R语言全栈学习合集：从入门到数据科学（视频+字幕+课件）

📁 共 1644 个文件💾 总大小 52.8GB🕐 更新于 2026-09-24👁 0 次浏览🏅 平台定级 A 级

📋 资源介绍

本合集为R语言系统学习资源，共1644个文件、52.8GB，覆盖从零基础到数据科学的完整路径。资源构成：①初级教程（共42学时）——R语言进阶，含基本制图函数、关键制图参数、散点图、线图与时间序列谱图、柱形图/点图/饼图/直方图、箱线图与热力图、等高线/地图/图形文件转换、R扩展包制作等模块，配套PDF讲义与作业资料；②中级教程（共311集）——R语言Data Science数据科学，含数据科学家的宝箱（28学时）、R语言编程（41学时，中文）、数据采集与清洗（27学时）、探索性数据分析（31学时）等，视频多为MP4并配中英文字幕（SRT）。适合人群：零基础转行者、在校学生、数据分析从业者及需用R做统计建模与可视化的职场人。学习收获：掌握R语法与函数、数据获取与清洗、探索性分析与ggplot2可视化、聚类与降维等核心技能，可独立完成数据分析项目。重要参数：1644个文件，52.8GB，视频+PDF+字幕+压缩包，中文为主、部分英文原声配中英字幕。

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🗂️ 完整文件清单（1644 个文件 / 52.8GB）

📁 004.初级教程（共42学时）——R语言进阶 55 项
- 📁 001——（全4学时）第1周基本制图函数综述 6 项
  - 📄 Rgraph01c.mp474.5MB
  - 📄 Rgraph01d.mp471.4MB
  - 📄 Rgraph01b.mp491.4MB
  - 📄 Rgraph01a.mp482.6MB
  - 📄 更多资源关注微信公众【虎猫365资源库】.jpg115KB
  - 📄 数据展现01.pdf2.5MB
- 📁 002——（全2学时）第2周理解关键制图参数 4 项
  - 📄 Rgraph02a.mp489.6MB
  - 📄 更多资源关注微信公众【虎猫365资源库】.jpg115KB
  - 📄 Rgraph02b.mp484.6MB
  - 📄 数据展现02.pdf1.7MB
- 📁 003——（全3学时）第3周散点图 5 项
  - 📄 Rgraph03c.mp443MB
  - 📄 Rgraph03b.mp492.4MB
  - 📄 更多资源关注微信公众【虎猫365资源库】.jpg115KB
  - 📄 数据展现03.pdf1.3MB
  - 📄 Rgraph03a.mp456.2MB
- 📁 004——（全4学时）第4周线图与时间序列谱图 6 项
  - 📄 Rgraph04b.mp446.6MB
  - 📄 Rgraph04c.mp471.6MB
  - 📄 更多资源关注微信公众【虎猫365资源库】.jpg115KB
  - 📄 数据展现04.pdf1.4MB
  - 📄 Rgraph04a.mp499.9MB
  - 📄 Rgraph04d.mp497.5MB
- 📁 005——（全3学时）第5周柱形图，点图，饼图，直方图 5 项
  - 📄 Rgraph05c.mp464MB
  - 📄 数据展现05.pdf2.1MB
  - 📄 Rgraph05a.mp481.2MB
  - 📄 更多资源关注微信公众【虎猫365资源库】.jpg115KB
  - 📄 Rgraph05b.mp475.2MB
- 📁 006——（全4学时）第6周箱线图，热力图 6 项
  - 📄 数据展现06.pdf774KB
  - 📄 Rgraph06d.mp441.5MB
  - 📄 更多资源关注微信公众【虎猫365资源库】.jpg115KB
  - 📄 Rgraph06c.mp464.9MB
  - 📄 Rgraph06b.mp466.8MB
  - 📄 Rgraph06a.mp494.1MB
- 📁 007——（全5学时）第7周等高线，地图，转换为图形文件 7 项
  - 📄 Rgraph07c.mp4132MB
  - 📄 数据展现07.pdf1.8MB
  - 📄 Rgraph07a.mp486.1MB
  - 📄 Rgraph07d.mp464.1MB
  - 📄 更多资源关注微信公众【虎猫365资源库】.jpg115KB
  - 📄 Rgraph07e.mp449.4MB
  - 📄 Rgraph07b.mp465.5MB
- 📁 013——（全2学时）第13周怎样制作R扩展包 3 项
  - 📄 Rpackage.pdf643KB
  - 📄 Rpackage2.mp447.8MB
  - 📄 Rpackage1.mp438.8MB
- 📁 014——课程资料 3 项
  - 📄 资料.rar53.1MB
  - 📄 更多资源关注微信公众【虎猫365资源库】.jpg115KB
  - 📄 作业.rar2.1KB
- 📄 更多资源关注微信公众【虎猫365资源库】.jpg115KB
📁 006.中级教程（共 311集）——R语言Data Science数据科学 501 项
- 📁 001——（全28学时）数据科学家的宝箱 86 项
  - 📁 1.数据科学家的宝箱英文字幕 28 项
    📄 1 - 11 - Practical Machine Learning Overview (1-31).srt2.6KB
    📄 1 - 5 - R Programming Overview (2-12).srt3.9KB
    📄 1 - 8 - Reproducible Research Overview (1-27).srt2.4KB
    📄 1 - 2 - The Data Scientist-'s Toolbox (5-09).srt8.9KB
    📄 1 - 12 - Building Data Products Overview (1-19).srt2.4KB
    📄 3 - 3 - What About Big Data- (4-15).srt6.7KB
    📄 3 - 2 - What is Data- (5-15).srt9.1KB
    📄 2 - 2 - Command Line Interface (16-04).srt23.5KB
    📄 1 - 4 - Finding Answers (4-35).srt8.1KB
    📄 2 - 6 - Basic Git Commands (5-52).srt10.3KB
    📄 1 - 9 - Statistical Inference Overview (1-06).srt1.7KB
    📄 2 - 3 - Introduction to Git (4-49).srt7.6KB
    📄 1 - 13 - Installing R on Windows (3-20) {Roger Peng}.srt5.9KB
    📄 3 - 1 - Types of Questions (9-09).srt15.5KB
    📄 1 - 3 - Getting Help (8-52).srt15.2KB
    📄 2 - 5 - Creating a Github Repository (5-51).srt8.7KB
    📄 2 - 8 - Installing R Packages (5-37).srt8.7KB
    📄 2 - 7 - Basic Markdown (2-22).srt3.8KB
    📄 2 - 9 - Installing Rtools (2-29).srt4KB
    📄 1 - 15 - Installing Rstudio (1-36) {Roger Peng}.srt2.5KB
    📄 1 - 10 - Regression Models Overview (1-46).srt3.1KB
    📄 1 - 6 - Getting Data Overview (1-34).srt2.8KB
    📄 1 - 7 - Exploratory Data Analysis Overview (1-21).srt2.4KB
    📄 更多资源关注微信公众【虎猫365资源库】.jpg115KB
    📄 2 - 4 - Introduction to Github (3-53).srt6.5KB
    📄 1 - 1 - Series Motivation (12-03).srt21.5KB
    📄 3 - 4 - Experimental Design (15-59).srt27KB
    📄 1 - 14 - Install R on a Mac (2-02) {Roger Peng}.srt3.4KB
  - 📁 1.数据科学家的宝箱中文字幕 28 项
    📄 1 - 7 - Exploratory Data Analysis Overview (1-21).srt2.1KB
    📄 1 - 8 - Reproducible Research Overview (1-27).srt2.1KB
    📄 3 - 2 - What is Data- (5-15).srt8KB
    📄 1 - 11 - Practical Machine Learning Overview (1-31).srt2.5KB
    📄 1 - 4 - Finding Answers (4-35).srt7.3KB
    📄 3 - 4 - Experimental Design (15-59).srt23.6KB
    📄 2 - 2 - Command Line Interface (16-04).srt20.9KB
    📄 1 - 9 - Statistical Inference Overview (1-06).srt1.5KB
    📄 1 - 14 - Install R on a Mac (2-02) {Roger Peng}.srt2.8KB
    📄 1 - 5 - R Programming Overview (2-12).srt3.4KB
    📄 1 - 6 - Getting Data Overview (1-34).srt2.4KB
    📄 2 - 5 - Creating a Github Repository (5-51).srt8.8KB
    📄 1 - 2 - The Data Scientist-'s Toolbox (5-09).srt7.9KB
    📄 2 - 8 - Installing R Packages (5-37).srt7.6KB
    📄 2 - 7 - Basic Markdown (2-22).srt3.1KB
    📄 1 - 1 - Series Motivation (12-03).srt17.9KB
    📄 2 - 9 - Installing Rtools (2-29).srt3.5KB
    📄 2 - 4 - Introduction to Github (3-53).srt5.7KB
    📄 1 - 13 - Installing R on Windows (3-20) {Roger Peng}.srt5.1KB
    📄 3 - 3 - What About Big Data- (4-15).srt6.2KB
    📄 2 - 6 - Basic Git Commands (5-52).srt7.8KB
    📄 1 - 10 - Regression Models Overview (1-46).srt2.8KB
    📄 1 - 15 - Installing Rstudio (1-36) {Roger Peng}.srt2.2KB
    📄 更多资源关注微信公众【虎猫365资源库】.jpg115KB
    📄 1 - 3 - Getting Help (8-52).srt13.2KB
    📄 3 - 1 - Types of Questions (9-09).srt13.4KB
    📄 1 - 12 - Building Data Products Overview (1-19).srt2.2KB
    📄 2 - 3 - Introduction to Git (4-49).srt6.4KB
  - 📄 1 - 13 - Installing R on Windows (3-20) {Roger Peng}.mp45.1MB
  - 📄 1 - 10 - Regression Models Overview (1-46).mp41.5MB
  - 📄 2 - 5 - Creating a Github Repository (5-51).mp44.8MB
  - 📄 2 - 1 - Tips from Coursera Users - Optional Video (3-53).mp48MB
  - 📄 3 - 3 - What About Big Data- (4-15).mp43.8MB
  - 📄 2 - 4 - Introduction to Github (3-53).mp43.2MB
  - 📄 3 - 2 - What is Data- (5-15).mp44.7MB
  - 📄 1 - 1 - Series Motivation (12-03).mp49.6MB
  - 📄 2 - 7 - Basic Markdown (2-22).mp41.8MB
  - 📄 2 - 6 - Basic Git Commands (5-52).mp44.4MB
  - 📄 1 - 7 - Exploratory Data Analysis Overview (1-21).mp41.1MB
  - 📄 3 - 4 - Experimental Design (15-59).mp413.3MB
  - 📄 1 - 2 - The Data Scientist-'s Toolbox (5-09).mp44.4MB
  - 📄 2 - 8 - Installing R Packages (5-37).mp44.8MB
  - 📄 1 - 11 - Practical Machine Learning Overview (1-31).mp41.3MB
  - 📄 1 - 14 - Install R on a Mac (2-02) {Roger Peng}.mp44MB
  - 📄 更多资源关注微信公众【虎猫365资源库】.jpg115KB
  - 📄 2 - 2 - Command Line Interface (16-04).mp412.4MB
  - 📄 1 - 6 - Getting Data Overview (1-34).mp41.2MB
  - 📄 2 - 3 - Introduction to Git (4-49).mp46.2MB
  - 📄 1 - 4 - Finding Answers (4-35).mp43.8MB
  - 📄 1 - 12 - Building Data Products Overview (1-19).mp41.2MB
  - 📄 1 - 3 - Getting Help (8-52).mp46.7MB
  - 📄 1 - 8 - Reproducible Research Overview (1-27).mp41.1MB
  - 📄 1 - 5 - R Programming Overview (2-12).mp41.7MB
  - 📄 3 - 1 - Types of Questions (9-09).mp47.7MB
  - 📄 2 - 9 - Installing Rtools (2-29).mp42.2MB
  - 📄 1 - 9 - Statistical Inference Overview (1-06).mp4892KB
- 📁 002——（全41学时）R语言编程（中文） 42 项
  - 📄 2 - 9 - 向量化运算 [3-46].mp42.5MB
  - 📄 2 - 8 - 提取子集 (第2部分) [10-18].mp46.6MB
  - 📄 4 - 5 - split [9-09].mp46.2MB
  - 📄 3 - 7 - 作用域规则 (第2部分) [8-34].mp45.7MB
  - 📄 1 - 6 - 使用R版本3.1.1.mp42.5MB
  - 📄 3 - 3 - 你的第一个 R 函数 [10-29].mp416.5MB
  - 📄 4 - 7 - 调试工具 (第2部分) [6-25].mp44.9MB
  - 📄 2 - 11 - 读写数据 (第2部分) [9-30].mp46.6MB
  - 📄 3 - 4 - 函数 (第1部分) [9-17].mp46.5MB
  - 📄 2 - 3 - 寻求帮助 [13-53].mp49.2MB
  - 📄 2 - 5 - 数据类型 (第2部分) [9-45].mp46.6MB
  - 📄 5 - 5 - R编译器 (第2部分) [10-26].mp411.2MB
  - 📄 3 - 6 - 作用域规则 (第1部分) [10-32].mp47.6MB
  - 📄 3 - 1 - 控制结构 (第1部分) [7-10].mp44.8MB
  - 📄 5 - 3 - 模拟 (第2部分) [7-02].mp44.8MB
  - 📄 3 - 10 - 日期和时间 [10-29].mp411.8MB
  - 📄 4 - 6 - 调试工具 (第1部分) [12-33].mp48.4MB
  - 📄 1 - 4 - 写代码- 建立你的工作目录 (Windows).mp48.9MB
  - 📄 2 - 10 - 读写数据 (第1部分) [12-55].mp415.2MB
  - 📄 3 - 5 - 函数 (第2部分) [7-13].mp44.9MB
  - 📄 更多资源关注微信公众【虎猫365资源库】.jpg115KB
  - 📄 3 - 2 - 控制结构 (第2部分) [8-11].mp45.5MB
  - 📄 4 - 3 - mapply [4-46].mp43.2MB
  - 📄 5 - 1 - str 函数 [6-08].mp45.8MB
  - 📄 2 - 2 - 概述R的历史 [16-07].mp411.6MB
  - 📄 4 - 1 - lapply [9-23].mp46.1MB
  - 📄 1 - 1 - 在Windows上安装R.mp45.1MB
  - 📄 2 - 12 - swirl 简介.mp43.2MB
  - 📄 1 - 5 - 写代码- 建立你的工作目录 (Mac).mp411.2MB
  - 📄 4 - 4 - tapply [3-17].mp42.2MB
  - 📄 2 - 6 - 数据类型 (第3部分) [11-51].mp48.1MB
  - 📄 3 - 9 - 写代码标准 [8-59].mp414.8MB
  - 📄 4 - 8 - 调试工具 (第3部分) [8-21].mp45.4MB
  - 📄 4 - 2 - apply [7-21].mp45MB
  - 📄 5 - 2 - 模拟 (第1部分) [7-47].mp45.3MB
  - 📄 2 - 7 - 提取子集 (第1部分) [7-01].mp44.6MB
  - 📄 2 - 4 - 数据类型 (第1部分) [9-26].mp46.6MB
  - 📄 5 - 4 - R编译器 (第1部分) [10-39].mp49.2MB
  - 📄 3 - 8 - 作用域规则 (第3部分) [9-21].mp46.4MB
  - 📄 1 - 3 - 安装R Studio (Mac).mp42.6MB
  - 📄 1 - 2 - 在Mac上安装R.mp44MB
  - 📄 2 - 1 - 简介.mp44.1MB
- 📁 003——（全27学时）数据采集与清洗 81 项
  - 📁 3.数据获取与处理英文字幕 27 项
    📄 2 - 4 - Reading From APIs (7-57).srt12.6KB
    📄 2 - 2 - Reading from HDF5 (6-45).srt10.4KB
    📄 4 - 3 - Regular Expressions II (8-00).srt11.7KB
    📄 1 - 5 - Reading Local Files (4-55).srt7.5KB
    📄 1 - 9 - The data.table Package (11-18).srt17.1KB
    📄 1 - 7 - Reading XML (12-39).srt20.7KB
    📄 更多资源关注微信公众【虎猫365资源库】.jpg115KB
    📄 4 - 1 - Editing Text Variables (10-46).srt17.2KB
    📄 3 - 7 - Merging Data (6-19).srt9.5KB
    📄 3 - 1 - Subsetting and Sorting (6-51).srt10.4KB
    📄 4 - 5 - Data Resources (3-33).srt5.8KB
    📄 2 - 3 - Reading from The Web (6-47).srt11KB
    📄 2 - 1 - Reading from MySQL (14-44).srt24.5KB
    📄 3 - 6 - Managing Data Frames with dplyr - Basic Tools.srt19.2KB
    📄 1 - 2 - Raw and Processed Data (7-07).srt11.8KB
    📄 4 - 2 - Regular Expressions I (5-16).srt8.1KB
    📄 2 - 5 - Reading From Other Sources (4-44).srt7.4KB
    📄 1 - 6 - Reading Excel Files (3-55).srt6.6KB
    📄 1 - 4 - Downloading Files (7-09).srt11.4KB
    📄 1 - 1 - Obtaining Data Motivation (5-38).srt10KB
    📄 3 - 4 - Reshaping Data (9-13).srt13.8KB
    📄 1 - 3 - Components of Tidy Data (9-25).srt16.3KB
    📄 1 - 8 - Reading JSON (5-03).srt8.5KB
    📄 3 - 3 - Creating New Variables (10-32).srt16.6KB
    📄 3 - 2 - Summarizing Data (11-37).srt18.1KB
    📄 3 - 5 - Managing Data Frames with dplyr - Introduction.srt4.9KB
    📄 4 - 4 - Working with Dates (6-02).srt9.9KB
  - 📁 3.数据获取与处理中文字幕 24 项
    📄 4 - 2 - Regular Expressions I (5-16).srt6.9KB
    📄 2 - 2 - Reading from HDF5 (6-45).srt8.9KB
    📄 1 - 4 - Downloading Files (7-09).srt10.2KB
    📄 1 - 9 - The data.table Package (11-18).srt15.6KB
    📄 3 - 4 - Reshaping Data (9-13).srt12KB
    📄 3 - 7 - Merging Data (6-19).srt8.4KB
    📄 3 - 3 - Creating New Variables (10-32).srt13.9KB
    📄 2 - 5 - Reading From Other Sources (4-44).srt6.6KB
    📄 2 - 4 - Reading From APIs (7-57).srt10.8KB
    📄 1 - 7 - Reading XML (12-39).srt17.6KB
    📄 更多资源关注微信公众【虎猫365资源库】.jpg115KB
    📄 1 - 8 - Reading JSON (5-03).srt7.2KB
    📄 3 - 1 - Subsetting and Sorting (6-51).srt8.4KB
    📄 4 - 1 - Editing Text Variables (10-46).srt14.8KB
    📄 3 - 2 - Summarizing Data (11-37).srt14.7KB
    📄 4 - 5 - Data Resources (3-33).srt5.2KB
    📄 1 - 2 - Raw and Processed Data (7-07).srt10KB
    📄 1 - 6 - Reading Excel Files (3-55).srt5.7KB
    📄 4 - 3 - Regular Expressions II (8-00).srt10.2KB
    📄 2 - 3 - Reading from The Web (6-47).srt9.2KB
    📄 2 - 1 - Reading from MySQL (14-44).srt20.9KB
    📄 1 - 3 - Components of Tidy Data (9-25).srt13.5KB
    📄 4 - 4 - Working with Dates (6-02).srt8.7KB
    📄 1 - 5 - Reading Local Files (4-55).srt6.5KB
  - 📄 2 - 3 - Reading from The Web (6-47).mp45.6MB
  - 📄 1 - 8 - Reading JSON (5-03).mp44.6MB
  - 📄 1 - 3 - Components of Tidy Data (9-25).mp47.6MB
  - 📄 3 - 7 - Merging Data (6-19).mp45.7MB
  - 📄 3 - 4 - Reshaping Data (9-13).mp47.2MB
  - 📄 4 - 2 - Regular Expressions I (5-16).mp44.1MB
  - 📄 4 - 5 - Data Resources (3-33).mp43MB
  - 📄 3 - 6 - Managing Data Frames with dplyr - Basic Tools.mp417.5MB
  - 📄 1 - 2 - Raw and Processed Data (7-07).mp45.9MB
  - 📄 3 - 2 - Summarizing Data (11-37).mp49.6MB
  - 📄 2 - 1 - Reading from MySQL (14-44).mp412.2MB
  - 📄 2 - 2 - Reading from HDF5 (6-45).mp45.5MB
  - 📄 1 - 6 - Reading Excel Files (3-55).mp43.5MB
  - 📄 1 - 1 - Obtaining Data Motivation (5-38).mp45MB
  - 📄 3 - 1 - Subsetting and Sorting (6-51).mp44.9MB
  - 📄 3 - 3 - Creating New Variables (10-32).mp48.5MB
  - 📄 1 - 5 - Reading Local Files (4-55).mp44.4MB
  - 📄 3 - 5 - Managing Data Frames with dplyr - Introduction.mp44.7MB
  - 📄 2 - 5 - Reading From Other Sources (4-44).mp43.9MB
  - 📄 更多资源关注微信公众【虎猫365资源库】.jpg115KB
  - 📄 1 - 1 - Obtaining Data Motivation (5-38).srt8.7KB
  - 📄 4 - 4 - Working with Dates (6-02).mp44.7MB
  - 📄 1 - 7 - Reading XML (12-39).mp411.5MB
  - 📄 4 - 1 - Editing Text Variables (10-46).mp49MB
  - 📄 4 - 3 - Regular Expressions II (8-00).mp46.5MB
  - 📄 1 - 9 - The data.table Package (11-18).mp48.9MB
  - 📄 1 - 4 - Downloading Files (7-09).mp45.9MB
  - 📄 2 - 4 - Reading From APIs (7-57).mp46.4MB
- 📁 004——（全31学时）.探索性数据分析 95 项
  - 📁 数据探索英文字幕 31 项
    📄 5 - 1 - Clustering Case Study [14-51].srt24.8KB
    📄 4 - 3 - Hierarchical Clustering (part 3) [7-34].srt13.3KB
    📄 2 - 2 - Principles of Analytic Graphics [12-11].srt21.6KB
    📄 3 - 4 - ggplot2 (part 2) [13-53].srt24.2KB
    📄 2 - 10 - Graphics Devices in R (part 2) [7-31].srt11.9KB
    📄 2 - 8 - Base Plotting Demonstration [16-56].srt24.7KB
    📄 4 - 4 - K-Means Clustering (part 1) [5-46].srt10.5KB
    📄 4 - 1 - Hierarchical Clustering (part 1) [7-21].srt13.3KB
    📄 2 - 7 - Base Plotting System (part 2) [6-56].srt11.3KB
    📄 2 - 4 - Exploratory Graphs (part 2) [5-13].srt9.1KB
    📄 4 - 2 - Hierarchical Clustering (part 2) [5-24].srt9.5KB
    📄 2 - 6 - Base Plotting System (part 1) [11-20].srt19.7KB
    📄 3 - 7 - ggplot2 (part 5) [8-11].srt14.3KB
    📄 4 - 10 - Working with Color in R Plots (part 2) [7-41].srt12.3KB
    📄 3 - 2 - Lattice Plotting System (part 2) [6-12].srt10.9KB
    📄 3 - 1 - Lattice Plotting System (part 1) [6-22].srt10.9KB
    📄 4 - 11 - Working with Color in R Plots (part 3) [6-39].srt11.8KB
    📄 2 - 1 - Introduction.srt2.5KB
    📄 3 - 3 - ggplot2 (part 1) [6-26].srt11.1KB
    📄 4 - 9 - Working with Color in R Plots (part 1) [4-08].srt6.8KB
    📄 2 - 9 - Graphics Devices in R (part 1) [5-34].srt9.9KB
    📄 2 - 5 - Plotting Systems in R [9-34].srt16.6KB
    📄 2 - 3 - Exploratory Graphs (part 1) [9-28].srt17.2KB
    📄 4 - 5 - K-Means Clustering (part 2) [4-26].srt7.6KB
    📄 5 - 2 - Air Pollution Case Study [40-35].srt61.6KB
    📄 4 - 8 - Dimension Reduction (part 3) [6-42].srt11.6KB
    📄 3 - 5 - ggplot2 (part 3) [9-47].srt16.9KB
    📄 3 - 6 - ggplot2 (part 4) [10-38].srt18.5KB
    📄 4 - 12 - Working with Color in R Plots (part 4) [3-35].srt5.8KB
    📄 4 - 7 - Dimension Reduction (part 2) [9-26].srt15.6KB
    📄 4 - 6 - Dimension Reduction (part 1) [7-55].srt13.1KB
  - 📁 数据探索中文字幕 31 项
    📄 4 - 4 - K-Means Clustering (part 1) [5-46].srt9KB
    📄 4 - 12 - Working with Color in R Plots (part 4) [3-35].srt4.6KB
    📄 3 - 2 - Lattice Plotting System (part 2) [6-12].srt9.3KB
    📄 3 - 3 - ggplot2 (part 1) [6-26].srt9.5KB
    📄 4 - 1 - Hierarchical Clustering (part 1) [7-21].srt10.8KB
    📄 3 - 1 - Lattice Plotting System (part 1) [6-22].srt9.3KB
    📄 2 - 2 - Principles of Analytic Graphics [12-11].srt18.2KB
    📄 2 - 8 - Base Plotting Demonstration [16-56].srt21.3KB
    📄 4 - 10 - Working with Color in R Plots (part 2) [7-41].srt10.2KB
    📄 4 - 11 - Working with Color in R Plots (part 3) [6-39].srt9.3KB
    📄 2 - 3 - Exploratory Graphs (part 1) [9-28].srt13.9KB
    📄 2 - 5 - Plotting Systems in R [9-34].srt14.2KB
    📄 2 - 9 - Graphics Devices in R (part 1) [5-34].srt8.1KB
    📄 2 - 10 - Graphics Devices in R (part 2) [7-31].srt10.4KB
    📄 4 - 9 - Working with Color in R Plots (part 1) [4-08].srt5.3KB
    📄 4 - 2 - Hierarchical Clustering (part 2) [5-24].srt7.5KB
    📄 3 - 7 - ggplot2 (part 5) [8-11].srt10.2KB
    📄 3 - 5 - ggplot2 (part 3) [9-47].srt14.4KB
    📄 5 - 1 - Clustering Case Study [14-51].srt20.6KB
    📄 4 - 3 - Hierarchical Clustering (part 3) [7-34].srt11.1KB
    📄 4 - 7 - Dimension Reduction (part 2) [9-26].srt13.4KB
    📄 4 - 8 - Dimension Reduction (part 3) [6-42].srt10KB
    📄 更多资源关注微信公众【虎猫365资源库】.jpg115KB
    📄 3 - 4 - ggplot2 (part 2) [13-53].srt20.1KB
    📄 2 - 6 - Base Plotting System (part 1) [11-20].srt15.9KB
    📄 4 - 6 - Dimension Reduction (part 1) [7-55].srt10.1KB
    📄 3 - 6 - ggplot2 (part 4) [10-38].srt15KB
    📄 2 - 7 - Base Plotting System (part 2) [6-56].srt9.3KB
    📄 4 - 5 - K-Means Clustering (part 2) [4-26].srt6.4KB
    📄 2 - 1 - Introduction.srt2.2KB
    📄 2 - 4 - Exploratory Graphs (part 2) [5-13].srt7.2KB
  - 📄 2 - 2 - Principles of Analytic Graphics [12-11].mp410.8MB
  - 📄 4 - 10 - Working with Color in R Plots (part 2) [7-41].mp45.5MB
  - 📄 3 - 3 - ggplot2 (part 1) [6-26].mp45.9MB
  - 📄 2 - 9 - Graphics Devices in R (part 1) [5-34].mp44.8MB
  - 📄 4 - 2 - Hierarchical Clustering (part 2) [5-24].mp44MB
  - 📄 2 - 8 - Base Plotting Demonstration [16-56].mp416MB
  - 📄 4 - 5 - K-Means Clustering (part 2) [4-26].mp42.9MB
  - 📄 4 - 11 - Working with Color in R Plots (part 3) [6-39].mp44.8MB
  - 📄 5 - 1 - Clustering Case Study [14-51].mp416.8MB
  - 📄 4 - 9 - Working with Color in R Plots (part 1) [4-08].mp43MB
  - 📄 4 - 1 - Hierarchical Clustering (part 1) [7-21].mp45MB
  - 📄 2 - 10 - Graphics Devices in R (part 2) [7-31].mp46.1MB
  - 📄 4 - 6 - Dimension Reduction (part 1) [7-55].mp45.9MB
  - 📄 2 - 1 - Introduction.mp44MB
  - 📄 4 - 12 - Working with Color in R Plots (part 4) [3-35].mp42.7MB
  - 📄 4 - 7 - Dimension Reduction (part 2) [9-26].mp47.1MB
  - 📄 3 - 5 - ggplot2 (part 3) [9-47].mp48.7MB
  - 📄 3 - 1 - Lattice Plotting System (part 1) [6-22].mp44.9MB
  - 📄 2 - 6 - Base Plotting System (part 1) [11-20].mp49.2MB
  - 📄 2 - 3 - Exploratory Graphs (part 1) [9-28].mp46.9MB
  - 📄 3 - 4 - ggplot2 (part 2) [13-53].mp418.4MB
  - 📄 2 - 5 - Plotting Systems in R [9-34].mp48.3MB
  - 📄 3 - 2 - Lattice Plotting System (part 2) [6-12].mp45MB
  - 📄 3 - 6 - ggplot2 (part 4) [10-38].mp49.8MB
  - 📄 4 - 8 - Dimension Reduction (part 3) [6-42].mp45.1MB
  - 📄 2 - 7 - Base Plotting System (part 2) [6-56].mp45.4MB
  - 📄 4 - 3 - Hierarchical Clustering (part 3) [7-34].mp45.4MB
  - 📄 4 - 4 - K-Means Clustering (part 1) [5-46].mp43.7MB
  - 📄 5 - 2 - Air Pollution Case Study [40-35].mp472MB
  - 📄 2 - 4 - Exploratory Graphs (part 2) [5-13].mp43.8MB
  - 📄 3 - 7 - ggplot2 (part 5) [8-11].mp47.3MB
- 📁 005——（全32学时）可重复性研究 33 项
  - 📄 3 - 2 - RPubs [3-21].mp45.2MB
  - 📄 2 - 7 - knitr (part 3) [4-46].mp46.1MB
  - 📄 4 - 2 - Case Study- Air Pollution [14-12].mp420.9MB
  - 📄 3 - 10 - Evidence-based Data Analysis (part 5) [7-56].mp49.3MB
  - 📄 3 - 11 - Introduction to Peer Assessment 2.mp41.1MB
  - 📄 1 - 8 - Organizing Your Analysis [11-05].mp414.1MB
  - 📄 3 - 5 - Reproducible Research Checklist (part 3) [6-54].mp48.9MB
  - 📄 2 - 9 - Introduction to Peer Assessment 1.mp48.4MB
  - 📄 3 - 7 - Evidence-based Data Analysis (part 2) [3-34].mp44.1MB
  - 📄 1 - 3 - Reproducible Research- Concepts and Ideas (part 2) [5-27].mp47.5MB
  - 📄 2 - 2 - Markdown [5-15].mp47.2MB
  - 📄 3 - 9 - Evidence-based Data Analysis (part 4) [4-47].mp45.5MB
  - 📄 1 - 6 - Structure of a Data Analysis (part 1) [12-29].mp414.9MB
  - 📄 1 - 7 - Structure of a Data Analysis (part 2) [17-41].mp421MB
  - 📄 2 - 4 - R Markdown Demonstration [7-24].mp410MB
  - 📄 1 - 9 - Use R version 3.1.1.mp42.4MB
  - 📄 更多资源关注微信公众【虎猫365资源库】.jpg115KB
  - 📄 2 - 6 - knitr (part 2) [4-11].mp45.4MB
  - 📄 3 - 3 - Reproducible Research Checklist (part 1) [8-22].mp411.1MB
  - 📄 4 - 3 - Case Study- High Throughput Biology [30-51].mp450.6MB
  - 📄 1 - 5 - Scripting Your Analysis [4-36].mp410.2MB
  - 📄 3 - 8 - Evidence-based Data Analysis (part 3) [4-25].mp44.9MB
  - 📄 3 - 6 - Evidence-based Data Analysis (part 1) [3-51].mp44.5MB
  - 📄 2 - 1 - Coding Standards in R [8-59].mp418.9MB
  - 📄 2 - 8 - knitr (part 4) [9-21].mp412.5MB
  - 📄 4 - 1 - Caching Computations [11-16].mp416.5MB
  - 📄 1 - 4 - Reproducible Research- Concepts and Ideas (part 3) [3-26].mp45MB
  - 📄 1 - 2 - Reproducible Research- Concepts and Ideas (part 1) [7-11].mp410.1MB
  - 📄 3 - 4 - Reproducible Research Checklist (part 2) [10-20].mp415.4MB
  - 📄 3 - 1 - Communicating Results [6-54].mp48.2MB
  - 📄 2 - 3 - R Markdown [6-35].mp47.9MB
  - 📄 2 - 5 - knitr (part 1) [7-05].mp49.5MB
  - 📄 1 - 1 - Introduction.mp45.9MB
- 📁 006——（全41学时）统计推断 41 项
  - 📄 4 - 1 - 11 01 Power (4-54).mp48MB
  - 📄 3 - 8 - 09 04 Two group testing (17-54).mp422.4MB
  - 📄 1 - 4 - 02 02 Probability mass functions (7-14).mp410.5MB
  - 📄 1 - 9 - 04 01 Expected values (5-14).mp48MB
  - 📄 2 - 4 - 05 04 Variance data example (3-33).mp45.6MB
  - 📄 3 - 3 - 08 03 Independent group T intervals (14-36).mp421.1MB
  - 📄 4 - 4 - 11 04 T test power (8-02).mp411.6MB
  - 📄 2 - 7 - 06 03 Poisson (6-08).mp49MB
  - 📄 1 - 6 - 03 01 Conditional Probability (3-23).mp46.1MB
  - 📄 9 - 1 - Just enough knitr to do the project.mp46.2MB
  - 📄 3 - 9 - 10 01 Pvalues (7-50).mp412.9MB
  - 📄 4 - 9 - 13 04 Permutation tests (9-07).mp411MB
  - 📄 2 - 3 - 05 03 Standard error of the mean (7-12).mp412.1MB
  - 📄 2 - 9 - 07 02 Asymptotics and the CLT (8-27).mp412.6MB
  - 📄 3 - 10 - 10 02 Pvalue further examples (5-54).mp49.2MB
  - 📄 1 - 7 - 03 02 Baye-'s rule (7-52).mp412.8MB
  - 📄 3 - 4 - 08 04 A note on unequal variance (3-29).mp44.8MB
  - 📄 4 - 8 - 13 03 Notes on the bootstrap (10-20).mp413.4MB
  - 📄 1 - 10 - 04 02 Expected values, simple examples (2-12).mp43.3MB
  - 📄 1 - 2 - Brief note on new materials.mp41.1MB
  - 📄 4 - 6 - 13 01 Bootstrapping (7-10).mp49.5MB
  - 📄 2 - 8 - 07 01 Asymptotics and LLN (4-28).mp46.9MB
  - 📄 3 - 7 - 09 03 T tests (7-04).mp48.7MB
  - 📄 3 - 1 - 08 01 T confidence intervals (9-12).mp411.8MB
  - 📄 4 - 3 - 11 03 Notes on power (4-57).mp47MB
  - 📄 1 - 5 - 02 03 Probability density functions (13-27).mp417.9MB
  - 📄 3 - 6 - 09 02 Example of choosing a rejection region (5-12).mp47.6MB
  - 📄 2 - 5 - 06 01 Binomial distrubtion (3-02).mp45.2MB
  - 📄 3 - 2 - 08 02 T confidence intervals example (4-06).mp45.1MB
  - 📄 2 - 1 - 05 01 Introduction to variability (4-57).mp47.3MB
  - 📄 4 - 2 - 11 02 Calculating Power (12-51).mp417.8MB
  - 📄 1 - 11 - 04 03 Expected values for PDFs (7-46).mp410.9MB
  - 📄 2 - 10 - 07 03 Asymptotics and confidence intervals (20-10).mp431.1MB
  - 📄 1 - 8 - 03 03 Independence (3-04).mp45.3MB
  - 📄 2 - 6 - 06 02 Normal distribution (15-12).mp423.4MB
  - 📄 4 - 5 - 12 Multiple Comparisons (25-22).mp430.5MB
  - 📄 4 - 7 - 13 02 Bootstrapping example (3-29).mp45.5MB
  - 📄 1 - 1 - 01 01 Introduction (7-05).mp414MB
  - 📄 1 - 3 - 02 01 Introduction to probability (6-13).mp49.1MB
  - 📄 3 - 5 - 09 01 Hypothesis testing (4-17).mp46.6MB
  - 📄 2 - 2 - 05 02 Variance simulation examples (2-46).mp43.2MB
- 📁 007——（全48学时）回归模型 48 项
  - 📄 1 - 3 - 01_01_c Least squares continued (5-38).mp47.5MB
  - 📄 3 - 5 - 02_03_b More simulation exercises (3-53).mp44.8MB
  - 📄 4 - 2 - 03_01_b GLM Examples (6-21).mp47.9MB
  - 📄 2 - 8 - 01_07_b T Tests for Regression Coefficients (12-33).mp416.3MB
  - 📄 4 - 5 - 03_02_b GLMs and Odds (14-03).mp417.6MB
  - 📄 1 - 8 - 01_03_b Linear Least Squares Special Cases (4-22).mp45.2MB
  - 📄 2 - 9 - 01_07_c Prediction Intervals (14-13).mp419MB
  - 📄 4 - 9 - 03_03_c Poisson Rate Models (12-53).mp415.8MB
  - 📄 4 - 7 - 03_03_a Poisson Regression (8-15).mp49.9MB
  - 📄 1 - 7 - 01_03_a Linear Least Squares (6-01).mp47.3MB
  - 📄 1 - 10 - 01_04_a Regression to the Mean (3-46).mp45MB
  - 📄 3 - 10 - 02_04_c Residuals and diagnostics examples (6-32).mp48.5MB
  - 📄 2 - 5 - 01_06_b Properties of Residuals (8-48).mp411MB
  - 📄 2 - 3 - 01_05_c Statistical Regression Models Examples (6-00).mp47.6MB
  - 📄 4 - 8 - 03_03_b Poisson Regression Example (14-12).mp417.8MB
  - 📄 3 - 6 - 02_03_c More simulation examples 2 (2-52).mp43.6MB
  - 📄 3 - 1 - 02_02_a Multivariable regression examples (14-38).mp419.5MB
  - 📄 2 - 10 - 02_01_a Multivariate Regression (2-47).mp43.7MB
  - 📄 3 - 2 - 02_02_b Dummy variables (27-08).mp435.2MB
  - 📄 1 - 2 - 01_01_b Basic least squares (5-41).mp47.2MB
  - 📄 2 - 1 - 01_05_a Statistical Linear Regression Models (5-58).mp47.4MB
  - 📄 1 - 9 - 01_03_c Linear Least Squares Solved (11-33).mp414.4MB
  - 📄 3 - 11 - 02_05_a Some thoughts on model selection (6-38).mp49.1MB
  - 📄 2 - 11 - 02_01_b Multivariable Least Squares (12-59).mp416.2MB
  - 📄 3 - 13 - 02_05_c Model comparison and search (8-05).mp411.1MB
  - 📄 4 - 11 - 03_04_b Fun Example (8-02).mp410MB
  - 📄 4 - 1 - 03_01_a Generalized Linear Models (2-32).mp43.3MB
  - 📄 1 - 5 - 01_02_a Basic Notation and Background (3-26).mp44.3MB
  - 📄 3 - 7 - 02_03_d Simulation examples finished (4-22).mp45.8MB
  - 📄 1 - 6 - 01_02_b Normalization and Correlation (5-22).mp46.8MB
  - 📄 2 - 13 - 02_01_d Multivariable Linear Models Interpretation (9-46).mp412.7MB
  - 📄 2 - 6 - 01_06_c Residual Variation (11-20).mp414.1MB
  - 📄 3 - 9 - 02_04_b More on diagnostics (5-18).mp47.6MB
  - 📄 3 - 3 - 02_02_c Interactions (26-29).mp434.4MB
  - 📄 3 - 8 - 02_04_a Residuals (4-48).mp46MB
  - 📄 4 - 3 - 03_01_c Variances and Quasi Likelihood (7-05).mp49MB
  - 📄 1 - 4 - 01_01_d Regression through the origin (7-37).mp49.7MB
  - 📄 4 - 10 - 03_04_a Fitting Functions (9-52).mp412.8MB
  - 📄 4 - 6 - 03_02_c More on Odds (12-29).mp415.3MB
  - 📄 2 - 2 - 01_05_b Interpreting Regression Coefficients (6-28).mp48.4MB
  - 📄 4 - 4 - 03_02_a Binary Data GLMs (7-11).mp48.9MB
  - 📄 1 - 11 - 01_04_b Regression to the Mean Example (10-46).mp413.9MB
  - 📄 2 - 12 - 02_01_c More Multivariable Least Squares (8-35).mp411.9MB
  - 📄 2 - 4 - 01_06_a Residuals (2-51).mp43.5MB
  - 📄 3 - 4 - 02_03_a Multivariable simulation exercises (5-42).mp47.5MB
  - 📄 3 - 12 - 02_05_b Variance inflation (10-33).mp413.3MB
  - 📄 2 - 7 - 01_07_a Inference in Regression (1-28).mp41.8MB
  - 📄 1 - 1 - 01_01_a Introduction to regression (4-10).mp45.5MB
- 📁 008——（全27学时）机器学习 28 项
  - 📄 2 - 6 - Covariate creation (17-31).mp422.8MB
  - 📄 2 - 3 - Training options (7-15).mp49MB
  - 📄 4 - 3 - Forecasting.mp410.6MB
  - 📄 1 - 6 - Types of errors (10-35).mp413.9MB
  - 📄 4 - 4 - Unsupervised Prediction (4-24).mp45.4MB
  - 📄 2 - 9 - Predicting with Regression Multiple Covariates (11-12).mp414.5MB
  - 📄 3 - 5 - Model Based Prediction (11-39).mp414.5MB
  - 📄 1 - 3 - Relative importance of steps (9-45).mp412.3MB
  - 📄 2 - 4 - Plotting predictors (10-39).mp414.2MB
  - 📄 2 - 2 - Data slicing (5-40).mp47MB
  - 📄 1 - 8 - Cross validation (8-20).mp410.1MB
  - 📄 3 - 3 - Random Forests (6-49).mp48.7MB
  - 📄 1 - 7 - Receiver Operating Characteristic (5-03).mp46.1MB
  - 📄 2 - 5 - Basic preprocessing (10-52).mp413.6MB
  - 📄 1 - 5 - Prediction study design (9-05).mp411.1MB
  - 📄 1 - 1 - Prediction motivation (8-26).mp410.5MB
  - 📄 3 - 2 - Bagging (9-13).mp411.4MB
  - 📄 更多资源关注微信公众【虎猫365资源库】.jpg115KB
  - 📄 2 - 7 - Preprocessing with principal components analysis (14-07).mp417.4MB
  - 📄 1 - 2 - What is prediction- (8-39).mp411MB
  - 📄 3 - 1 - Predicting with trees (12-51).mp416.2MB
  - 📄 1 - 9 - What data should you use- (6-01).mp47.8MB
  - 📄 3 - 4 - Boosting (7-08).mp49.1MB
  - 📄 2 - 1 - Caret package (6-16).mp48.2MB
  - 📄 1 - 4 - In and out of sample errors (6-57).mp48.7MB
  - 📄 2 - 8 - Predicting with Regression (12-22).mp415.8MB
  - 📄 4 - 2 - Combining predictors (7-11).mp49.3MB
  - 📄 4 - 1 - Regularized regression (13-20).mp416.8MB
- 📁 009——（全36学时）数据产品 37 项
  - 📄 4 - 3 - Building R Packages Demo (18-00).mp432MB
  - 📄 2 - 13 - Intro to rCharts and GoogleVis (1-01).mp41.9MB
  - 📄 4 - 2 - R Packages (Part 2) (14-59).mp417.1MB
  - 📄 2 - 14 - rCharts introduction (4-45).mp45.8MB
  - 📄 3 - 1 - Presenting Data Analysis Writing a Data Report (3-18).mp47.4MB
  - 📄 2 - 2 - Motivating Shiny (1-49).mp43.4MB
  - 📄 3 - 8 - RStudio Presenter 2 Authoring details (11-14).mp417.6MB
  - 📄 3 - 2 - Slidify intro (5-32).mp47.2MB
  - 📄 2 - 16 - rCharts mapping and discussion (5-32).mp48.4MB
  - 📄 2 - 3 - Shiny 1 Introduction to Shiny (8-36).mp410.9MB
  - 📄 2 - 1 - Introduction to Data Products (1-05).mp41.4MB
  - 📄 2 - 15 - rCharts more examples (5-40).mp47.6MB
  - 📄 2 - 8 - More advanced shiny discussion, reactivity (9-30).mp412.6MB
  - 📄 3 - 3 - Slidify working it out (2-01).mp43.4MB
  - 📄 3 - 5 - Slidify more details (7-24).mp49.3MB
  - 📄 3 - 6 - Slidify reminder about knitting R (1-52).mp43.3MB
  - 📄 3 - 9 - RStudio Presenter 3 Discussion and comparison with Slidify (4-13).mp45.7MB
  - 📄 2 - 6 - Shiny 4 Working with images (2-39).mp43.2MB
  - 📄 3 - 4 - Slidify customization (4-09).mp45.5MB
  - 📄 3 - 7 - RStudio Presenter 1 Introduction and getting started (4-59).mp48.6MB
  - 📄 4 - 7 - yhat (Part 2) (11-38).mp421.2MB
  - 📄 更多资源关注微信公众【虎猫365资源库】.jpg115KB
  - 📄 2 - 18 - shinyApps.io.mp45.8MB
  - 📄 4 - 4 - R Classes and Methods (Part 1) (13-50).mp418.1MB
  - 📄 2 - 19 - plotly.mp413.4MB
  - 📄 3 - 10 - Very quick introduction to gh-pages.mp410.1MB
  - 📄 2 - 7 - Shiny 5 Discussion (4-48).mp46.5MB
  - 📄 2 - 5 - Shiny 3 Creating a very basic prediction function (4-12).mp45.1MB
  - 📄 4 - 5 - R Classes and Methods (Part 2) (11-19).mp413.3MB
  - 📄 4 - 6 - yhat (Part 1) (24-39).mp440.1MB
  - 📄 2 - 17 - GoogleVis (9-34).mp412.4MB
  - 📄 2 - 12 - Manipulate (4-49).mp46.1MB
  - 📄 2 - 4 - Shiny 2 basic html and getting input (4-56).mp46MB
  - 📄 2 - 9 - More advanced shiny, the reactive function (5-50).mp46.8MB
  - 📄 4 - 1 - R Packages (Part 1) (7-11).mp49.1MB
  - 📄 2 - 11 - More advanced shiny, odds and ends (4-55).mp46.3MB
  - 📄 2 - 10 - More advanced shiny, conditional execution of reactive statements (4-16).mp45.4MB
- 📄 更多资源关注微信公众【虎猫365资源库】.jpg115KB
📁 008.中级教程（共30学时）——R(蔡-金融时间序列)初级班 258 项
- 📁 时间序列初级配套资料 226 项
  - 📁 金融时间序列分析与应用(初级班)除视频外资料 223 项
    📁 参考资料和讲义 22 项
    📁 主要讲义 3 项
    📄 补充讲义.pdf2.3MB
    📄 更多资源关注微信公众【虎猫365资源库】.jpg115KB
    📄 金融时间序列分析第二版.pdf4.7MB
    📁 R 基本知识 3 项
    📄 SPLUS&R培训教程（初级班）第一讲.pdf255KB
    📄 SPLUS&R培训视频教程（初级班）之第二讲.pdf332KB
    📄 R常见问题解答.pdf758KB
    📄 modelling Financial Time Series with S-PLUS.pdf5.6MB
    📄 Time series analysis and its applications with R examples.rar5.6MB
    📄 关于ADF与PP单位根检验方法的探讨.pdf92.9KB
    📄 R中使用GARCH.pdf87KB
    📄 ADF单位根检验中联合检验F统计量研究.pdf489KB
    📄 time series 指导小册.pdf459KB
    📄 更多资源关注微信公众【虎猫365资源库】.jpg115KB
    📄 多种单位根检验法的比较研究.pdf516KB
    📄 时间序列分析－蔡.rar1.8MB
    📄 Analysis of Integrated and Co-integrated Time Series with R.pdf1.8MB
    📄 times series with R.pdf386KB
    📄 Time series analysis and its applications with R examples.pdf6MB
    📄 单位根的DF_ADF检验与PP检验比较研究.pdf147KB
    📄 Time series.chm2.4MB
    📁 data 90 项
    📁 金融时间序列分析与应用(初级班)除视频外资料 15 项
    📁 金融时间序列分析与应用(初级班)除视频外资料 14 项
    📁 data 7 项
    📁 ch 2-3 线性时序和异方差模型 3 项
    📁 .Data 1 项
    📄 arch311.9KB
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    📁 ch1 时序特征 2 项
    📄 d-fxca00.txt19.7KB
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    📁 OX&G@ARCH42 4 项
    📁 Garch42 3 项
    📁 doc 1 项
    📄 default.htm2.1KB
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    📁 ch 2-3 线性时序和异方差模型 48 项
    📁 .Data 7 项
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    📄 m-ibm2698.txt9.3KB
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    📄 .Rhistory12.5KB
    📄 d-ibmvwewsp6202.txt577KB
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    📄 d-ibmvwewsp6203.txt592KB
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    📄 .RData402KB
    📄 m-ibm3dx2603.txt53KB
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    📄 q-jnj.txt655B
    📄 OxSeries.csv11.2KB
    📄 OxParameters.csv248B
    📄 d-sp8099.txt109KB
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    📄 sp5may.dat193KB
    📄 OxParameter.txt31B
    📄 OxResiduals.csv13.7KB
    📄 m-3m4603.txt14.9KB
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    📁 ch1 时序特征 23 项
    📄 d-c8603.txt93.1KB
    📄 d-msft8603.txt96.5KB
    📄 m-gs5.txt11.4KB
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    📄 w-tb3ms.dat45.6KB
    📄 d-3m6203.txt224KB
    📄 m-gs1.txt11.4KB
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    📄 d-intc7303.txt168KB
    📄 d-fxjp00.txt20.8KB
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    📄 d-3stock.txt103KB
    📄 m-c8603.txt4.4KB
    📄 w-tb6ms.dat40.9KB
    📄 d-fxca00.txt19.7KB
    📄 .RData458KB
    📄 d-fxuk00.txt18.7KB
    📄 Rplots.pdf681KB
    📄 m-fama-bond5203.txt37.8KB
    📄 m-gs10.txt11.4KB
    📄 .Rhistory12.4KB
    📄 d-fxeu00.txt18.7KB
    📄 EFAKeynoteFranklinAllen0406.ppt156KB
    📄 更多资源关注微信公众【虎猫365资源库】.jpg115KB
    📁 OX&G@ARCH42 92 项
    📁 Garch42 89 项
    📁 data 5 项
    📄 TXCH.xls451KB
    📄 cac40.bn739.2KB
    📄 nasdaq.xls231KB
    📄 cac40.in7317B
    📄 cac40.xls135KB
    📁 doc 49 项
    📁 Images 34 项
    📄 image.bmp15.4KB
    📄 initvalues2.gif14.2KB
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    📄 garchstart.html66.4KB
    📄 toolbar.html3KB
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    📄 garchintro.html14.4KB
    📄 body.css2.8KB
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    📁 Examples 26 项
    📁 Oxgauss 4 项
    📄 gaussprocs.src2.3KB
    📄 gaussprocs.h136B
    📄 GarchEstim.ox665B
    📄 更多资源关注微信公众【虎猫365资源库】.jpg115KB
    📄 VaR_insample.ox3KB
    📄 GarchEstim_Riskmetrics.ox4.3KB
    📄 Simul_Continuous_GARCH_RV.ox2.4KB
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    📄 GarchEstim_Modified.ox336B
    📄 UR_TESTS.ox358B
    📄 Stat_Constr_FIGARCH.ox2.8KB
    📄 Simul_Continuous_GARCH_Jumps.ox2.8KB
    📄 FFF.ox4.7KB
    📄 GarchEstim_Globals.ox503B
    📄 VaR_outofsample.ox3.6KB
    📄 Simul_Continuous_GARCH.ox2.7KB
    📄 Stat_Constr_GARCH.ox1.7KB
    📄 GarchEstim_Dated_Database.ox414B
    📄 Simul_Wiener.ox677B
    📄 GarchEstim.ox4.3KB
    📄 Stationarity_constr.ox1.7KB
    📄 Forecast.ox2.7KB
    📄 Simul_Garch.ox964B
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    📄 Garch.oxo641KB
    📄 Garch.h22.6KB
    📄 MBase2.oxo12.6KB
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    📄 MBase2.h283B
    📄 readmegarch42.txt6.5KB
    📄 更多资源关注微信公众【虎猫365资源库】.jpg115KB
    📄 oxcons510.exe4.4MB
    📁 R code 14 项
    📄 ch1.r2.6KB
    📄 garchOxFit安装方法.txt3.9KB
    📄 ch5 PCA&FCA.r5.5KB
    📄 factor.pca.R833B
    📄 Garch-splus.SSC1KB
    📄 mqtest.r536B
    📄 garchOxFit.r2.9KB
    📄 EACF.r1012B
    📄 ch2.r5.9KB
    📄 ch4.r2.9KB
    📄 bivariate cross-corelation.r444B
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    📄 ch3.r3.4KB
    📄 GarchOxModelling.r6.1KB
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  - 📄 更多资源关注微信公众【虎猫365资源库】.jpg115KB
  - 📄 时间序列初级课程介绍.txt2.4KB
- 📄 ch1-1资产收益率计算_Pak.wmv317MB
- 📄 ch2-6 单位根检验_Pak.wmv291MB
- 📄 ch4-1 弱平稳和交叉相关_Pak.wmv290MB
- 📄 ch3-1 条件异方差模型基本概念_Paa.wmv200MB
- 📄 ch3-1 条件异方差模型基本概念_Paak.wmv19.9MB
- 📄 ch3-2 ARCH模型原理_Pa.wmv212MB
- 📄 ch5-4 主成分分析及其在金融中的应用_Pak.wmv275MB
- 📄 ch3-4 GARCH模型与应用_Pa.wmv272MB
- 📄 ch2-1线性时间序列基本概念_Pak.wmv241MB
- 📄 ch5-3 基本面因子模型_Pak.wmv165MB
- 📄 ch5-1 单因子模型_Pak.wmv270MB
- 📄 ch4-3 VAR模型原理_Pak.wmv212MB
- 📄 ch1-4习题案例分析_Pak.wmv116MB
- 📄 ch3-5 IGARCH&GARCH-M应用_Pa.wmv149MB
- 📄 ch4-5 脉冲相应函数_Pak.wmv127MB
- 📄 ch4-2 多元混成检验_Pak.wmv117MB
- 📄 更多资源关注微信公众【虎猫365资源库】.jpg115KB
- 📄 ch2-8时序误差及长记忆模型应用_Pak.wmv200MB
- 📄 ch2-4 MA模型与应用_Pak.wmv202MB
- 📄 ch1-2收益率分布特征_Pak.wmv224MB
- 📄 ch2-3 AR模型参数估计与应用_Pak.wmv202MB
- 📄 ch1-3收益率分布应用_Pak.wmv252MB
- 📄 ch2-2 AR模型原理_Pak.wmv220MB
- 📄 ch5-5 因子分析原理_Pak.wmv203MB
- 📄 ch4-4 VAR案例分析_Pak.wmv264MB
- 📄 ch3-6 EGARCH模型与应用_Pa.wmv184MB
- 📄 ch3-7 TGARCH模型与应用_Pak.wmv122MB
- 📄 ch3-3 ARCH模型应用分析_Pa.wmv231MB
- 📄 ch2-7 季节模型与应用_Pak.wmv220MB
- 📄 ch2-5 ARMA模型与应用_Pak.wmv243MB
- 📄 ch5-2 多因子模型_Pak.wmv89.8MB
📁 011.中级教程（共44学时）——Econometrics+in+R视频 44 项
- 📄 R31. Logistic regression in R.mp416.6MB
- 📄 R43. R Programming- Variables - YouTube.mp423.9MB
- 📄 R37. Simple Linear Regression in R.mp418.3MB
- 📄 R8_ Line plots (Econometrics in R).mp414.1MB
- 📄 R20. Confidence intervals on means in R - YouTube.mp415MB
- 📄 R24. Hypothesis Tests on Means in R (updated) - YouTube.mp418.3MB
- 📄 R36. Random Number Generation in R - YouTube.mp413.8MB
- 📄 R23. Correlation in R - YouTube.mp419.8MB
- 📄 R26. Hypothesis tests on proportions in R (updated) - YouTube.mp413.3MB
- 📄 R17. ANOVA in R - YouTube.mp414.9MB
- 📄 R4. Running a regression (Econometrics in R).mp423.3MB
- 📄 R13. Statistical Power (Econometrics in R).mp419.7MB
- 📄 R18. Assessing Normality in R - YouTube.mp419.4MB
- 📄 R10_ How to Bootstrap. The case of R-squared (Econometrics i.mp427.6MB
- 📄 R11. Shading Under a Bell Curve (Econometrics in R).mp422.5MB
- 📄 R38. Test for Constant Variance in ANOVA using R - YouTube.mp411.5MB
- 📄 R16. Panels and Clustering in R (Econometrics in R).mp425.9MB
- 📄 R30. Introduction to Lists in R - YouTube.mp414.3MB
- 📄 R42. R Programming- Data Frames - YouTube.mp457.1MB
- 📄 R22. Confidence on Proportions in R (updated) - YouTube.mp48.4MB
- 📄 R14. Data Creation (Econometrics in R).mp432.1MB
- 📄 R3. Tutorial on Distributions (Econometrics in R).mp431MB
- 📄 R9. IV Regression (Econometrics in R).mp412.8MB
- 📄 R1. R Tutorial on the data frame (Econometrics in R).mp426.5MB
- 📄 R12. Robust_White Standard Errors. (Econometrics in R).mp410.8MB
- 📄 R29. Introduction to Functions in R - YouTube.mp418.9MB
- 📄 R44. R Programming- Vectors - YouTube.mp415.4MB
- 📄 R7. Scatter plots (Econometrics in R).mp420.2MB
- 📄 R15. Merging Multiple Data Frames (Econometrics in R).mp414.1MB
- 📄 R41. Reasons to learn the R Programming Language - YouTube.mp432.7MB
- 📄 R5. Regressions with Categorical Explanatory Variables (Econ.mp415.9MB
- 📄 R28. Introduction to ARIMA modeling in R - YouTube.mp421.1MB
- 📄 R25. Hypothesis tests on means in R - YouTube.mp49.8MB
- 📄 R6. Testing Multiple Linear Hypotheses (Econometrics in R).mp422.1MB
- 📄 R33. Non Parametric Statistics in R - YouTube.mp415.7MB
- 📄 R40. R Programming- Arithmetic Operations - YouTube.mp419.1MB
- 📄 R21. Confidence intervals on proportions in R - YouTube.mp410.9MB
- 📄 R34. PCA in R - YouTube.mp416.8MB
- 📄 R27. Hypothesis tests on proportions in R - YouTube.mp420.1MB
- 📄 R2. Reading Stata files and Data Manipulation (Econometrics -1.mp433.1MB
- 📄 R39. Working with Probability Distributions in R - YouTube.mp425MB
- 📄 R19. Breuch-Pagan test in R.mp48.4MB
- 📄 R32. MANOVA in R.mp425.5MB
- 📄 R35. Plotting in R_ Part II.mp420.4MB
📁 016.高级教程（共15学时）——R语言七种武器之ggplot2 38 项
- 📁 课程资料 21 项
  - 📄 3.txt1.2KB
  - 📄 GG05.pdf1.1MB
  - 📄 lesson8.txt3.3KB
  - 📄 GG05.rar87.1MB
  - 📄 GG03.rar109MB
  - 📄 GG04.rar56.6MB
  - 📄 ggplot2 Elegant Graphics for Data Analysis.PDF10.3MB
  - 📄 更多资源关注微信公众【虎猫365资源库】.jpg115KB
  - 📄 GG01.rar77.9MB
  - 📄 The_Grammar_of_Graphics.part2.rar2.7MB
  - 📄 GG02.pdf1.3MB
  - 📄 4-5_1.txt1.9KB
  - 📄 GG01.pdf1.5MB
  - 📄 The Grammar of Graphics 2nd ed - L. Wilkinson (Springer, 2005) WW.pdf13.4MB
  - 📄 GG04.pdf937KB
  - 📄 GG03.pdf1.6MB
  - 📄 1_all.txt1.6KB
  - 📄 GG02.rar64.5MB
  - 📄 The_Grammar_of_Graphics.part1.rar9.4MB
  - 📄 ggplot2_Elegant_Graphics_for_Data_Analysis.rar7.3MB
  - 📄 2.txt429B
- 📄 GG01a.mp485.2MB
- 📄 GG01c.mp482.5MB
- 📄 GG02b.mp479.2MB
- 📄 GG03a.mp486.7MB
- 📄 GG03c.mp472.1MB
- 📄 GG05a.mp492.9MB
- 📄 GG04b.mp450MB
- 📄 GG03b.mp468.1MB
- 📄 GG04c.mp453.7MB
- 📄 GG05b.mp4121MB
- 📄 GG04a.mp454MB
- 📄 GG02a.mp473.1MB
- 📄 更多资源关注微信公众【虎猫365资源库】.jpg115KB
- 📄 GG03d.mp494.3MB
- 📄 GG02c.mp455.6MB
- 📄 GG01b.mp4104MB
📁 018.高级教程（共17学时）——R语言统计分析软件简明教程初级篇 23 项
- 📁 R的课堂笔记整理（英） 4 项
  - 📁 R资料 3 项
    📄 R语言简介.pdf541KB
    📄 Programming with R.pdf7.4MB
    📄 更多资源关注微信公众【虎猫365资源库】.jpg115KB
- 📄 第05讲参数估计_Pak.wmv290MB
- 📄 第08讲方差分析.wmv341MB
- 📄 第06讲假设检验1_Pak.wmv301MB
- 📄 第04讲数据探索性分析3_Pak.wmv108MB
- 📄 第07讲回归分析_Pak.wmv292MB
- 📄 第04讲数据探索性分析2_Pak.wmv240MB
- 📄 第02讲数据对象与运算2_Pak.wmv246MB
- 📄 第06讲假设检验2_Pak.wmv187MB
- 📄 第09讲非参数检验_Pak.wmv237MB
- 📄 第04讲数据探索性分析1_Pak.wmv122MB
- 📄 更多资源关注微信公众【虎猫365资源库】.jpg115KB
- 📄 第01讲 SPLUS&R介绍基本使用1_Pak.wmv179MB
- 📄 第10讲统计案例综合分析1_Pak.wmv174MB
- 📄 第03讲统计模拟_Pak.wmv150MB
- 📄 第02讲数据对象与运算（函数、循环）3_Pak.wmv244MB
- 📄 第10讲统计案例综合分析2_Pak.wmv136MB
- 📄 第02讲数据对象与运算1_Pak.wmv243MB
- 📄 第01讲 SPLUS&R介绍与基本使用2_Pak.wmv266MB
📁 020高级教程（共55学时）——R语言编程教程（中文字幕） 56 项
- 📄 35、03_Week_2 07_Functions_part_1_9-17_20170325141027.mp472.7MB
- 📄 42、04_Week_3 01_Loop_Functions_-_lapply_9-23_20170325123051.mp452.6MB
- 📄 33、03_Week_2 05_Control_Structures_-_Repeat_Next_Break_4-57_20170329234709.mp426.3MB
- 📄 31、03_Week_2 02_Control_Structures_-_If-else_1-58_20170325034920.mp48.9MB
- 📄 50、05_Week_4 01_The_str_Function_6-08_20170325040610.mp4102MB
- 📄 10、02_Week_1 04_R_Console_Input_and_Evaluation_4-46.mp429.7MB
- 📄 46、04_Week_3 05_Loop_Functions_-_split_9-09_20170325131356.mp461.3MB
- 📄 6、05_Writing_Code_-_Setting_Your_Working_Directory_Mac.mp4170MB
- 📄 18、02_Week_1 12_Data_Types_-_Summary_0-43.mp44.6MB
- 📄 3、02_Installing_R_on_Windows_3.2.1.mp432.9MB
- 📄 38、03_Week_2 10_Scoping_Rules_-_R_Scoping_Rules_8-34_20170402160650.mp452.6MB
- 📄 27、02_Week_1 21_Subsetting_-_Removing_Missing_Values_20170329232325.mp426.1MB
- 📄 34、03_Week_2 06_Your_First_R_Function_10-29_20170325142552.mp4228MB
- 📄 12、02_Week_1 06_Data_Types_-_Vectors_and_Lists_6-27.mp441.3MB
- 📄 36、03_Week_2 08_Functions_part_2_7-13_20170325140846.mp449.7MB
- 📄 47、04_Week_3 06_Debugging_Tools_-_Diagnosing_the_Problem_12-33_20170325131926.mp486.3MB
- 📄 45、04_Week_3 04_Loop_Functions_-_tapply_3-17_20170325130054.mp421.2MB
- 📄 15、02_Week_1 09_Data_Types_-_Missing_Values_2-10.mp413.8MB
- 📄 51、05_Week_4 02_Simulation_-_Generating_Random_Numbers_7-47_20170325040441.mp458.7MB
- 📄 37、03_Week_2 09_Scoping_Rules_-_Symbol_Binding_10-32_20170325140512.mp499.7MB
- 📄 14、02_Week_1 08_Data_Types_-_Factors_4-31.mp429.4MB
- 📄 19、02_Week_1 13_Reading_Tabular_Data_5-51.mp459.2MB
- 📄 7、02_Week_1 01_Introduction.mp457.1MB
- 📄 9、02_Week_1 03_Getting_Help_13-53.mp482.5MB
- 📄 20、02_Week_1 14_Reading_Large_Tables_7-08.mp466.6MB
- 📄 32、03_Week_2 04_Control_Structures_-_While_loops_3-22_20170329234532.mp418.4MB
- 📄 26、02_Week_1 20_Subsetting_-_Partial_Matching_20170329232243.mp49.5MB
- 📄 41、03_Week_2 13_Dates_and_Times_10-29_20170329235752.mp468.1MB
- 📄 1、03_Week_2 03_Control_Structures_-_For_loops_4-25_20170325035005.mp422.8MB
- 📄 28、02_Week_1 22_Vectorized_Operations_3-46_20170329232712.mp432.1MB
- 📄 23、02_Week_1 17_Subsetting_-_Basics_20170329230745.mp429.2MB
- 📄 21、02_Week_1 15_Textual_Data_Formats_4-58_20170329230328.mp447.6MB
- 📄 30、03_Week_2 01_Control_Structures_-_Introduction_0-54_20170325034857.mp48.5MB
- 📄 8、02_Week_1 02_Overview_and_History_of_R_16-07.mp4146MB
- 📄 4、03_Installing_R_Studio_Mac.mp436.4MB
- 📄 29、02_Week_1 23_Introduction_to_swirl.mp446.1MB
- 📄 17、02_Week_1 11_Data_Types_-_Names_Attribute_1-49.mp49.1MB
- 📄 16、02_Week_1 10_Data_Types_-_Data_Frames_2-44.mp424.8MB
- 📄 53、05_Week_4 04_Simulation_-_Random_Sampling_2-37_20170325040204.mp420.5MB
- 📄 22、02_Week_1 16_Connections-_Interfaces_to_the_Outside_World_4-35.mp434.6MB
- 📄 5、04_Writing_Code_-_Setting_Your_Working_Directory_Windows.mp476.9MB
- 📄 40、03_Week_2 12_Coding_Standards_8-59_20170329235018.mp4287MB
- 📄 24、02_Week_1 18_Subsetting_-_Lists_20170329231250.mp426.8MB
- 📄 更多资源关注微信公众【虎猫365资源库】.jpg115KB
- 📄 49、04_Week_3 08_Debugging_Tools_-_Using_the_Tools_8-21_20170330000422.mp448.9MB
- 📄 55、05_Week_4 06_R_Profiler_part_2_10-26_20170325035142.mp4163MB
- 📄 43、04_Week_3 02_Loop_Functions_-_apply_7-21_20170325123325.mp454.4MB
- 📄 11、02_Week_1 05_Data_Types_-_R_Objects_and_Attributes_4-43.mp434.1MB
- 📄 54、05_Week_4 05_R_Profiler_part_1_10-39_20170325035413.mp4119MB
- 📄 25、02_Week_1 19_Subsetting_-_Matrices_20170329232017.mp419.5MB
- 📄 13、02_Week_1 07_Data_Types_-_Matrices_3-24.mp418.7MB
- 📄 39、03_Week_2 11_Scoping_Rules_-_Optimization_Example_OPTIONAL_9-21_20170325134423.mp471.4MB
- 📄 48、04_Week_3 07_Debugging_Tools_-_Basic_Tools_6-25_20170325132410.mp481.3MB
- 📄 2、01_Installing_R_on_a_Mac_3.2.1.mp444.3MB
- 📄 44、04_Week_3 03_Loop_Functions_-_mapply_4-46_20170329224215.mp434.5MB
- 📄 52、05_Week_4 03_Simulation_-_Simulating_a_Linear_Model_4-31_20170325040330.mp437.8MB
📁 021高级教程（共16学时）——边学边教R语言 17 项
- 📄 阿雷边学边教R语言第08期—分组数据处理.mp435.1MB
- 📄 阿雷边学边教R语言第03期—导入与导出数据.mp445.2MB
- 📄 阿雷边学边教R语言第05期—排序和选取子集.mp442.4MB
- 📄 阿雷边学边教R语言第06期—重命名和数据组合.mp490.3MB
- 📄 阿雷边学边教R语言第14期统计篇—参数估计和假设检验.mp4122MB
- 📄 阿雷边学边教R语言第01期—使用R和R的语法.mp492.4MB
- 📄 阿雷边学边教R语言第10期—用ggplot2作图.mp4235MB
- 📄 阿雷边学边教R语言第02期—数据结构.mp492.3MB
- 📄 阿雷边学边教R语言第16期—方差分析.mp4107MB
- 📄 阿雷边学边教R语言第12期统计篇—描述性统计.mp434.4MB
- 📄 阿雷边学边教R语言第07期—apply家族函数.mp457.8MB
- 📄 阿雷边学边教R语言第04期—数据框常用操作.mp448.8MB
- 📄 阿雷边学边教R语言第13期统计篇—正态分布和抽样分布.mp4209MB
- 📄 更多资源关注微信公众【虎猫365资源库】.jpg115KB
- 📄 阿雷边学边教R语言第15期统计篇—t检验.mp465.7MB
- 📄 阿雷边学边教R语言第11期统计篇—常用的2种抽样方法.mp4248MB
- 📄 阿雷边学边教R语言第09期—缺失值处理和转换函数.mp436.7MB

R语言全栈学习合集：从入门到数据科学（视频+字幕+课件）

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