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introduction to Rprogramming Hopkins
magnet:?xt=urn:btih:482da6e7772f72ae1beb8599d909d694b335bf75&dn=introduction to Rprogramming Hopkins
磁力链接详情
Hash值:
482da6e7772f72ae1beb8599d909d694b335bf75
点击数:
170
文件大小:
2.66 GB
文件数量:
306
创建日期:
2017-9-19 12:46
最后访问:
2024-9-21 14:44
访问标签:
introduction
to
Rprogramming
Hopkins
文件列表详情
4-Exploratory Data Analysis/5 - 2 - Air Pollution Case Study [40-35].mp4 72.01 MB
5-Reproducible Research/4 - 3 - Case Study- High Throughput Biology [30-51].mp4 50.56 MB
9-Data Product/4 - 6 - yhat (Part 1) (24-39).mp4 40.06 MB
7-Regression Models/3 - 2 - 02_02_b Dummy variables (27-08).mp4 35.23 MB
7-Regression Models/3 - 3 - 02_02_c Interactions (26-29).mp4 34.41 MB
9-Data Product/4 - 3 - Building R Packages Demo (18-00).mp4 31.99 MB
8-machine learning/2 - 6 - Covariate creation (17-31).mp4 22.77 MB
9-Data Product/4 - 7 - yhat (Part 2) (11-38).mp4 21.23 MB
5-Reproducible Research/1 - 7 - Structure of a Data Analysis (part 2) [17-41].mp4 21.04 MB
5-Reproducible Research/4 - 2 - Case Study- Air Pollution [14-12].mp4 20.91 MB
6-Statistical Inference/1 - 1 - 01_01_a Introduction, motivating examples (14-23).mp4 20.45 MB
7-Regression Models/3 - 1 - 02_02_a Multivariable regression examples (14-38).mp4 19.5 MB
7-Regression Models/2 - 9 - 01_07_c Prediction Intervals (14-13).mp4 18.96 MB
5-Reproducible Research/2 - 1 - Coding Standards in R [8-59].mp4 18.91 MB
9-Data Product/4 - 4 - R Classes and Methods (Part 1) (13-50).mp4 18.12 MB
7-Regression Models/4 - 8 - 03_03_b Poisson Regression Example (14-12).mp4 17.8 MB
6-Statistical Inference/2 - 5 - 02_01_b Gaussian (13-50).mp4 17.68 MB
9-Data Product/3 - 8 - RStudio Presenter 2 Authoring details (11-14).mp4 17.63 MB
8-machine learning/2 - 7 - Preprocessing with principal components analysis (14-07).mp4 17.4 MB
6-Statistical Inference/4 - 5 - 03_05_a Multiple testing (13-59).mp4 17.15 MB
9-Data Product/4 - 2 - R Packages (Part 2) (14-59).mp4 17.1 MB
8-machine learning/4 - 1 - Regularized regression (13-20).mp4 16.76 MB
4-Exploratory Data Analysis/5 - 1 - Clustering Case Study [14-51].mp4 16.76 MB
5-Reproducible Research/4 - 1 - Caching Computations [11-16].mp4 16.5 MB
2-R-programming/3 - 5 - Your First R Function [10-29].mp4 16.48 MB
7-Regression Models/2 - 8 - 01_07_b T Tests for Regression Coefficients (12-33).mp4 16.26 MB
8-machine learning/3 - 1 - Predicting with trees (12-51).mp4 16.18 MB
6-Statistical Inference/2 - 3 - 01_05_c Bayes_' Rule Example- Diagnostic Tests (12-52).mp4 16.06 MB
4-Exploratory Data Analysis/2 - 8 - Base Plotting Demonstration [16-56].mp4 16.04 MB
8-machine learning/2 - 8 - Predicting with Regression (12-22).mp4 15.8 MB
7-Regression Models/4 - 9 - 03_03_c Poisson Rate Models (12-53).mp4 15.8 MB
5-Reproducible Research/3 - 4 - Reproducible Research Checklist (part 2) [10-20].mp4 15.36 MB
7-Regression Models/4 - 6 - 03_02_c More on Odds (12-29).mp4 15.3 MB
5-Reproducible Research/1 - 6 - Structure of a Data Analysis (part 1) [12-29].mp4 14.9 MB
2-R-programming/3 - 6 - Coding Standards [8-59].mp4 14.81 MB
6-Statistical Inference/3 - 6 - 02_05_c example and credible intervals (11-04).mp4 14.56 MB
8-machine learning/3 - 5 - Model Based Prediction (11-39).mp4 14.55 MB
8-machine learning/2 - 9 - Predicting with Regression Multiple Covariates (11-12).mp4 14.5 MB
7-Regression Models/1 - 9 - 01_03_c Linear Least Squares Solved (11-33).mp4 14.41 MB
6-Statistical Inference/4 - 4 - 03_04_b Power continued (11-26).mp4 14.25 MB
8-machine learning/2 - 4 - Plotting predictors (10-39).mp4 14.21 MB
6-Statistical Inference/2 - 4 - 02_01_a Bernoulli and Binomial (11-13).mp4 14.18 MB
7-Regression Models/2 - 6 - 01_06_c Residual Variation (11-20).mp4 14.12 MB
5-Reproducible Research/1 - 8 - Organizing Your Analysis [11-05].mp4 14.12 MB
6-Statistical Inference/3 - 11 - 03_02_c Hypothesis testing example and binomial example (10-52).mp4 13.96 MB
7-Regression Models/1 - 11 - 01_04_b Regression to the Mean Example (10-46).mp4 13.92 MB
8-machine learning/1 - 6 - Types of errors (10-35).mp4 13.87 MB
6-Statistical Inference/1 - 9 - 01_04_b Correlation, Variances and IID RVs (11-03).mp4 13.85 MB
8-machine learning/2 - 5 - Basic preprocessing (10-52).mp4 13.6 MB
9-Data Product/2 - 19 - plotly.mp4 13.36 MB
7-Regression Models/3 - 12 - 02_05_b Variance inflation (10-33).mp4 13.3 MB
1-The Data Scientist’s Toolbox/3 - 4 - Experimental Design (15-59).mp4 13.28 MB
9-Data Product/4 - 5 - R Classes and Methods (Part 2) (11-19).mp4 13.28 MB
6-Statistical Inference/1 - 3 - 01_02_b Random variables, densities and pmfs (10-19).mp4 12.8 MB
6-Statistical Inference/3 - 9 - 03_02_a Introduction to hypothesis testing (9-57).mp4 12.63 MB
6-Statistical Inference/3 - 10 - 03_02_b Further discussion of hypothesis testing (9-58).mp4 12.6 MB
9-Data Product/2 - 8 - More advanced shiny discussion, reactivity (9-30).mp4 12.55 MB
5-Reproducible Research/2 - 8 - knitr (part 4) [9-21].mp4 12.47 MB
9-Data Product/2 - 17 - GoogleVis (9-34).mp4 12.45 MB
1-The Data Scientist’s Toolbox/2 - 1 - Command Line Interface (16-04).mp4 12.37 MB
8-machine learning/1 - 3 - Relative importance of steps (9-45).mp4 12.31 MB
3-gettting and cleaning data/2 - 1 - Reading from MySQL (14-44).mp4 12.23 MB
4-Exploratory Data Analysis/3 - 4 - ggplot2 (part 2) [13-53].mp4 12.19 MB
6-Statistical Inference/4 - 9 - 03_06_b Resampling the bootstrap (9-34).mp4 12.12 MB
6-Statistical Inference/3 - 3 - 02_04_c maximum likelihood (9-35).mp4 12.02 MB
7-Regression Models/2 - 12 - 02_01_c More Multivariable Least Squares (8-35).mp4 11.85 MB
6-Statistical Inference/4 - 3 - 03_04_a Power (9-15).mp4 11.75 MB
6-Statistical Inference/2 - 9 - 02_02_c Asymptotic Confidence Intervals (9-12).mp4 11.75 MB
6-Statistical Inference/2 - 6 - 02_01_c Poisson (9-44).mp4 11.75 MB
2-R-programming/2 - 2 - Overview and History of R [16-07].mp4 11.59 MB
6-Statistical Inference/4 - 6 - 03_05_b Multiple testing further discussion (11-23).mp4 11.54 MB
3-gettting and cleaning data/1 - 7 - Reading XML (12-39).mp4 11.51 MB
8-machine learning/3 - 2 - Bagging (9-13).mp4 11.45 MB
2-R-programming/5 - 5 - R Profiler (part 2) [10-26].mp4 11.23 MB
2-R-programming/1 - 5 - Writing Code - Setting Your Working Directory (Mac).mp4 11.21 MB
6-Statistical Inference/1 - 7 - 01_03_c Variances (8-51).mp4 11.15 MB
7-Regression Models/3 - 13 - 02_05_c Model comparison and search (8-05).mp4 11.14 MB
8-machine learning/1 - 5 - Prediction study design (9-05).mp4 11.13 MB
5-Reproducible Research/3 - 3 - Reproducible Research Checklist (part 1) [8-22].mp4 11.1 MB
7-Regression Models/2 - 5 - 01_06_b Properties of Residuals (8-48).mp4 11.03 MB
8-machine learning/1 - 2 - What is prediction- (8-39).mp4 10.98 MB
9-Data Product/2 - 3 - Shiny 1 Introduction to Shiny (8-36).mp4 10.89 MB
4-Exploratory Data Analysis/2 - 2 - Principles of Analytic Graphics [12-11].mp4 10.79 MB
6-Statistical Inference/4 - 10 - 03_06_c Permutation tests (8-23).mp4 10.7 MB
6-Statistical Inference/4 - 7 - 03_05_c Multiple testing case studies (9-03) .mp4 10.68 MB
6-Statistical Inference/3 - 2 - 02_04_b Likelihood example, binomial (8-24).mp4 10.64 MB
8-machine learning/4 - 3 - Forecasting.mp4 10.6 MB
8-machine learning/1 - 1 - Prediction motivation (8-26).mp4 10.49 MB
5-Reproducible Research/1 - 5 - Scripting Your Analysis [4-36].mp4 10.2 MB
6-Statistical Inference/4 - 2 - 03_03_b P-values some examples and the attained significance level (7-59).mp4 10.14 MB
8-machine learning/1 - 8 - Cross validation (8-20).mp4 10.1 MB
5-Reproducible Research/1 - 2 - Reproducible Research- Concepts and Ideas (part 1) [7-11].mp4 10.08 MB
9-Data Product/3 - 10 - Very quick introduction to gh-pages.mp4 10.07 MB
5-Reproducible Research/2 - 4 - R Markdown Demonstration [7-24].mp4 10.04 MB
6-Statistical Inference/1 - 10 - 01_04_c Sample Variance (8-17).mp4 10.03 MB
7-Regression Models/4 - 7 - 03_03_a Poisson Regression (8-15).mp4 9.91 MB
6-Statistical Inference/1 - 6 - 01_03_b Continuous Random Variables, Rules for Expected Values (8-18).mp4 9.91 MB
6-Statistical Inference/2 - 11 - 02_03_b T distribution and T intervals (evaluated in Quiz 3) (7-37).mp4 9.83 MB
6-Statistical Inference/2 - 7 - 02_02_a Limits LLN (7-25).mp4 9.82 MB
4-Exploratory Data Analysis/3 - 6 - ggplot2 (part 4) [10-38].mp4 9.78 MB
7-Regression Models/1 - 4 - 01_01_d Regression through the origin (7-37).mp4 9.7 MB
1-The Data Scientist’s Toolbox/1 - 1 - Series Motivation (12-03).mp4 9.6 MB
3-gettting and cleaning data/3 - 2 - Summarizing Data (11-37).mp4 9.56 MB
5-Reproducible Research/2 - 5 - knitr (part 1) [7-05].mp4 9.47 MB
5-Reproducible Research/3 - 10 - Evidence-based Data Analysis (part 5) [7-56].mp4 9.34 MB
8-machine learning/4 - 2 - Combining predictors (7-11).mp4 9.31 MB
9-Data Product/3 - 5 - Slidify more details (7-24).mp4 9.29 MB
2-R-programming/2 - 9 - Reading and Writing Data (part 1) [12-55].mp4 9.24 MB
4-Exploratory Data Analysis/2 - 6 - Base Plotting System (part 1) [11-20].mp4 9.21 MB
2-R-programming/5 - 4 - R Profiler (part 1) [10-39].mp4 9.17 MB
2-R-programming/2 - 3 - Getting Help [13-53].mp4 9.16 MB
7-Regression Models/3 - 11 - 02_05_a Some thoughts on model selection (6-38).mp4 9.13 MB
9-Data Product/4 - 1 - R Packages (Part 1) (7-11).mp4 9.07 MB
8-machine learning/3 - 4 - Boosting (7-08).mp4 9.07 MB
7-Regression Models/4 - 3 - 03_01_c Variances and Quasi Likelihood (7-05).mp4 9.01 MB
8-machine learning/2 - 3 - Training options (7-15).mp4 9.01 MB
3-gettting and cleaning data/4 - 1 - Editing Text Variables (10-46).mp4 8.98 MB
7-Regression Models/4 - 4 - 03_02_a Binary Data GLMs (7-11).mp4 8.93 MB
5-Reproducible Research/3 - 5 - Reproducible Research Checklist (part 3) [6-54].mp4 8.92 MB
3-gettting and cleaning data/1 - 9 - The data.table Package (11-18).mp4 8.89 MB
2-R-programming/1 - 4 - Writing Code - Setting Your Working Directory (Windows).mp4 8.87 MB
6-Statistical Inference/2 - 8 - 02_02_b CLT (6-55).mp4 8.79 MB
8-machine learning/3 - 3 - Random Forests (6-49).mp4 8.73 MB
4-Exploratory Data Analysis/3 - 5 - ggplot2 (part 3) [9-47].mp4 8.68 MB
8-machine learning/1 - 4 - In and out of sample errors (6-57).mp4 8.67 MB
9-Data Product/3 - 7 - RStudio Presenter 1 Introduction and getting started (4-59).mp4 8.61 MB
3-gettting and cleaning data/3 - 3 - Creating New Variables (10-32).mp4 8.5 MB
9-Data Product/2 - 16 - rCharts mapping and discussion (5-32).mp4 8.44 MB
5-Reproducible Research/2 - 9 - Introduction to Peer Assessment 1.mp4 8.43 MB
7-Regression Models/2 - 2 - 01_05_b Interpreting Regression Coefficients (6-28).mp4 8.43 MB
6-Statistical Inference/3 - 4 - 02_05_a Introduction to Bayesian analysis (6-42).mp4 8.43 MB
2-R-programming/4 - 6 - Debugging Tools (part 1) [9-26].mp4 8.37 MB
4-Exploratory Data Analysis/2 - 5 - Plotting Systems in R [9-34].mp4 8.33 MB
8-machine learning/2 - 1 - Caret package (6-16).mp4 8.23 MB
6-Statistical Inference/3 - 7 - 03_01_a Two group intervals, T intervals with a common variance (6-20).mp4 8.2 MB
5-Reproducible Research/3 - 1 - Communicating Results [6-54].mp4 8.2 MB
6-Statistical Inference/1 - 2 - 01_02_a Basic probability (6-19).mp4 8.13 MB
2-R-programming/2 - 6 - Data Types (part 3) [11-51].mp4 8.12 MB
6-Statistical Inference/3 - 8 - 03_01_b Two group T test examples (6-17).mp4 8.06 MB
6-Statistical Inference/4 - 1 - 03_03_a P-values, introduction (6-01).mp4 7.98 MB
7-Regression Models/4 - 2 - 03_01_b GLM Examples (6-21).mp4 7.9 MB
5-Reproducible Research/2 - 3 - R Markdown [6-35].mp4 7.85 MB
8-machine learning/1 - 9 - What data should you use- (6-01).mp4 7.77 MB
6-Statistical Inference/1 - 5 - 01_03_a Expected Values, Discrete Random Variables (5-51).mp4 7.71 MB
1-The Data Scientist’s Toolbox/3 - 1 - Types of Questions (9-09).mp4 7.67 MB
6-Statistical Inference/4 - 8 - 03_06_a Resampling the jackknife (6-01).mp4 7.66 MB
6-Statistical Inference/1 - 4 - 01_02_c Distribution functions and quantiles (6-06).mp4 7.64 MB
2-R-programming/3 - 7 - Scoping Rules (part 1) [10-32].mp4 7.6 MB
7-Regression Models/2 - 3 - 01_05_c Statistical Regression Models Examples (6-00).mp4 7.58 MB
9-Data Product/2 - 15 - rCharts more examples (5-40).mp4 7.58 MB
3-gettting and cleaning data/1 - 3 - Components of Tidy Data (9-25).mp4 7.57 MB
7-Regression Models/3 - 9 - 02_04_b More on diagnostics (5-18).mp4 7.56 MB
5-Reproducible Research/1 - 3 - Reproducible Research- Concepts and Ideas (part 2) [5-27].mp4 7.51 MB
7-Regression Models/3 - 4 - 02_03_a Multivariable simulation exercises (5-42).mp4 7.5 MB
7-Regression Models/1 - 3 - 01_01_c Least squares continued (5-38).mp4 7.49 MB
7-Regression Models/2 - 1 - 01_05_a Statistical Linear Regression Models (5-58).mp4 7.41 MB
9-Data Product/3 - 1 - Presenting Data Analysis Writing a Data Report (3-18).mp4 7.35 MB
7-Regression Models/1 - 7 - 01_03_a Linear Least Squares (6-01).mp4 7.29 MB
4-Exploratory Data Analysis/3 - 7 - ggplot2 (part 5) [8-11].mp4 7.26 MB
5-Reproducible Research/2 - 2 - Markdown [5-15].mp4 7.25 MB
3-gettting and cleaning data/3 - 4 - Reshaping Data (9-13).mp4 7.21 MB
6-Statistical Inference/2 - 2 - 01_05_b Bayes_' Rule (5-54).mp4 7.21 MB
9-Data Product/3 - 2 - Slidify intro (5-32).mp4 7.19 MB
7-Regression Models/1 - 2 - 01_01_b Basic least squares (5-41).mp4 7.15 MB
4-Exploratory Data Analysis/4 - 7 - Dimension Reduction (part 2) [9-26].mp4 7.15 MB
8-machine learning/2 - 2 - Data slicing (5-40).mp4 7 MB
2-R-programming/3 - 10 - Dates and Times [10-29].mp4 6.99 MB
4-Exploratory Data Analysis/2 - 3 - Exploratory Graphs (part 1) [9-28].mp4 6.89 MB
9-Data Product/2 - 9 - More advanced shiny, the reactive function (5-50).mp4 6.82 MB
7-Regression Models/1 - 6 - 01_02_b Normalization and Correlation (5-22).mp4 6.75 MB
1-The Data Scientist’s Toolbox/1 - 3 - Getting Help (8-52).mp4 6.71 MB
6-Statistical Inference/3 - 5 - 02_05_b posteriors (5-21).mp4 6.65 MB
2-R-programming/2 - 5 - Data Types (part 2) [9-45].mp4 6.6 MB
2-R-programming/2 - 8 - Subsetting (part 2) [10-18].mp4 6.58 MB
2-R-programming/2 - 10 - Reading and Writing Data (part 2) [9-30].mp4 6.57 MB
2-R-programming/2 - 4 - Data Types (part 1) [9-26].mp4 6.57 MB
9-Data Product/2 - 7 - Shiny 5 Discussion (4-48).mp4 6.51 MB
6-Statistical Inference/3 - 1 - 02_04_a Introduction to likelihoods (5-05).mp4 6.49 MB
3-gettting and cleaning data/4 - 3 - Regular Expressions II (8-00).mp4 6.46 MB
2-R-programming/3 - 3 - Functions (part 1) [9-17].mp4 6.46 MB
3-gettting and cleaning data/2 - 4 - Reading From APIs (7-57).mp4 6.37 MB
2-R-programming/5 - 6 - Scoping Rules (part 3) [9-21].mp4 6.35 MB
9-Data Product/2 - 11 - More advanced shiny, odds and ends (4-55).mp4 6.32 MB
2-R-programming/4 - 4 - split [9-09].mp4 6.16 MB
4-Exploratory Data Analysis/2 - 10 - Graphics Devices in R (part 2) [7-31].mp4 6.14 MB
9-Data Product/2 - 12 - Manipulate (4-49).mp4 6.12 MB
5-Reproducible Research/2 - 7 - knitr (part 3) [4-46].mp4 6.12 MB
2-R-programming/4 - 1 - lapply [9-23].mp4 6.1 MB
8-machine learning/1 - 7 - Receiver Operating Characteristic (5-03).mp4 6.07 MB
7-Regression Models/3 - 8 - 02_04_a Residuals (4-48).mp4 5.98 MB
9-Data Product/2 - 4 - Shiny 2 basic html and getting input (4-56).mp4 5.98 MB
3-gettting and cleaning data/1 - 2 - Raw and Processed Data (7-07).mp4 5.95 MB
4-Exploratory Data Analysis/3 - 3 - ggplot2 (part 1) [6-26].mp4 5.91 MB
3-gettting and cleaning data/1 - 4 - Downloading Files (7-09).mp4 5.9 MB
4-Exploratory Data Analysis/4 - 6 - Dimension Reduction (part 1) [7-55].mp4 5.89 MB
5-Reproducible Research/1 - 1 - Introduction.mp4 5.86 MB
9-Data Product/2 - 18 - shinyApps.io.mp4 5.85 MB
9-Data Product/2 - 14 - rCharts introduction (4-45).mp4 5.83 MB
2-R-programming/5 - 1 - The str Function [6-08].mp4 5.78 MB
7-Regression Models/3 - 7 - 02_03_d Simulation examples finished (4-22).mp4 5.77 MB
9-Data Product/3 - 9 - RStudio Presenter 3 Discussion and comparison with Slidify (4-13).mp4 5.75 MB
2-R-programming/3 - 8 - Scoping Rules (part 2) [8-34].mp4 5.7 MB
3-gettting and cleaning data/3 - 5 - Merging Data (6-19).mp4 5.69 MB
3-gettting and cleaning data/2 - 3 - Reading from The Web (6-47).mp4 5.59 MB
5-Reproducible Research/3 - 9 - Evidence-based Data Analysis (part 4) [4-47].mp4 5.54 MB
7-Regression Models/1 - 1 - 01_01_a Introduction to regression (4-10).mp4 5.54 MB
9-Data Product/3 - 4 - Slidify customization (4-09).mp4 5.5 MB
2-R-programming/3 - 2 - Control Structures (part 2) [8-11].mp4 5.5 MB
3-gettting and cleaning data/2 - 2 - Reading from HDF5 (6-45).mp4 5.47 MB
4-Exploratory Data Analysis/4 - 10 - Working with Color in R Plots (part 2) [7-41].mp4 5.46 MB
9-Data Product/2 - 10 - More advanced shiny, conditional execution of reactive statements (4-16).mp4 5.42 MB
4-Exploratory Data Analysis/2 - 7 - Base Plotting System (part 2) [6-56].mp4 5.41 MB
5-Reproducible Research/2 - 6 - knitr (part 2) [4-11].mp4 5.4 MB
8-machine learning/4 - 4 - Unsupervised Prediction (4-24).mp4 5.4 MB
2-R-programming/4 - 8 - Debugging Tools (part 3) [11-51].mp4 5.37 MB
4-Exploratory Data Analysis/4 - 3 - Hierarchical Clustering (part 3) [7-34].mp4 5.36 MB
2-R-programming/5 - 2 - Simulation (part 1) [7-47].mp4 5.34 MB
6-Statistical Inference/2 - 10 - 02_03_a Chi Squared Distribution (4-05).mp4 5.31 MB
6-Statistical Inference/1 - 8 - 01_04_a Basic Independence (4-13).mp4 5.28 MB
5-Reproducible Research/3 - 2 - RPubs [3-21].mp4 5.22 MB
7-Regression Models/1 - 8 - 01_03_b Linear Least Squares Special Cases (4-22).mp4 5.21 MB
2-R-programming/1 - 1 - Installing R on Windows.mp4 5.12 MB
1-The Data Scientist’s Toolbox/1 - 16 - Installing R on Windows (3-20) {Roger Peng}.mp4 5.12 MB
9-Data Product/2 - 5 - Shiny 3 Creating a very basic prediction function (4-12).mp4 5.07 MB
4-Exploratory Data Analysis/4 - 8 - Dimension Reduction (part 3) [6-42].mp4 5.06 MB
7-Regression Models/1 - 10 - 01_04_a Regression to the Mean (3-46).mp4 5.04 MB
4-Exploratory Data Analysis/4 - 1 - Hierarchical Clustering (part 1) [7-21].mp4 5.03 MB
5-Reproducible Research/1 - 4 - Reproducible Research- Concepts and Ideas (part 3) [3-26].mp4 4.99 MB
3-gettting and cleaning data/1 - 1 - Obtaining Data Motivation (5-38).mp4 4.98 MB
6-Statistical Inference/2 - 1 - 01_05_a Conditional probability (4-01).mp4 4.97 MB
2-R-programming/4 - 2 - apply [7-21].mp4 4.96 MB
4-Exploratory Data Analysis/3 - 2 - Lattice Plotting System (part 2) [6-12].mp4 4.96 MB
3-gettting and cleaning data/3 - 1 - Subsetting and Sorting (6-51).mp4 4.94 MB
4-Exploratory Data Analysis/3 - 1 - Lattice Plotting System (part 1) [6-22].mp4 4.92 MB
2-R-programming/4 - 7 - Debugging Tools (part 2) [6-25].mp4 4.92 MB
5-Reproducible Research/3 - 8 - Evidence-based Data Analysis (part 3) [4-25].mp4 4.86 MB
2-R-programming/3 - 4 - Functions (part 2) [7-13].mp4 4.86 MB
1-The Data Scientist’s Toolbox/2 - 4 - Creating a Github Repository (5-51).mp4 4.84 MB
7-Regression Models/3 - 5 - 02_03_b More simulation exercises (3-53).mp4 4.84 MB
4-Exploratory Data Analysis/2 - 9 - Graphics Devices in R (part 1) [5-34].mp4 4.84 MB
2-R-programming/3 - 1 - Control Structures (part 1) [7-10].mp4 4.82 MB
4-Exploratory Data Analysis/4 - 11 - Working with Color in R Plots (part 3) [6-39].mp4 4.8 MB
1-The Data Scientist’s Toolbox/2 - 7 - Installing R Packages (5-37).mp4 4.8 MB
2-R-programming/5 - 3 - Simulation (part 2) [7-02].mp4 4.8 MB
3-gettting and cleaning data/4 - 4 - Working with Dates (6-02).mp4 4.7 MB
1-The Data Scientist’s Toolbox/3 - 2 - What is Data- (5-15).mp4 4.68 MB
2-R-programming/2 - 7 - Subsetting (part 1) [7-01].mp4 4.62 MB
3-gettting and cleaning data/1 - 8 - Reading JSON (5-03).mp4 4.59 MB
5-Reproducible Research/3 - 6 - Evidence-based Data Analysis (part 1) [3-51].mp4 4.54 MB
1-The Data Scientist’s Toolbox/2 - 5 - Basic Git Commands (5-52).mp4 4.43 MB
1-The Data Scientist’s Toolbox/1 - 2 - The Data Scientist-'s Toolbox (5-09).mp4 4.41 MB
3-gettting and cleaning data/1 - 5 - Reading Local Files (4-55).mp4 4.39 MB
7-Regression Models/1 - 5 - 01_02_a Basic Notation and Background (3-26).mp4 4.31 MB
3-gettting and cleaning data/4 - 2 - Regular Expressions I (5-16).mp4 4.15 MB
5-Reproducible Research/3 - 7 - Evidence-based Data Analysis (part 2) [3-34].mp4 4.1 MB
2-R-programming/2 - 1 - Introduction.mp4 4.09 MB
1-The Data Scientist’s Toolbox/2 - 2 - Introduction to Git (4-49).mp4 4.02 MB
1-The Data Scientist’s Toolbox/1 - 15 - Install R on a Mac (2-02) {Roger Peng}.mp4 3.98 MB
2-R-programming/1 - 2 - Installing R on a Mac.mp4 3.98 MB
4-Exploratory Data Analysis/2 - 1 - Introduction.mp4 3.98 MB
4-Exploratory Data Analysis/4 - 2 - Hierarchical Clustering (part 2) [5-24].mp4 3.97 MB
3-gettting and cleaning data/2 - 5 - Reading From Other Sources (4-44).mp4 3.93 MB
1-The Data Scientist’s Toolbox/1 - 4 - Finding Answers (4-35).mp4 3.82 MB
1-The Data Scientist’s Toolbox/3 - 3 - What About Big Data- (4-15).mp4 3.82 MB
4-Exploratory Data Analysis/2 - 4 - Exploratory Graphs (part 2) [5-13].mp4 3.8 MB
4-Exploratory Data Analysis/4 - 4 - K-Means Clustering (part 1) [5-46].mp4 3.74 MB
7-Regression Models/2 - 10 - 02_01_a Multivariate Regression (2-47).mp4 3.68 MB
7-Regression Models/3 - 6 - 02_03_c More simulation examples 2 (2-52).mp4 3.56 MB
7-Regression Models/2 - 4 - 01_06_a Residuals (2-51).mp4 3.52 MB
3-gettting and cleaning data/1 - 6 - Reading Excel Files (3-55).mp4 3.46 MB
9-Data Product/2 - 2 - Motivating Shiny (1-49).mp4 3.4 MB
9-Data Product/3 - 3 - Slidify working it out (2-01).mp4 3.37 MB
9-Data Product/3 - 6 - Slidify reminder about knitting R (1-52).mp4 3.33 MB
7-Regression Models/4 - 1 - 03_01_a Generalized Linear Models (2-32).mp4 3.26 MB
2-R-programming/4 - 5 - mapply [4-46].mp4 3.21 MB
1-The Data Scientist’s Toolbox/2 - 3 - Introduction to Github (3-53).mp4 3.18 MB
9-Data Product/2 - 6 - Shiny 4 Working with images (2-39).mp4 3.17 MB
2-R-programming/2 - 11 - Introduction to swirl.mp4 3.17 MB
3-gettting and cleaning data/4 - 5 - Data Resources (3-33).mp4 3.03 MB
4-Exploratory Data Analysis/4 - 9 - Working with Color in R Plots (part 1) [4-08].mp4 2.97 MB
4-Exploratory Data Analysis/4 - 5 - K-Means Clustering (part 2) [4-26].mp4 2.94 MB
4-Exploratory Data Analysis/4 - 12 - Working with Color in R Plots (part 4) [3-35].mp4 2.73 MB
1-The Data Scientist’s Toolbox/1 - 13 - Installing Rstudio (1-36) {Roger Peng}.mp4 2.61 MB
2-R-programming/1 - 3 - Installing R Studio (Mac).mp4 2.61 MB
2-R-programming/3 - 9 - Vectorized Operations [3-46].mp4 2.49 MB
1-The Data Scientist’s Toolbox/1 - 14 - Installing Outside Software on Mac (OS X Mavericks) [1-19].mp4 2.18 MB
2-R-programming/1 - 6 - Installing Outside Software (Mac OS X Mavericks).mp4 2.18 MB
1-The Data Scientist’s Toolbox/2 - 8 - Installing Rtools (2-29).mp4 2.18 MB
2-R-programming/4 - 3 - tapply [3-17].mp4 2.17 MB
9-Data Product/2 - 13 - Intro to rCharts and GoogleVis (1-01).mp4 1.94 MB
1-The Data Scientist’s Toolbox/2 - 6 - Basic Markdown (2-22).mp4 1.76 MB
7-Regression Models/2 - 7 - 01_07_a Inference in Regression (1-28).mp4 1.76 MB
1-The Data Scientist’s Toolbox/1 - 5 - R Programming Overview (2-12).mp4 1.73 MB
1-The Data Scientist’s Toolbox/1 - 10 - Regression Models Overview (1-46).mp4 1.5 MB
9-Data Product/2 - 1 - Introduction to Data Products (1-05).mp4 1.37 MB
7-Regression Models/2 - 13 - 02_01_d Multivariable Linear Models Interpretation (9-46).mp4 1.34 MB
1-The Data Scientist’s Toolbox/1 - 11 - Practical Machine Learning Overview (1-31).mp4 1.27 MB
1-The Data Scientist’s Toolbox/1 - 6 - Getting Data Overview (1-34).mp4 1.22 MB
1-The Data Scientist’s Toolbox/1 - 12 - Building Data Products Overview (1-19).mp4 1.16 MB
1-The Data Scientist’s Toolbox/1 - 7 - Exploratory Data Analysis Overview (1-21).mp4 1.07 MB
5-Reproducible Research/3 - 11 - Introduction to Peer Assessment 2.mp4 1.06 MB
1-The Data Scientist’s Toolbox/1 - 8 - Reproducible Research Overview (1-27).mp4 1.06 MB
1-The Data Scientist’s Toolbox/1 - 9 - Statistical Inference Overview (1-06).mp4 891.93 KB
7-Regression Models/4 - 5 - 03_02_b GLMs and Odds (14-03).mp4 356.36 KB
7-Regression Models/3 - 10 - 02_04_c Residuals and diagnostics examples (6-32).mp4 169.32 KB
7-Regression Models/2 - 11 - 02_01_b Multivariable Least Squares (12-59).mp4 118.33 KB
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