing data. I recommend that you watch the videos in the listed order, but watching the videos out of order isn't going to ruin the story.

Name:Week 2: Programming with R

Description:Welcome to Week 2 of R Programming. This week, we take the gloves off, and the lectures cover key topics like control structures and functions. We also introduce the first programming assignment for the course, which is due at the end of the week.

Name:Week 3: Loop Functions and Debugging

Description:We have now entered the third week of R Programming, which also marks the halfway point. The lectures this week cover loop functions and the debugging tools in R. These aspects of R make R useful for both interactive work and writing longer code, and so they are commonly used in practice.

Name:Week 4: Simulation & Profiling

Description:This week covers how to simulate data in R, which serves as the basis for doing simulation studies. We also cover the profiler in R which lets you collect detailed information on how your R functions are running and to identify bottlenecks that can be addressed. The profiler is a key tool in helping you optimize your programs. Finally, we cover the str function, which I personally believe is the most useful function in R.

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