约翰霍普金斯大学数据科学家专项课程视频教程中英字幕

<约翰霍普金斯大学数据科学家专项课程>
├<1.数据科学家的宝箱>
│  ├1 - 1 - Series Motivation (12-03).mp4
│  ├1 - 10 - Regression Models Overview (1-46).mp4
│  ├1 - 11 - Practical Machine Learning Overview (1-31).mp4
│  ├1 - 12 - Building Data Products Overview (1-19).mp4
│  ├1 - 13 - Installing R on Windows (3-20) {Roger Peng}.mp4
│  ├1 - 14 - Install R on a Mac (2-02) {Roger Peng}.mp4
│  ├1 - 15 - Installing Rstudio (1-36) {Roger Peng}.mp4
│  ├1 - 2 - The Data Scientist-'s Toolbox (5-09).mp4
│  ├1 - 3 - Getting Help (8-52).mp4
│  ├1 - 4 - Finding Answers (4-35).mp4
│  ├1 - 5 - R Programming Overview (2-12).mp4
│  ├1 - 6 - Getting Data Overview (1-34).mp4
│  ├1 - 7 - Exploratory Data Analysis Overview (1-21).mp4
│  ├1 - 8 - Reproducible Research Overview (1-27).mp4
│  ├1 - 9 - Statistical Inference Overview (1-06).mp4
│  ├2 - 1 - Tips from Coursera Users - Optional Video (3-53).mp4
│  ├2 - 2 - Command Line Interface (16-04).mp4
│  ├2 - 3 - Introduction to Git (4-49).mp4
│  ├2 - 4 - Introduction to Github (3-53).mp4
│  ├2 - 5 - Creating a Github Repository (5-51).mp4
│  ├2 - 6 - Basic Git Commands (5-52).mp4
│  ├2 - 7 - Basic Markdown (2-22).mp4
│  ├2 - 8 - Installing R Packages (5-37).mp4
│  ├2 - 9 - Installing Rtools (2-29).mp4
│  ├3 - 1 - Types of Questions (9-09).mp4
│  ├3 - 2 - What is Data- (5-15).mp4
│  ├3 - 3 - What About Big Data- (4-15).mp4
│  ├3 - 4 - Experimental Design (15-59).mp4
│  ├<1.数据科学家的宝箱英文字幕>
│  │  ├1 - 1 - Series Motivation (12-03).srt
│  │  ├1 - 10 - Regression Models Overview (1-46).srt
│  │  ├1 - 11 - Practical Machine Learning Overview (1-31).srt
│  │  ├1 - 12 - Building Data Products Overview (1-19).srt
│  │  ├1 - 13 - Installing R on Windows (3-20) {Roger Peng}.srt
│  │  ├1 - 14 - Install R on a Mac (2-02) {Roger Peng}.srt
│  │  ├1 - 15 - Installing Rstudio (1-36) {Roger Peng}.srt
│  │  ├1 - 2 - The Data Scientist-'s Toolbox (5-09).srt
│  │  ├1 - 3 - Getting Help (8-52).srt
│  │  ├1 - 4 - Finding Answers (4-35).srt
│  │  ├1 - 5 - R Programming Overview (2-12).srt
│  │  ├1 - 6 - Getting Data Overview (1-34).srt
│  │  ├1 - 7 - Exploratory Data Analysis Overview (1-21).srt
│  │  ├1 - 8 - Reproducible Research Overview (1-27).srt
│  │  ├1 - 9 - Statistical Inference Overview (1-06).srt
│  │  ├2 - 2 - Command Line Interface (16-04).srt
│  │  ├2 - 3 - Introduction to Git (4-49).srt
│  │  ├2 - 4 - Introduction to Github (3-53).srt
│  │  ├2 - 5 - Creating a Github Repository (5-51).srt
│  │  ├2 - 6 - Basic Git Commands (5-52).srt
│  │  ├2 - 7 - Basic Markdown (2-22).srt
│  │  ├2 - 8 - Installing R Packages (5-37).srt
│  │  ├2 - 9 - Installing Rtools (2-29).srt
│  │  ├3 - 1 - Types of Questions (9-09).srt
│  │  ├3 - 2 - What is Data- (5-15).srt
│  │  ├3 - 3 - What About Big Data- (4-15).srt
│  │  └3 - 4 - Experimental Design (15-59).srt
│  ├<1.数据科学家的宝箱中文字幕>
│  │  ├1 - 1 - Series Motivation (12-03).srt
│  │  ├1 - 10 - Regression Models Overview (1-46).srt
│  │  ├1 - 11 - Practical Machine Learning Overview (1-31).srt
│  │  ├1 - 12 - Building Data Products Overview (1-19).srt
│  │  ├1 - 13 - Installing R on Windows (3-20) {Roger Peng}.srt
│  │  ├1 - 14 - Install R on a Mac (2-02) {Roger Peng}.srt
│  │  ├1 - 15 - Installing Rstudio (1-36) {Roger Peng}.srt
│  │  ├1 - 2 - The Data Scientist-'s Toolbox (5-09).srt
│  │  ├1 - 3 - Getting Help (8-52).srt
│  │  ├1 - 4 - Finding Answers (4-35).srt
│  │  ├1 - 5 - R Programming Overview (2-12).srt
│  │  ├1 - 6 - Getting Data Overview (1-34).srt
│  │  ├1 - 7 - Exploratory Data Analysis Overview (1-21).srt
│  │  ├1 - 8 - Reproducible Research Overview (1-27).srt
│  │  ├1 - 9 - Statistical Inference Overview (1-06).srt
│  │  ├2 - 2 - Command Line Interface (16-04).srt
│  │  ├2 - 3 - Introduction to Git (4-49).srt
│  │  ├2 - 4 - Introduction to Github (3-53).srt
│  │  ├2 - 5 - Creating a Github Repository (5-51).srt
│  │  ├2 - 6 - Basic Git Commands (5-52).srt
│  │  ├2 - 7 - Basic Markdown (2-22).srt
│  │  ├2 - 8 - Installing R Packages (5-37).srt
│  │  ├2 - 9 - Installing Rtools (2-29).srt
│  │  ├3 - 1 - Types of Questions (9-09).srt
│  │  ├3 - 2 - What is Data- (5-15).srt
│  │  ├3 - 3 - What About Big Data- (4-15).srt
│  │  └3 - 4 - Experimental Design (15-59).srt
├<2.R语言编程（英文）>
│  ├2 - 1 - Introduction.mp4
│  ├2 - 1 - Introduction.srt
│  ├2 - 1 - Introduction_zh.srt
│  ├2 - 10 - Data Types - Data Frames [2-44].mp4
│  ├2 - 10 - Data Types - Data Frames [2-44].srt
│  ├2 - 11 - Data Types - Names Attribute [1-49].mp4
│  ├2 - 11 - Data Types - Names Attribute [1-49].srt
│  ├2 - 12 - Data Types - Summary [0-43].mp4
│  ├2 - 12 - Data Types - Summary [0-43].srt
│  ├2 - 13 - Reading Tabular Data [5-51].mp4
│  ├2 - 13 - Reading Tabular Data [5-51].srt
│  ├2 - 14 - Reading Large Tables [7-08].mp4
│  ├2 - 14 - Reading Large Tables [7-08].srt
│  ├2 - 15 - Textual Data Formats [4-58].mp4
│  ├2 - 15 - Textual Data Formats [4-58].srt
│  ├2 - 16 - Connections- Interfaces to the Outside World [4-35].mp4
│  ├2 - 16 - Connections- Interfaces to the Outside World [4-35].srt
│  ├2 - 17 - Subsetting - Basics.mp4
│  ├2 - 17 - Subsetting - Basics.srt
│  ├2 - 18 - Subsetting - Lists.mp4
│  ├2 - 18 - Subsetting - Lists.srt
│  ├2 - 19 - Subsetting - Matrices.mp4
│  ├2 - 19 - Subsetting - Matrices.srt
│  ├2 - 2 - Overview and History of R [16-07].mp4
│  ├2 - 2 - Overview and History of R [16-07].srt
│  ├2 - 20 - Subsetting - Partial Matching.mp4
│  ├2 - 20 - Subsetting - Partial Matching.srt
│  ├2 - 21 - Subsetting - Removing Missing Values.mp4
│  ├2 - 21 - Subsetting - Removing Missing Values.srt
│  ├2 - 22 - Vectorized Operations [3-46].mp4
│  ├2 - 22 - Vectorized Operations [3-46].srt
│  ├2 - 23 - Introduction to swirl.mp4
│  ├2 - 23 - Introduction to swirl.srt
│  ├2 - 3 - Getting Help [13-53].mp4
│  ├2 - 3 - Getting Help [13-53].srt
│  ├2 - 4 - R Console Input and Evaluation [4-46].mp4
│  ├2 - 4 - R Console Input and Evaluation [4-46].srt
│  ├2 - 5 - Data Types - R Objects and Attributes [4-43].mp4
│  ├2 - 5 - Data Types - R Objects and Attributes [4-43].srt
│  ├2 - 6 - Data Types - Vectors and Lists [6-27].mp4
│  ├2 - 6 - Data Types - Vectors and Lists [6-27].srt
│  ├2 - 7 - Data Types - Matrices [3-24].mp4
│  ├2 - 7 - Data Types - Matrices [3-24].srt
│  ├2 - 8 - Data Types - Factors [4-31].mp4
│  ├2 - 8 - Data Types - Factors [4-31].srt
│  ├2 - 9 - Data Types - Missing Values [2-10].mp4
│  ├2 - 9 - Data Types - Missing Values [2-10].srt
│  ├3 - 1 - Control Structures - Introduction [0-54].mp4
│  ├3 - 1 - Control Structures - Introduction [0-54].srt
│  ├3 - 10 - Scoping Rules - R Scoping Rules [8-34].mp4
│  ├3 - 10 - Scoping Rules - R Scoping Rules [8-34].srt
│  ├3 - 11 - Scoping Rules - Optimization Example (OPTIONAL) [9-21].mp4
│  ├3 - 11 - Scoping Rules - Optimization Example (OPTIONAL) [9-21].srt
│  ├3 - 12 - Coding Standards [8-59].mp4
│  ├3 - 12 - Coding Standards [8-59].srt
│  ├3 - 13 - Dates and Times [10-29].mp4
│  ├3 - 13 - Dates and Times [10-29].srt
│  ├3 - 2 - Control Structures - If-else [1-58].mp4
│  ├3 - 2 - Control Structures - If-else [1-58].srt
│  ├3 - 3 - Control Structures - For loops [4-25].mp4
│  ├3 - 3 - Control Structures - For loops [4-25].srt
│  ├3 - 4 - Control Structures - While loops [3-22].mp4
│  ├3 - 4 - Control Structures - While loops [3-22].srt
│  ├3 - 5 - Control Structures - Repeat, Next, Break [4-57].mp4
│  ├3 - 5 - Control Structures - Repeat, Next, Break [4-57].srt
│  ├3 - 6 - Your First R Function [10-29].mp4
│  ├3 - 6 - Your First R Function [10-29].srt
│  ├3 - 7 - Functions (part 1) [9-17].mp4
│  ├3 - 7 - Functions (part 1) [9-17].srt
│  ├3 - 8 - Functions (part 2) [7-13].mp4
│  ├3 - 8 - Functions (part 2) [7-13].srt
│  ├3 - 9 - Scoping Rules - Symbol Binding [10-32].mp4
│  ├3 - 9 - Scoping Rules - Symbol Binding [10-32].srt
│  ├4 - 1 - Loop Functions - lapply [9-23].mp4
│  ├4 - 1 - Loop Functions - lapply [9-23].srt
│  ├4 - 2 - Loop Functions - apply [7-21].mp4
│  ├4 - 2 - Loop Functions - apply [7-21].srt
│  ├4 - 3 - Loop Functions - mapply [4-46].mp4
│  ├4 - 3 - Loop Functions - mapply [4-46].srt
│  ├4 - 4 - Loop Functions - tapply [3-17].mp4
│  ├4 - 4 - Loop Functions - tapply [3-17].srt
│  ├4 - 5 - Loop Functions - split [9-09].mp4
│  ├4 - 5 - Loop Functions - split [9-09].srt
│  ├4 - 6 - Debugging Tools - Diagnosing the Problem [12-33].mp4
│  ├4 - 6 - Debugging Tools - Diagnosing the Problem [12-33].srt
│  ├4 - 7 - Debugging Tools - Basic Tools [6-25].mp4
│  ├4 - 7 - Debugging Tools - Basic Tools [6-25].srt
│  ├4 - 8 - Debugging Tools - Using the Tools [8-21].mp4
│  ├4 - 8 - Debugging Tools - Using the Tools [8-21].srt
│  ├5 - 1 - The str Function [6-08].mp4
│  ├5 - 1 - The str Function [6-08].srt
│  ├5 - 2 - Simulation - Generating Random Numbers [7-47].mp4
│  ├5 - 2 - Simulation - Generating Random Numbers [7-47].srt
│  ├5 - 3 - Simulation - Simulating a Linear Model [4-31].mp4
│  ├5 - 3 - Simulation - Simulating a Linear Model [4-31].srt
│  ├5 - 4 - Simulation - Random Sampling [2-37].mp4
│  ├5 - 4 - Simulation - Random Sampling [2-37].srt
│  ├5 - 5 - R Profiler (part 1) [10-39].mp4
│  ├5 - 5 - R Profiler (part 1) [10-39].srt
│  ├5 - 6 - R Profiler (part 2) [10-26].mp4
│  └5 - 6 - R Profiler (part 2) [10-26].srt
├<2.R语言编程（中文）>
│  ├1 - 1 - 在Windows上安装R.mp4
│  ├1 - 1 - 在Windows上安装R.srt
│  ├1 - 2 - 在Mac上安装R.mp4
│  ├1 - 2 - 在Mac上安装R.srt
│  ├1 - 3 - 安装R Studio (Mac).mp4
│  ├1 - 3 - 安装R Studio (Mac).srt
│  ├1 - 4 - 写代码- 建立你的工作目录 (Windows).mp4
│  ├1 - 4 - 写代码- 建立你的工作目录 (Windows).srt
│  ├1 - 5 - 写代码- 建立你的工作目录 (Mac).mp4
│  ├1 - 5 - 写代码- 建立你的工作目录 (Mac).srt
│  ├1 - 6 - 使用R版本3.1.1.mp4
│  ├1 - 6 - 使用R版本3.1.1.srt
│  ├2 - 1 - 简介.mp4
│  ├2 - 1 - 简介.srt
│  ├2 - 10 - 读写数据 (第1部分) [12-55].mp4
│  ├2 - 10 - 读写数据 (第1部分) [12-55].srt
│  ├2 - 11 - 读写数据 (第2部分) [9-30].mp4
│  ├2 - 11 - 读写数据 (第2部分) [9-30].srt
│  ├2 - 12 - swirl 简介.mp4
│  ├2 - 12 - swirl 简介.srt
│  ├2 - 2 - 概述R的历史 [16-07].mp4
│  ├2 - 2 - 概述R的历史 [16-07].srt
│  ├2 - 3 - 寻求帮助 [13-53].mp4
│  ├2 - 3 - 寻求帮助 [13-53].srt
│  ├2 - 4 - 数据类型 (第1部分) [9-26].mp4
│  ├2 - 4 - 数据类型 (第1部分) [9-26].srt
│  ├2 - 5 - 数据类型 (第2部分) [9-45].mp4
│  ├2 - 5 - 数据类型 (第2部分) [9-45].srt
│  ├2 - 6 - 数据类型 (第3部分) [11-51].mp4
│  ├2 - 6 - 数据类型 (第3部分) [11-51].srt
│  ├2 - 7 - 提取子集 (第1部分) [7-01].mp4
│  ├2 - 7 - 提取子集 (第1部分) [7-01].srt
│  ├2 - 8 - 提取子集 (第2部分) [10-18].mp4
│  ├2 - 8 - 提取子集 (第2部分) [10-18].srt
│  ├2 - 9 - 向量化运算 [3-46].mp4
│  ├2 - 9 - 向量化运算 [3-46].srt
│  ├3 - 1 - 控制结构 (第1部分) [7-10].mp4
│  ├3 - 1 - 控制结构 (第1部分) [7-10].srt
│  ├3 - 10 - 日期和时间 [10-29].mp4
│  ├3 - 10 - 日期和时间 [10-29].srt
│  ├3 - 2 - 控制结构 (第2部分) [8-11].mp4
│  ├3 - 2 - 控制结构 (第2部分) [8-11].srt
│  ├3 - 3 - 你的第一个 R 函数 [10-29].mp4
│  ├3 - 3 - 你的第一个 R 函数 [10-29].srt
│  ├3 - 4 - 函数 (第1部分) [9-17].mp4
│  ├3 - 4 - 函数 (第1部分) [9-17].srt
│  ├3 - 5 - 函数 (第2部分) [7-13].mp4
│  ├3 - 5 - 函数 (第2部分) [7-13].srt
│  ├3 - 6 - 作用域规则 (第1部分) [10-32].mp4
│  ├3 - 6 - 作用域规则 (第1部分) [10-32].srt
│  ├3 - 7 - 作用域规则 (第2部分) [8-34].mp4
│  ├3 - 7 - 作用域规则 (第2部分) [8-34].srt
│  ├3 - 8 - 作用域规则 (第3部分) [9-21].mp4
│  ├3 - 8 - 作用域规则 (第3部分) [9-21].srt
│  ├3 - 9 - 写代码标准 [8-59].mp4
│  ├3 - 9 - 写代码标准 [8-59].srt
│  ├4 - 1 - lapply [9-23].mp4
│  ├4 - 1 - lapply [9-23].srt
│  ├4 - 2 - apply [7-21].mp4
│  ├4 - 2 - apply [7-21].srt
│  ├4 - 3 - mapply [4-46].mp4
│  ├4 - 3 - mapply [4-46].srt
│  ├4 - 4 - tapply [3-17].mp4
│  ├4 - 4 - tapply [3-17].srt
│  ├4 - 5 - split [9-09].mp4
│  ├4 - 5 - split [9-09].srt
│  ├4 - 6 - 调试工具 (第1部分) [12-33].mp4
│  ├4 - 6 - 调试工具 (第1部分) [12-33].srt
│  ├4 - 7 - 调试工具 (第2部分) [6-25].mp4
│  ├4 - 7 - 调试工具 (第2部分) [6-25].srt
│  ├4 - 8 - 调试工具 (第3部分) [8-21].mp4
│  ├4 - 8 - 调试工具 (第3部分) [8-21].srt
│  ├5 - 1 - str 函数 [6-08].mp4
│  ├5 - 1 - str 函数 [6-08].srt
│  ├5 - 2 - 模拟 (第1部分) [7-47].mp4
│  ├5 - 2 - 模拟 (第1部分) [7-47].srt
│  ├5 - 3 - 模拟 (第2部分) [7-02].mp4
│  ├5 - 3 - 模拟 (第2部分) [7-02].srt
│  ├5 - 4 - R编译器 (第1部分) [10-39].mp4
│  ├5 - 4 - R编译器 (第1部分) [10-39].srt
│  ├5 - 5 - R编译器 (第2部分) [10-26].mp4
│  └5 - 5 - R编译器 (第2部分) [10-26].srt
├<3.数据采集与清洗>
│  ├1 - 1 - Obtaining Data Motivation (5-38).mp4
│  ├1 - 1 - Obtaining Data Motivation (5-38).srt
│  ├1 - 2 - Raw and Processed Data (7-07).mp4
│  ├1 - 3 - Components of Tidy Data (9-25).mp4
│  ├1 - 4 - Downloading Files (7-09).mp4
│  ├1 - 5 - Reading Local Files (4-55).mp4
│  ├1 - 6 - Reading Excel Files (3-55).mp4
│  ├1 - 7 - Reading XML (12-39).mp4
│  ├1 - 8 - Reading JSON (5-03).mp4
│  ├1 - 9 - The data.table Package (11-18).mp4
│  ├2 - 1 - Reading from MySQL (14-44).mp4
│  ├2 - 2 - Reading from HDF5  (6-45).mp4
│  ├2 - 3 - Reading from The Web (6-47).mp4
│  ├2 - 4 - Reading From APIs (7-57).mp4
│  ├2 - 5 - Reading From Other Sources (4-44).mp4
│  ├3 - 1 - Subsetting and Sorting (6-51).mp4
│  ├3 - 2 - Summarizing Data (11-37).mp4
│  ├3 - 3 - Creating New Variables (10-32).mp4
│  ├3 - 4 - Reshaping Data (9-13).mp4
│  ├3 - 5 - Managing Data Frames with dplyr - Introduction.mp4
│  ├3 - 6 - Managing Data Frames with dplyr - Basic Tools.mp4
│  ├3 - 7 - Merging Data (6-19).mp4
│  ├4 - 1 - Editing Text Variables (10-46).mp4
│  ├4 - 2 - Regular Expressions I (5-16).mp4
│  ├4 - 3 - Regular Expressions II (8-00).mp4
│  ├4 - 4 - Working with Dates (6-02).mp4
│  ├4 - 5 - Data Resources (3-33).mp4
│  ├<3.数据获取与处理英文字幕>
│  │  ├1 - 1 - Obtaining Data Motivation (5-38).srt
│  │  ├1 - 2 - Raw and Processed Data (7-07).srt
│  │  ├1 - 3 - Components of Tidy Data (9-25).srt
│  │  ├1 - 4 - Downloading Files (7-09).srt
│  │  ├1 - 5 - Reading Local Files (4-55).srt
│  │  ├1 - 6 - Reading Excel Files (3-55).srt
│  │  ├1 - 7 - Reading XML (12-39).srt
│  │  ├1 - 8 - Reading JSON (5-03).srt
│  │  ├1 - 9 - The data.table Package (11-18).srt
│  │  ├2 - 1 - Reading from MySQL (14-44).srt
│  │  ├2 - 2 - Reading from HDF5  (6-45).srt
│  │  ├2 - 3 - Reading from The Web (6-47).srt
│  │  ├2 - 4 - Reading From APIs (7-57).srt
│  │  ├2 - 5 - Reading From Other Sources (4-44).srt
│  │  ├3 - 1 - Subsetting and Sorting (6-51).srt
│  │  ├3 - 2 - Summarizing Data (11-37).srt
│  │  ├3 - 3 - Creating New Variables (10-32).srt
│  │  ├3 - 4 - Reshaping Data (9-13).srt
│  │  ├3 - 5 - Managing Data Frames with dplyr - Introduction.srt
│  │  ├3 - 6 - Managing Data Frames with dplyr - Basic Tools.srt
│  │  ├3 - 7 - Merging Data (6-19).srt
│  │  ├4 - 1 - Editing Text Variables (10-46).srt
│  │  ├4 - 2 - Regular Expressions I (5-16).srt
│  │  ├4 - 3 - Regular Expressions II (8-00).srt
│  │  ├4 - 4 - Working with Dates (6-02).srt
│  │  └4 - 5 - Data Resources (3-33).srt
│  ├<3.数据获取与处理中文字幕>
│  │  ├1 - 1 - Obtaining Data Motivation (5-38).srt
│  │  ├1 - 2 - Raw and Processed Data (7-07).srt
│  │  ├1 - 3 - Components of Tidy Data (9-25).srt
│  │  ├1 - 4 - Downloading Files (7-09).srt
│  │  ├1 - 5 - Reading Local Files (4-55).srt
│  │  ├1 - 6 - Reading Excel Files (3-55).srt
│  │  ├1 - 7 - Reading XML (12-39).srt
│  │  ├1 - 8 - Reading JSON (5-03).srt
│  │  ├1 - 9 - The data.table Package (11-18).srt
│  │  ├2 - 1 - Reading from MySQL (14-44).srt
│  │  ├2 - 2 - Reading from HDF5  (6-45).srt
│  │  ├2 - 3 - Reading from The Web (6-47).srt
│  │  ├2 - 4 - Reading From APIs (7-57).srt
│  │  ├2 - 5 - Reading From Other Sources (4-44).srt
│  │  ├3 - 1 - Subsetting and Sorting (6-51).srt
│  │  ├3 - 2 - Summarizing Data (11-37).srt
│  │  ├3 - 3 - Creating New Variables (10-32).srt
│  │  ├3 - 4 - Reshaping Data (9-13).srt
│  │  ├3 - 7 - Merging Data (6-19).srt
│  │  ├4 - 1 - Editing Text Variables (10-46).srt
│  │  ├4 - 2 - Regular Expressions I (5-16).srt
│  │  ├4 - 3 - Regular Expressions II (8-00).srt
│  │  ├4 - 4 - Working with Dates (6-02).srt
│  │  └4 - 5 - Data Resources (3-33).srt
├<4.探索性数据分析>
│  ├2 - 1 - Introduction.mp4
│  ├2 - 10 - Graphics Devices in R (part 2) [7-31].mp4
│  ├2 - 2 - Principles of Analytic Graphics [12-11].mp4
│  ├2 - 3 - Exploratory Graphs (part 1) [9-28].mp4
│  ├2 - 4 - Exploratory Graphs (part 2) [5-13].mp4
│  ├2 - 5 - Plotting Systems in R [9-34].mp4
│  ├2 - 6 - Base Plotting System (part 1) [11-20].mp4
│  ├2 - 7 - Base Plotting System (part 2) [6-56].mp4
│  ├2 - 8 - Base Plotting Demonstration [16-56].mp4
│  ├2 - 9 - Graphics Devices in R (part 1) [5-34].mp4
│  ├3 - 1 - Lattice Plotting System (part 1) [6-22].mp4
│  ├3 - 2 - Lattice Plotting System (part 2) [6-12].mp4
│  ├3 - 3 - ggplot2 (part 1) [6-26].mp4
│  ├3 - 4 - ggplot2 (part 2) [13-53].mp4
│  ├3 - 5 - ggplot2 (part 3) [9-47].mp4
│  ├3 - 6 - ggplot2 (part 4) [10-38].mp4
│  ├3 - 7 - ggplot2 (part 5) [8-11].mp4
│  ├4 - 1 - Hierarchical Clustering (part 1) [7-21].mp4
│  ├4 - 10 - Working with Color in R Plots (part 2) [7-41].mp4
│  ├4 - 11 - Working with Color in R Plots (part 3) [6-39].mp4
│  ├4 - 12 - Working with Color in R Plots (part 4) [3-35].mp4
│  ├4 - 2 - Hierarchical Clustering (part 2) [5-24].mp4
│  ├4 - 3 - Hierarchical Clustering (part 3) [7-34].mp4
│  ├4 - 4 - K-Means Clustering (part 1) [5-46].mp4
│  ├4 - 5 - K-Means Clustering (part 2) [4-26].mp4
│  ├4 - 6 - Dimension Reduction (part 1) [7-55].mp4
│  ├4 - 7 - Dimension Reduction (part 2) [9-26].mp4
│  ├4 - 8 - Dimension Reduction (part 3) [6-42].mp4
│  ├4 - 9 - Working with Color in R Plots (part 1) [4-08].mp4
│  ├5 - 1 - Clustering Case Study [14-51].mp4
│  ├5 - 2 - Air Pollution Case Study [40-35].mp4
│  ├<数据探索英文字幕>
│  │  ├2 - 1 - Introduction.srt
│  │  ├2 - 10 - Graphics Devices in R (part 2) [7-31].srt
│  │  ├2 - 2 - Principles of Analytic Graphics [12-11].srt
│  │  ├2 - 3 - Exploratory Graphs (part 1) [9-28].srt
│  │  ├2 - 4 - Exploratory Graphs (part 2) [5-13].srt
│  │  ├2 - 5 - Plotting Systems in R [9-34].srt
│  │  ├2 - 6 - Base Plotting System (part 1) [11-20].srt
│  │  ├2 - 7 - Base Plotting System (part 2) [6-56].srt
│  │  ├2 - 8 - Base Plotting Demonstration [16-56].srt
│  │  ├2 - 9 - Graphics Devices in R (part 1) [5-34].srt
│  │  ├3 - 1 - Lattice Plotting System (part 1) [6-22].srt
│  │  ├3 - 2 - Lattice Plotting System (part 2) [6-12].srt
│  │  ├3 - 3 - ggplot2 (part 1) [6-26].srt
│  │  ├3 - 4 - ggplot2 (part 2) [13-53].srt
│  │  ├3 - 5 - ggplot2 (part 3) [9-47].srt
│  │  ├3 - 6 - ggplot2 (part 4) [10-38].srt
│  │  ├3 - 7 - ggplot2 (part 5) [8-11].srt
│  │  ├4 - 1 - Hierarchical Clustering (part 1) [7-21].srt
│  │  ├4 - 10 - Working with Color in R Plots (part 2) [7-41].srt
│  │  ├4 - 11 - Working with Color in R Plots (part 3) [6-39].srt
│  │  ├4 - 12 - Working with Color in R Plots (part 4) [3-35].srt
│  │  ├4 - 2 - Hierarchical Clustering (part 2) [5-24].srt
│  │  ├4 - 3 - Hierarchical Clustering (part 3) [7-34].srt
│  │  ├4 - 4 - K-Means Clustering (part 1) [5-46].srt
│  │  ├4 - 5 - K-Means Clustering (part 2) [4-26].srt
│  │  ├4 - 6 - Dimension Reduction (part 1) [7-55].srt
│  │  ├4 - 7 - Dimension Reduction (part 2) [9-26].srt
│  │  ├4 - 8 - Dimension Reduction (part 3) [6-42].srt
│  │  ├4 - 9 - Working with Color in R Plots (part 1) [4-08].srt
│  │  ├5 - 1 - Clustering Case Study [14-51].srt
│  │  └5 - 2 - Air Pollution Case Study [40-35].srt
│  ├<数据探索中文字幕>
│  │  ├2 - 1 - Introduction.srt
│  │  ├2 - 10 - Graphics Devices in R (part 2) [7-31].srt
│  │  ├2 - 2 - Principles of Analytic Graphics [12-11].srt
│  │  ├2 - 3 - Exploratory Graphs (part 1) [9-28].srt
│  │  ├2 - 4 - Exploratory Graphs (part 2) [5-13].srt
│  │  ├2 - 5 - Plotting Systems in R [9-34].srt
│  │  ├2 - 6 - Base Plotting System (part 1) [11-20].srt
│  │  ├2 - 7 - Base Plotting System (part 2) [6-56].srt
│  │  ├2 - 8 - Base Plotting Demonstration [16-56].srt
│  │  ├2 - 9 - Graphics Devices in R (part 1) [5-34].srt
│  │  ├3 - 1 - Lattice Plotting System (part 1) [6-22].srt
│  │  ├3 - 2 - Lattice Plotting System (part 2) [6-12].srt
│  │  ├3 - 3 - ggplot2 (part 1) [6-26].srt
│  │  ├3 - 4 - ggplot2 (part 2) [13-53].srt
│  │  ├3 - 5 - ggplot2 (part 3) [9-47].srt
│  │  ├3 - 6 - ggplot2 (part 4) [10-38].srt
│  │  ├3 - 7 - ggplot2 (part 5) [8-11].srt
│  │  ├4 - 1 - Hierarchical Clustering (part 1) [7-21].srt
│  │  ├4 - 10 - Working with Color in R Plots (part 2) [7-41].srt
│  │  ├4 - 11 - Working with Color in R Plots (part 3) [6-39].srt
│  │  ├4 - 12 - Working with Color in R Plots (part 4) [3-35].srt
│  │  ├4 - 2 - Hierarchical Clustering (part 2) [5-24].srt
│  │  ├4 - 3 - Hierarchical Clustering (part 3) [7-34].srt
│  │  ├4 - 4 - K-Means Clustering (part 1) [5-46].srt
│  │  ├4 - 5 - K-Means Clustering (part 2) [4-26].srt
│  │  ├4 - 6 - Dimension Reduction (part 1) [7-55].srt
│  │  ├4 - 7 - Dimension Reduction (part 2) [9-26].srt
│  │  ├4 - 8 - Dimension Reduction (part 3) [6-42].srt
│  │  ├4 - 9 - Working with Color in R Plots (part 1) [4-08].srt
│  │  └5 - 1 - Clustering Case Study [14-51].srt
├<5.可重复性研究>
│  ├1 - 1 - Introduction.mp4
│  ├1 - 1 - Introduction.srt
│  ├1 - 2 - Reproducible Research- Concepts and Ideas (part 1) [7-11].mp4
│  ├1 - 2 - Reproducible Research- Concepts and Ideas (part 1) [7-11].srt
│  ├1 - 3 - Reproducible Research- Concepts and Ideas (part 2) [5-27].mp4
│  ├1 - 3 - Reproducible Research- Concepts and Ideas (part 2) [5-27].srt
│  ├1 - 4 - Reproducible Research- Concepts and Ideas (part 3) [3-26].mp4
│  ├1 - 4 - Reproducible Research- Concepts and Ideas (part 3) [3-26].srt
│  ├1 - 5 - Scripting Your Analysis [4-36].mp4
│  ├1 - 5 - Scripting Your Analysis [4-36].srt
│  ├1 - 6 - Structure of a Data Analysis (part 1) [12-29].mp4
│  ├1 - 6 - Structure of a Data Analysis (part 1) [12-29].srt
│  ├1 - 7 - Structure of a Data Analysis (part 2) [17-41].mp4
│  ├1 - 7 - Structure of a Data Analysis (part 2) [17-41].srt
│  ├1 - 8 - Organizing Your Analysis [11-05].mp4
│  ├1 - 8 - Organizing Your Analysis [11-05].srt
│  ├1 - 9 - Use R version 3.1.1.mp4
│  ├1 - 9 - Use R version 3.1.1.srt
│  ├2 - 1 - Coding Standards in R [8-59].mp4
│  ├2 - 1 - Coding Standards in R [8-59].srt
│  ├2 - 2 - Markdown [5-15].mp4
│  ├2 - 2 - Markdown [5-15].srt
│  ├2 - 3 - R Markdown [6-35].mp4
│  ├2 - 3 - R Markdown [6-35].srt
│  ├2 - 4 - R Markdown Demonstration [7-24].mp4
│  ├2 - 4 - R Markdown Demonstration [7-24].srt
│  ├2 - 5 - knitr (part 1) [7-05].mp4
│  ├2 - 5 - knitr (part 1) [7-05].srt
│  ├2 - 6 - knitr (part 2) [4-11].mp4
│  ├2 - 6 - knitr (part 2) [4-11].srt
│  ├2 - 7 - knitr (part 3) [4-46].mp4
│  ├2 - 7 - knitr (part 3) [4-46].srt
│  ├2 - 8 - knitr (part 4) [9-21].mp4
│  ├2 - 8 - knitr (part 4) [9-21].srt
│  ├2 - 9 - Introduction to Peer Assessment 1.mp4
│  ├2 - 9 - Introduction to Peer Assessment 1.srt
│  ├3 - 1 - Communicating Results [6-54].mp4
│  ├3 - 1 - Communicating Results [6-54].srt
│  ├3 - 10 - Evidence-based Data Analysis (part 5) [7-56].mp4
│  ├3 - 10 - Evidence-based Data Analysis (part 5) [7-56].srt
│  ├3 - 11 - Introduction to Peer Assessment 2.mp4
│  ├3 - 11 - Introduction to Peer Assessment 2.srt
│  ├3 - 2 - RPubs [3-21].mp4
│  ├3 - 2 - RPubs [3-21].srt
│  ├3 - 3 - Reproducible Research Checklist (part 1) [8-22].mp4
│  ├3 - 3 - Reproducible Research Checklist (part 1) [8-22].srt
│  ├3 - 4 - Reproducible Research Checklist (part 2) [10-20].mp4
│  ├3 - 4 - Reproducible Research Checklist (part 2) [10-20].srt
│  ├3 - 5 - Reproducible Research Checklist (part 3) [6-54].mp4
│  ├3 - 5 - Reproducible Research Checklist (part 3) [6-54].srt
│  ├3 - 6 - Evidence-based Data Analysis (part 1) [3-51].mp4
│  ├3 - 6 - Evidence-based Data Analysis (part 1) [3-51].srt
│  ├3 - 7 - Evidence-based Data Analysis (part 2) [3-34].mp4
│  ├3 - 7 - Evidence-based Data Analysis (part 2) [3-34].srt
│  ├3 - 8 - Evidence-based Data Analysis (part 3) [4-25].mp4
│  ├3 - 8 - Evidence-based Data Analysis (part 3) [4-25].srt
│  ├3 - 9 - Evidence-based Data Analysis (part 4) [4-47].mp4
│  ├3 - 9 - Evidence-based Data Analysis (part 4) [4-47].srt
│  ├4 - 1 - Caching Computations [11-16].mp4
│  ├4 - 1 - Caching Computations [11-16].srt
│  ├4 - 2 - Case Study- Air Pollution [14-12].mp4
│  ├4 - 2 - Case Study- Air Pollution [14-12].srt
│  ├4 - 3 - Case Study- High Throughput Biology [30-51].mp4
│  └4 - 3 - Case Study- High Throughput Biology [30-51].srt
├<6.统计推断>
│  ├1 - 1 - 01 01 Introduction (7-05).mp4
│  ├1 - 1 - 01 01 Introduction (7-05).srt
│  ├1 - 10 - 04 02 Expected values, simple examples (2-12).mp4
│  ├1 - 10 - 04 02 Expected values, simple examples (2-12).srt
│  ├1 - 11 - 04 03 Expected values for PDFs  (7-46).mp4
│  ├1 - 11 - 04 03 Expected values for PDFs  (7-46).srt
│  ├1 - 2 - Brief note on new materials.mp4
│  ├1 - 3 - 02 01 Introduction to probability (6-13).mp4
│  ├1 - 3 - 02 01 Introduction to probability (6-13).srt
│  ├1 - 4 - 02 02 Probability mass functions (7-14).mp4
│  ├1 - 4 - 02 02 Probability mass functions (7-14).srt
│  ├1 - 5 - 02 03 Probability density functions (13-27).mp4
│  ├1 - 5 - 02 03 Probability density functions (13-27).srt
│  ├1 - 6 - 03 01 Conditional Probability (3-23).mp4
│  ├1 - 6 - 03 01 Conditional Probability (3-23).srt
│  ├1 - 7 - 03 02 Baye-'s rule (7-52).mp4
│  ├1 - 7 - 03 02 Baye-'s rule (7-52).srt
│  ├1 - 8 - 03 03 Independence (3-04).mp4
│  ├1 - 8 - 03 03 Independence (3-04).srt
│  ├1 - 9 - 04 01 Expected values (5-14).mp4
│  ├1 - 9 - 04 01 Expected values (5-14).srt
│  ├2 - 1 - 05 01 Introduction to variability (4-57).mp4
│  ├2 - 1 - 05 01 Introduction to variability (4-57).srt
│  ├2 - 10 - 07 03 Asymptotics and confidence intervals (20-10).mp4
│  ├2 - 10 - 07 03 Asymptotics and confidence intervals (20-10).srt
│  ├2 - 2 - 05 02 Variance simulation examples (2-46).mp4
│  ├2 - 2 - 05 02 Variance simulation examples (2-46).srt
│  ├2 - 3 - 05 03 Standard error of the mean (7-12).mp4
│  ├2 - 3 - 05 03 Standard error of the mean (7-12).srt
│  ├2 - 4 - 05 04 Variance data example (3-33).mp4
│  ├2 - 4 - 05 04 Variance data example (3-33).srt
│  ├2 - 5 - 06 01 Binomial distrubtion (3-02).mp4
│  ├2 - 5 - 06 01 Binomial distrubtion (3-02).srt
│  ├2 - 6 - 06 02 Normal distribution (15-12).mp4
│  ├2 - 6 - 06 02 Normal distribution (15-12).srt
│  ├2 - 7 - 06 03 Poisson (6-08).mp4
│  ├2 - 7 - 06 03 Poisson (6-08).srt
│  ├2 - 8 - 07 01 Asymptotics and LLN (4-28).mp4
│  ├2 - 8 - 07 01 Asymptotics and LLN (4-28).srt
│  ├2 - 9 - 07 02 Asymptotics and the CLT (8-27).mp4
│  ├2 - 9 - 07 02 Asymptotics and the CLT (8-27).srt
│  ├3 - 1 - 08 01 T confidence intervals (9-12).mp4
│  ├3 - 1 - 08 01 T confidence intervals (9-12).srt
│  ├3 - 10 - 10 02 Pvalue further examples (5-54).mp4
│  ├3 - 10 - 10 02 Pvalue further examples (5-54).srt
│  ├3 - 2 - 08 02 T confidence intervals example (4-06).mp4
│  ├3 - 2 - 08 02 T confidence intervals example (4-06).srt
│  ├3 - 3 - 08 03 Independent group T intervals (14-36).mp4
│  ├3 - 3 - 08 03 Independent group T intervals (14-36).srt
│  ├3 - 4 - 08 04 A note on unequal variance (3-29).mp4
│  ├3 - 4 - 08 04 A note on unequal variance (3-29).srt
│  ├3 - 5 - 09 01 Hypothesis testing (4-17).mp4
│  ├3 - 5 - 09 01 Hypothesis testing (4-17).srt
│  ├3 - 6 - 09 02 Example of choosing a rejection region (5-12).mp4
│  ├3 - 6 - 09 02 Example of choosing a rejection region (5-12).srt
│  ├3 - 7 - 09 03 T tests (7-04).mp4
│  ├3 - 7 - 09 03 T tests (7-04).srt
│  ├3 - 8 - 09 04 Two group testing (17-54).mp4
│  ├3 - 8 - 09 04 Two group testing (17-54).srt
│  ├3 - 9 - 10 01 Pvalues (7-50).mp4
│  ├3 - 9 - 10 01 Pvalues (7-50).srt
│  ├4 - 1 - 11 01 Power (4-54).mp4
│  ├4 - 1 - 11 01 Power (4-54).srt
│  ├4 - 2 - 11 02 Calculating Power (12-51).mp4
│  ├4 - 2 - 11 02 Calculating Power (12-51).srt
│  ├4 - 3 - 11 03 Notes on power (4-57).mp4
│  ├4 - 3 - 11 03 Notes on power (4-57).srt
│  ├4 - 4 - 11 04 T test power (8-02).mp4
│  ├4 - 4 - 11 04 T test power (8-02).srt
│  ├4 - 5 - 12 Multiple Comparisons (25-22).mp4
│  ├4 - 5 - 12 Multiple Comparisons (25-22).srt
│  ├4 - 6 - 13 01 Bootstrapping (7-10).mp4
│  ├4 - 6 - 13 01 Bootstrapping (7-10).srt
│  ├4 - 7 - 13 02 Bootstrapping example (3-29).mp4
│  ├4 - 7 - 13 02 Bootstrapping example (3-29).srt
│  ├4 - 8 - 13 03 Notes on the bootstrap (10-20).mp4
│  ├4 - 8 - 13 03 Notes on the bootstrap (10-20).srt
│  ├4 - 9 - 13 04 Permutation tests (9-07).mp4
│  ├4 - 9 - 13 04 Permutation tests (9-07).srt
│  ├9 - 1 - Just enough knitr to do the project.mp4
│  └9 - 1 - Just enough knitr to do the project.srt
├<7.回归模型>
│  ├1 - 1 - 01_01_a Introduction to regression (4-10).mp4
│  ├1 - 1 - 01_01_a Introduction to regression (4-10).srt
│  ├1 - 10 - 01_04_a Regression to the Mean (3-46).mp4
│  ├1 - 10 - 01_04_a Regression to the Mean (3-46).srt
│  ├1 - 11 - 01_04_b Regression to the Mean Example (10-46).mp4
│  ├1 - 11 - 01_04_b Regression to the Mean Example (10-46).srt
│  ├1 - 2 - 01_01_b Basic least squares (5-41).mp4
│  ├1 - 2 - 01_01_b Basic least squares (5-41).srt
│  ├1 - 3 - 01_01_c Least squares continued (5-38).mp4
│  ├1 - 3 - 01_01_c Least squares continued (5-38).srt
│  ├1 - 4 - 01_01_d Regression through the origin (7-37).mp4
│  ├1 - 4 - 01_01_d Regression through the origin (7-37).srt
│  ├1 - 5 - 01_02_a Basic Notation and Background (3-26).mp4
│  ├1 - 5 - 01_02_a Basic Notation and Background (3-26).srt
│  ├1 - 6 - 01_02_b Normalization and Correlation (5-22).mp4
│  ├1 - 6 - 01_02_b Normalization and Correlation (5-22).srt
│  ├1 - 7 - 01_03_a Linear Least Squares (6-01).mp4
│  ├1 - 7 - 01_03_a Linear Least Squares (6-01).srt
│  ├1 - 8 - 01_03_b Linear Least Squares Special Cases (4-22).mp4
│  ├1 - 8 - 01_03_b Linear Least Squares Special Cases (4-22).srt
│  ├1 - 9 - 01_03_c Linear Least Squares Solved (11-33).mp4
│  ├1 - 9 - 01_03_c Linear Least Squares Solved (11-33).srt
│  ├2 - 1 - 01_05_a Statistical Linear Regression Models (5-58).mp4
│  ├2 - 1 - 01_05_a Statistical Linear Regression Models (5-58).srt
│  ├2 - 10 - 02_01_a Multivariate Regression (2-47).mp4
│  ├2 - 10 - 02_01_a Multivariate Regression (2-47).srt
│  ├2 - 11 - 02_01_b Multivariable Least Squares (12-59).mp4
│  ├2 - 11 - 02_01_b Multivariable Least Squares (12-59).srt
│  ├2 - 12 - 02_01_c More Multivariable Least Squares (8-35).mp4
│  ├2 - 12 - 02_01_c More Multivariable Least Squares (8-35).srt
│  ├2 - 13 - 02_01_d Multivariable Linear Models Interpretation (9-46).mp4
│  ├2 - 13 - 02_01_d Multivariable Linear Models Interpretation (9-46).srt
│  ├2 - 2 - 01_05_b Interpreting Regression Coefficients (6-28).mp4
│  ├2 - 2 - 01_05_b Interpreting Regression Coefficients (6-28).srt
│  ├2 - 3 - 01_05_c Statistical Regression Models Examples (6-00).mp4
│  ├2 - 3 - 01_05_c Statistical Regression Models Examples (6-00).srt
│  ├2 - 4 - 01_06_a Residuals (2-51).mp4
│  ├2 - 4 - 01_06_a Residuals (2-51).srt
│  ├2 - 5 - 01_06_b Properties of Residuals (8-48).mp4
│  ├2 - 5 - 01_06_b Properties of Residuals (8-48).srt
│  ├2 - 6 - 01_06_c Residual Variation (11-20).mp4
│  ├2 - 6 - 01_06_c Residual Variation (11-20).srt
│  ├2 - 7 - 01_07_a Inference in Regression (1-28).mp4
│  ├2 - 7 - 01_07_a Inference in Regression (1-28).srt
│  ├2 - 8 - 01_07_b T Tests for Regression Coefficients (12-33).mp4
│  ├2 - 8 - 01_07_b T Tests for Regression Coefficients (12-33).srt
│  ├2 - 9 - 01_07_c Prediction Intervals (14-13).mp4
│  ├2 - 9 - 01_07_c Prediction Intervals (14-13).srt
│  ├3 - 1 - 02_02_a Multivariable regression examples (14-38).mp4
│  ├3 - 1 - 02_02_a Multivariable regression examples (14-38).srt
│  ├3 - 10 - 02_04_c Residuals and diagnostics examples (6-32).mp4
│  ├3 - 10 - 02_04_c Residuals and diagnostics examples (6-32).srt
│  ├3 - 11 - 02_05_a Some thoughts on model selection (6-38).mp4
│  ├3 - 11 - 02_05_a Some thoughts on model selection (6-38).srt
│  ├3 - 12 - 02_05_b Variance inflation (10-33).mp4
│  ├3 - 12 - 02_05_b Variance inflation (10-33).srt
│  ├3 - 13 - 02_05_c Model comparison and search (8-05).mp4
│  ├3 - 13 - 02_05_c Model comparison and search (8-05).srt
│  ├3 - 2 - 02_02_b Dummy variables (27-08).mp4
│  ├3 - 2 - 02_02_b Dummy variables (27-08).srt
│  ├3 - 3 - 02_02_c Interactions (26-29).mp4
│  ├3 - 3 - 02_02_c Interactions (26-29).srt
│  ├3 - 4 - 02_03_a Multivariable simulation exercises (5-42).mp4
│  ├3 - 4 - 02_03_a Multivariable simulation exercises (5-42).srt
│  ├3 - 5 - 02_03_b More simulation exercises (3-53).mp4
│  ├3 - 5 - 02_03_b More simulation exercises (3-53).srt
│  ├3 - 6 - 02_03_c More simulation examples 2 (2-52).mp4
│  ├3 - 6 - 02_03_c More simulation examples 2 (2-52).srt
│  ├3 - 7 - 02_03_d Simulation examples finished (4-22).mp4
│  ├3 - 7 - 02_03_d Simulation examples finished (4-22).srt
│  ├3 - 8 - 02_04_a Residuals (4-48).mp4
│  ├3 - 8 - 02_04_a Residuals (4-48).srt
│  ├3 - 9 - 02_04_b More on diagnostics (5-18).mp4
│  ├3 - 9 - 02_04_b More on diagnostics (5-18).srt
│  ├4 - 1 - 03_01_a Generalized Linear Models (2-32).mp4
│  ├4 - 1 - 03_01_a Generalized Linear Models (2-32).srt
│  ├4 - 10 - 03_04_a Fitting Functions (9-52).mp4
│  ├4 - 10 - 03_04_a Fitting Functions (9-52).srt
│  ├4 - 11 - 03_04_b Fun Example (8-02).mp4
│  ├4 - 11 - 03_04_b Fun Example (8-02).srt
│  ├4 - 2 - 03_01_b GLM Examples (6-21).mp4
│  ├4 - 2 - 03_01_b GLM Examples (6-21).srt
│  ├4 - 3 - 03_01_c Variances and Quasi Likelihood (7-05).mp4
│  ├4 - 3 - 03_01_c Variances and Quasi Likelihood (7-05).srt
│  ├4 - 4 - 03_02_a Binary Data GLMs (7-11).mp4
│  ├4 - 4 - 03_02_a Binary Data GLMs (7-11).srt
│  ├4 - 5 - 03_02_b GLMs and Odds (14-03).mp4
│  ├4 - 5 - 03_02_b GLMs and Odds (14-03).srt
│  ├4 - 6 - 03_02_c More on Odds (12-29).mp4
│  ├4 - 6 - 03_02_c More on Odds (12-29).srt
│  ├4 - 7 - 03_03_a Poisson Regression (8-15).mp4
│  ├4 - 7 - 03_03_a Poisson Regression (8-15).srt
│  ├4 - 8 - 03_03_b Poisson Regression Example (14-12).mp4
│  ├4 - 8 - 03_03_b Poisson Regression Example (14-12).srt
│  ├4 - 9 - 03_03_c Poisson Rate Models  (12-53).mp4
│  └4 - 9 - 03_03_c Poisson Rate Models  (12-53).srt
├<8.机器学习>
│  ├1 - 1 - Prediction motivation (8-26).mp4
│  ├1 - 1 - Prediction motivation (8-26).srt
│  ├1 - 2 - What is prediction- (8-39).mp4
│  ├1 - 2 - What is prediction- (8-39).srt
│  ├1 - 3 - Relative importance of steps (9-45).mp4
│  ├1 - 3 - Relative importance of steps (9-45).srt
│  ├1 - 4 - In and out of sample errors (6-57).mp4
│  ├1 - 4 - In and out of sample errors (6-57).srt
│  ├1 - 5 - Prediction study design (9-05).mp4
│  ├1 - 5 - Prediction study design (9-05).srt
│  ├1 - 6 - Types of errors (10-35).mp4
│  ├1 - 6 - Types of errors (10-35).srt
│  ├1 - 7 - Receiver Operating Characteristic (5-03).mp4
│  ├1 - 7 - Receiver Operating Characteristic (5-03).srt
│  ├1 - 8 - Cross validation (8-20).mp4
│  ├1 - 8 - Cross validation (8-20).srt
│  ├1 - 9 - What data should you use- (6-01).mp4
│  ├1 - 9 - What data should you use- (6-01).srt
│  ├2 - 1 - Caret package (6-16).mp4
│  ├2 - 1 - Caret package (6-16).srt
│  ├2 - 2 - Data slicing (5-40).mp4
│  ├2 - 2 - Data slicing (5-40).srt
│  ├2 - 3 - Training options (7-15).mp4
│  ├2 - 3 - Training options (7-15).srt
│  ├2 - 4 - Plotting predictors (10-39).mp4
│  ├2 - 4 - Plotting predictors (10-39).srt
│  ├2 - 5 - Basic preprocessing (10-52).mp4
│  ├2 - 5 - Basic preprocessing (10-52).srt
│  ├2 - 6 - Covariate creation (17-31).mp4
│  ├2 - 6 - Covariate creation (17-31).srt
│  ├2 - 7 - Preprocessing with principal components analysis (14-07).mp4
│  ├2 - 7 - Preprocessing with principal components analysis (14-07).srt
│  ├2 - 8 - Predicting with Regression (12-22).mp4
│  ├2 - 8 - Predicting with Regression (12-22).srt
│  ├2 - 9 - Predicting with Regression Multiple Covariates (11-12).mp4
│  ├2 - 9 - Predicting with Regression Multiple Covariates (11-12).srt
│  ├3 - 1 - Predicting with trees (12-51).mp4
│  ├3 - 1 - Predicting with trees (12-51).srt
│  ├3 - 2 - Bagging (9-13).mp4
│  ├3 - 2 - Bagging (9-13).srt
│  ├3 - 3 - Random Forests (6-49).mp4
│  ├3 - 3 - Random Forests (6-49).srt
│  ├3 - 4 - Boosting (7-08).mp4
│  ├3 - 4 - Boosting (7-08).srt
│  ├3 - 5 - Model Based Prediction (11-39).mp4
│  ├3 - 5 - Model Based Prediction (11-39).srt
│  ├4 - 1 - Regularized regression (13-20).mp4
│  ├4 - 1 - Regularized regression (13-20).srt
│  ├4 - 2 - Combining predictors (7-11).mp4
│  ├4 - 2 - Combining predictors (7-11).srt
│  ├4 - 3 - Forecasting.mp4
│  ├4 - 3 - Forecasting.srt
│  ├4 - 4 - Unsupervised Prediction (4-24).mp4
│  └4 - 4 - Unsupervised Prediction (4-24).srt
├<9.数据产品>
│  ├2 - 1 - Introduction to Data Products (1-05).mp4
│  ├2 - 1 - Introduction to Data Products (1-05).srt
│  ├2 - 10 - More advanced shiny, conditional execution of reactive statements (4-16).mp4
│  ├2 - 10 - More advanced shiny, conditional execution of reactive statements (4-16).srt
│  ├2 - 11 - More advanced shiny, odds and ends (4-55).mp4
│  ├2 - 11 - More advanced shiny, odds and ends (4-55).srt
│  ├2 - 12 - Manipulate (4-49).mp4
│  ├2 - 12 - Manipulate (4-49).srt
│  ├2 - 13 - Intro to rCharts and GoogleVis (1-01).mp4
│  ├2 - 13 - Intro to rCharts and GoogleVis (1-01).srt
│  ├2 - 14 - rCharts introduction (4-45).mp4
│  ├2 - 14 - rCharts introduction (4-45).srt
│  ├2 - 15 - rCharts more examples (5-40).mp4
│  ├2 - 15 - rCharts more examples (5-40).srt
│  ├2 - 16 - rCharts mapping and discussion (5-32).mp4
│  ├2 - 16 - rCharts mapping and discussion (5-32).srt
│  ├2 - 17 - GoogleVis (9-34).mp4
│  ├2 - 17 - GoogleVis (9-34).srt
│  ├2 - 18 - shinyApps.io.mp4
│  ├2 - 18 - shinyApps.io.srt
│  ├2 - 19 - plotly.mp4
│  ├2 - 19 - plotly.srt
│  ├2 - 2 - Motivating Shiny (1-49).mp4
│  ├2 - 2 - Motivating Shiny (1-49).srt
│  ├2 - 3 - Shiny 1 Introduction to Shiny (8-36).mp4
│  ├2 - 3 - Shiny 1 Introduction to Shiny (8-36).srt
│  ├2 - 4 - Shiny 2 basic html and getting input (4-56).mp4
│  ├2 - 4 - Shiny 2 basic html and getting input (4-56).srt
│  ├2 - 5 - Shiny 3 Creating a very basic prediction function (4-12).mp4
│  ├2 - 5 - Shiny 3 Creating a very basic prediction function (4-12).srt
│  ├2 - 6 - Shiny 4 Working with images (2-39).mp4
│  ├2 - 6 - Shiny 4 Working with images (2-39).srt
│  ├2 - 7 - Shiny 5 Discussion (4-48).mp4
│  ├2 - 7 - Shiny 5 Discussion (4-48).srt
│  ├2 - 8 - More advanced shiny discussion, reactivity (9-30).mp4
│  ├2 - 8 - More advanced shiny discussion, reactivity (9-30).srt
│  ├2 - 9 - More advanced shiny, the reactive function (5-50).mp4
│  ├2 - 9 - More advanced shiny, the reactive function (5-50).srt
│  ├3 - 1 - Presenting Data Analysis Writing a Data Report (3-18).mp4
│  ├3 - 10 - Very quick introduction to gh-pages.mp4
│  ├3 - 2 - Slidify intro (5-32).mp4
│  ├3 - 2 - Slidify intro (5-32).srt
│  ├3 - 3 - Slidify working it out (2-01).mp4
│  ├3 - 3 - Slidify working it out (2-01).srt
│  ├3 - 4 - Slidify customization (4-09).mp4
│  ├3 - 4 - Slidify customization (4-09).srt
│  ├3 - 5 - Slidify more details (7-24).mp4
│  ├3 - 5 - Slidify more details (7-24).srt
│  ├3 - 6 - Slidify reminder about knitting R (1-52).mp4
│  ├3 - 6 - Slidify reminder about knitting R (1-52).srt
│  ├3 - 7 - RStudio Presenter 1 Introduction and getting started (4-59).mp4
│  ├3 - 7 - RStudio Presenter 1 Introduction and getting started (4-59).srt
│  ├3 - 8 - RStudio Presenter 2 Authoring details (11-14).mp4
│  ├3 - 8 - RStudio Presenter 2 Authoring details (11-14).srt
│  ├3 - 9 - RStudio Presenter 3 Discussion and comparison with Slidify (4-13).mp4
│  ├3 - 9 - RStudio Presenter 3 Discussion and comparison with Slidify (4-13).srt
│  ├4 - 1 - R Packages (Part 1) (7-11).mp4
│  ├4 - 1 - R Packages (Part 1) (7-11).srt
│  ├4 - 2 - R Packages (Part 2) (14-59).mp4
│  ├4 - 2 - R Packages (Part 2) (14-59).srt
│  ├4 - 3 - Building R Packages Demo (18-00).mp4
│  ├4 - 3 - Building R Packages Demo (18-00).srt
│  ├4 - 4 - R Classes and Methods (Part 1) (13-50).mp4
│  ├4 - 4 - R Classes and Methods (Part 1) (13-50).srt
│  ├4 - 5 - R Classes and Methods (Part 2) (11-19).mp4
│  ├4 - 5 - R Classes and Methods (Part 2) (11-19).srt
│  ├4 - 6 - yhat (Part 1) (24-39).mp4
│  ├4 - 6 - yhat (Part 1) (24-39).srt
│  ├4 - 7 - yhat (Part 2) (11-38).mp4
│  └4 - 7 - yhat (Part 2) (11-38).srt
├<R语言学习笔记和精选教材>
│  ├20141204_Session1_RProgrammingLanguage.pdf
│  ├A.beginer.guide.to.R.PDF
│  ├Introductory.Statistics.with.R.pdf
│  ├introductory.time.series.with.r.pdf
│  ├mysql-130926215935-phpapp02.pptx
│  ├R GRAPG COOKBOOK.pdf
│  ├R.Graphics.pdf
│  ├R.in.a.Nutshell.pdf
│  ├R教程.pdf
│  ├R统计软件详细介绍(中文版).pdf
│  ├R语言.pdf
│  ├R语言初步_统计绘图与编程.ppt
│  ├R语言的绘图功能及应用案例.pdf
│  ├R语言环境下的文本挖掘.pdf
│  ├R语言入门教程.pdf
│  ├R语言数据挖掘案例.pdf
│  ├R语言与数据分析 - 云立方.pptx
│  ├Using.R.for.Data.Management，.Statistical.Analysis，.and.Graphics.pdf
│  ├大数据的Linux基础_01.pdf
│  ├大数据的Linux基础_02.pdf
│  ├简明参考卡片.pdf
│  ├数据分析展现与R语言01.pdf
│  ├数据分析展现与R语言02.pdf
│  ├数据科学家技能路线图.png
│  ├数据挖掘过程在R环境下的应用.pdf
│  ├统计编程的框架与R_语言统计分析基础.pdf
│  ├统计学与R笔记.pdf
│  ├<2013R大会>
│  │  ├DATA-MINING雲端決策平台CDMS-Smart-Score-II-以-R-為基礎-REVISED.pptx
│  │  ├lijian_ChinaR20130518.ppt
│  │  ├R-Case-Study-from-EBAY-DDI.pptx
│  │  └Rconference.Zhang_.Xiaohua.pptx
│  ├<2014R会议材料>
│  │  ├【批量下载】赵学敏等.zip
│  │  ├China-R-2014-BJ-DavidChiu.pdf
│  │  ├China-R-2014-BJ-Hadley-ggvis.pdf
│  │  ├China-R-2014-BJ-JingLiang.pptx
│  │  ├China-R-2014-BJ-JinZhihui.pdf
│  │  ├China-R-2014-BJ-KouQiang.pdf
│  │  ├China-R-2014-BJ-LiJian.pdf
│  │  ├China-R-2014-BJ-LinHui.pdf
│  │  ├China-R-2014-BJ-RenKun.pdf
│  │  ├China-R-2014-BJ-WangLiangbo.pdf
│  │  ├China-R-2014-BJ-WushWu.7z
│  │  ├China-R-2014-BJ-ZhangDan.pdf
│  │  └China-R-2014-BJ-ZhangYe.pptx
│  ├<PPV课网站资料>
│  │  ├3be994a2a04166fb0bfe88f0c50baa4d.jpg
│  │  ├eb8a49e664a04f77b113738394f96043.png
│  │  ├RCurl爬虫和Shiny包在游戏行业的应用.pdf
│  │  ├t_alibaba_data.csv
│  │  ├初级入门.rar
│  │  ├高级入门.rar
│  │  ├数据可视化.rar
│  │  ├数据挖掘比赛入门_以去年阿里天猫推荐比赛为例.docx
│  │  ├问题域研究.rar
│  │  └预备知识.rar
│  ├<R扩展包使用手册>
│  │  ├igraph.pdf
│  │  ├reshape2.pdf
│  │  ├Rwordseg_Vignette_CN.pdf
│  │  └tm.pdf
│  ├<R七种武器PPT>
│  │  ├R金融数据分析之quantmod包_01.pdf
│  │  ├R七种武器之交互化展示包shiny01.pdf
│  │  ├R七种武器之交互化展示包shiny02.pdf
│  │  ├R七种武器之数据加工厂plyr包01.pdf
│  │  ├R七种武器之数据加工厂plyr包02.pdf
│  │  └R七种武器之文本挖掘包tm_01.pdf
│  ├<数据库SQL>
│  │  └鸿鹄论坛_oracle四大宝典之1：Oracle Sql基础.pdf