magnet:?xt=urn:btih:25BB3D8A394EC05B76C7157E5620547110BE23E9
B4. Applying Linear Algebra with R (Brandon Strain, 2020)/8. Implementing Matrix Decomposition/2. Demo - Implementing Matrix Decomposition.mp4 32.3 MBB4. Applying Linear Algebra with R (Brandon Strain, 2020)/4. Getting Weird - Inverting, Transposing, and Row Equivalence/1. Getting Weird.mp4 24.5 MBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/3. Making Predictions with Monte Carlo/5. Predictions on Commodities Data.mp4 24.0 MBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/3. Making Predictions with Monte Carlo/4. Point Estimates and Confidence Intervals.mp4 22.1 MBB4. Applying Linear Algebra with R (Brandon Strain, 2020)/7. Calculating the kth Item in a Series/3. Demo - Calculating the kth Item in a Series.mp4 21.0 MBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/5. Performing Dimensional Analysis for Non-linear Data/2. Demo - Manifold Learning Using Metric and Non-metric MDS.mp4 21.0 MBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/3. Performing Predictive Analytics Using MASS Models/4. Demo - Linear Discriminant Analysis (LDA) and Visualization.mp4 20.4 MBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/3. Performing Predictive Analytics Using MASS Models/8. Demo - Robust Regression Using the Boston Housing Dataset.mp4 20.4 MBB4. Applying Linear Algebra with R (Brandon Strain, 2020)/2. Working with Vectors and Matrices in R/1. Working with Vectors and Matrices in R.mp4 20.3 MBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/3. Implementing Bootstrap Methods for Summary Statistics/2. Demo - Performing Bootstrapping on Real Data.mp4 20.1 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/5. Implementing Local Search and Optimizations/04. Demo - 8 Queens - Calculating Number of Attacks.mp4 20.0 MBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/3. Implementing Bootstrap Methods for Summary Statistics/1. Demo - Bootstrap Statistics and Sample Statistics.mp4 19.8 MBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/3. Making Predictions with Monte Carlo/3. Simulating Random Walk with MC.mp4 19.6 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/3. Applying Numerical Methods to Solve Problems/9. Demo - Eulers Method and Numerical Instability.mp4 19.5 MBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/5. Performing Dimensional Analysis for Non-linear Data/3. Demo - Manifold Learning Using t-SNE, Isomap, and LLE.mp4 17.5 MBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/4. Performing Dimensional Analysis for Categorical Data/3. Demo - Performing Linear Discriminant Analysis on Glass Data.mp4 17.4 MBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/2. Performing Qualitative and Quantitative Analysis Using MASS Datasets/08. Demo - Quantitative and Qualitative Analysis of Bi.mp4 17.3 MBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/4. Implementing Multi-state Models in R/09. Demo - Visualizing and Interpreting State Occupancy Probabilities.mp4 17.3 MBB4. Applying Linear Algebra with R (Brandon Strain, 2020)/5. Solving Linear Equations/1. Solving Linear Equations.mp4 17.2 MBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/4. Applying Mathematical Models in R/7. Demo - Setting up Helper Functions to Solve the 8 Queens Optimization Prob.mp4 17.0 MBB4. Applying Linear Algebra with R (Brandon Strain, 2020)/9. Using Least Squares Calculations/2. Demo - Using Least Squares Calculations.mp4 16.9 MBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/2. Understanding the Importance of Reducing Complexity in Data/08. Demo - Exploring the Boston Housing Dataset.mp4 16.3 MBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/4. Implementing Multi-state Models in R/07. Demo - Understanding the Multi-state Model Data.mp4 15.9 MBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/3. Performing Predictive Analytics Using MASS Models/7. Demo - Fitting a Robust Linear Model.mp4 15.9 MBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/4. Implementing Multi-state Models in R/08. Demo - Modeling Transition Probabilities and Simulating Outcomes.mp4 15.9 MBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/4. Implementing Statistical Models/8. Demo - Accuracy, Sensitivity, and Specificity of the Logistic Regression Model.mp4 15.9 MBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/3. Performing Dimensional Analysis for Continuous Data/3. Demo - Performing Principal Component Analysis.mp4 15.8 MBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/5. Implementing Bayesian AB Testing/07. Demo - Modelling Outcomes and Priors for the Bayes AB Test.mp4 15.8 MBB4. Applying Linear Algebra with R (Brandon Strain, 2020)/6. Understanding and Calculating Eigenvalues and Eigenvectors/1. Understanding and Calculating Eigenvalues and Eigenvectors.mp4 15.7 MBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/3. Solving Problems Using Statistical Inference/9. Demo - Two-way ANOVA.mp4 15.7 MBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/4. Implementing Statistical Models/4. Demo - Performing Linear Regression and Interpretings Results.mp4 15.6 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/3. Applying Numerical Methods to Solve Problems/1. Demo - Linear and Constant Interpolation.mp4 15.5 MBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/5. Performing Dimensional Analysis for Non-linear Data/1. Manifold Learning.mp4 15.4 MBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/3. Solving Problems Using Statistical Inference/3. Demo - Two Sample T-test.mp4 15.1 MBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/4. Implementing Multi-state Models in R/01. Multi-state Models.mp4 15.0 MBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/2. Understanding the Importance of Reducing Complexity in Data/10. Demo - Performing Stepwise and Kitchen Sink Regression.mp4 15.0 MBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/4. Using Monte Carlo for Value at Risk/3. Parametric and Historical VaR.mp4 14.9 MBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/4. Using Monte Carlo for Value at Risk/4. Monte Carlo VaR.mp4 14.8 MBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/4. Solving Differential Equations/4. Demo - Solving DAEs - An Auto-catalytic Chemical Reaction.mp4 14.7 MBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/2. Understanding Statistical and Mathematical Models/8. Demo - Querying and Setting Metadata Using the Meta Function.mp4 14.6 MBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/3. Implementing Bootstrap Methods for Summary Statistics/4. Demo - Bootstrapping Multiple Statistics.mp4 14.6 MBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/2. Getting Started with Bootstrapping in R/08. Demo - The Central Limit Theorem with Different Distributions.mp4 14.6 MBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/4. Performing Dimensional Analysis for Categorical Data/2. Demo - Exploring and Preparing Data for Linear Discriminant Analysis.mp4 14.5 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/4. Working with Graphs Using Numerical Techniques/09. Demo - Calculating Shortest Distances.mp4 14.4 MBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/2. Getting Started with Bootstrapping in R/12. Bootstrapped Confidence Intervals.mp4 14.2 MBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/5. Utilizing MC for AB Testing/4. AB Testing with Monte Carlo.mp4 13.8 MBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/2. Getting Started with Bootstrapping in R/04. Normally Distributed Data - Estimating Mean.mp4 13.7 MBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/3. Solving Problems Using Statistical Inference/7. Demo - One-way ANOVA.mp4 13.6 MBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/4. Solving Differential Equations/6. Demo - Solving PDEs - The Diffusion Equation for Heat Transfer.mp4 13.5 MBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/2. Understanding Monte Carlo Basics/2. MC Basics in R.mp4 13.5 MBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/3. Implementing Bootstrap Methods for Summary Statistics/7. Demo - Performing Bayesian Bootstrapping.mp4 13.5 MBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/3. Solving Problems Using Statistical Inference/4. Demo - Type I and Type II Errors.mp4 13.2 MBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/4. Implementing Bootstrap Methods for Regression Models/5. Demo - Estimating Coefficients Using Bootstrapping.mp4 13.1 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/5. Implementing Local Search and Optimizations/01. Solutions Approaches to N-Queens.mp4 13.0 MBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/2. Getting Started with Bootstrapping in R/11. Introducing Bootstrapping.mp4 12.9 MBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/4. Performing Dimensional Analysis for Categorical Data/1. Linear Discriminant Analysis and Quadratic Discriminant Analysis.mp4 12.8 MBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/2. Understanding Statistical and Mathematical Models/3. Understanding Mathematical Models and Statistical Models.mp4 12.8 MBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/4. Solving Differential Equations/7. Demo - Solving DDEs - Infectious Disease Modeling.mp4 12.8 MBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/5. Implementing Bayesian AB Testing/02. Distributions and Statistical Tests.mp4 12.7 MBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/2. Getting Started with Differential Equations/11. Modeling Financial Assets Using PDEs.mp4 12.6 MBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/3. Performing Dimensional Analysis for Continuous Data/1. Principal Components Analysis.mp4 12.6 MBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/5. Applying Statistical Models in R/7. Demo - Two Sample T-test.mp4 12.6 MBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/4. Applying Mathematical Models in R/5. The 8 Queens Problem.mp4 12.5 MBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/2. Understanding Statistical Summaries/04. Hypothesis Testing.mp4 12.5 MBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/4. Implementing Bootstrap Methods for Regression Models/4. Demo - Estimating R2 of Regression Models Using Bootstrapping.mp4 12.5 MBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/2. Understanding the Importance of Reducing Complexity in Data/05. Overfitting and the Bias-variance Trade-off.mp4 12.4 MBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/2. Understanding the Importance of Reducing Complexity in Data/03. The Curse of Dimensionality.mp4 12.4 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/3. Applying Numerical Methods to Solve Problems/2. Demo - Linear and Polynomial Extrapolation.mp4 12.4 MBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/4. Solving Differential Equations/1. Demo - Solving ODEs - The Population Growth Model.mp4 12.2 MBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/2. Understanding Monte Carlo Basics/3. Rolling the Dice.mp4 12.2 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/6. Implementing Integration and Differentiation/08. Demo - Using the ODE Solver to Solve Differential Equations.mp4 12.2 MBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/4. Applying Mathematical Models in R/8. Demo - Applying Local Search Optimization to Solve the Eight Queens Proble.mp4 12.1 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/5. Implementing Local Search and Optimizations/07. Objective Constraints and Decision Variables.mp4 12.0 MBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/3. Solving Problems Using Statistical Inference/2. Demo - One Sample T-test and Z-test.mp4 12.0 MBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/5. Applying Statistical Models in R/4. Demo - Exploring the Automobile Dataset.mp4 12.0 MBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/3. Performing Dimensional Analysis for Continuous Data/4. Demo - Regression Using Principal Components.mp4 11.9 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/6. Implementing Integration and Differentiation/09. Demo - Solving Verhulsts Equation.mp4 11.9 MBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/4. Implementing Multi-state Models in R/10. Demo - Modeling Survival Analysis.mp4 11.9 MBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/4. Using Monte Carlo for Value at Risk/2. Data Preparation.mp4 11.8 MBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/3. Solving Problems Using Statistical Inference/6. Demo - Interpreting the Results of Chi2 Analysis.mp4 11.8 MBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/4. Applying Mathematical Models in R/3. Demo - Solving Differential Equations.mp4 11.7 MBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/2. Getting Started with Bootstrapping in R/06. Data with Any Distribution - Estimating Mean and Confidence Intervals.mp4 11.7 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/4. Working with Graphs Using Numerical Techniques/06. Demo - Defining and Configuring Graphs.mp4 11.7 MBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/5. Applying Statistical Models in R/5. Demo - One Sample T-test.mp4 11.6 MBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/3. Performing Dimensional Analysis for Continuous Data/5. Demo - Principal Components Regression.mp4 11.6 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/6. Implementing Integration and Differentiation/03. Verhulsts Equation for Population Growth.mp4 11.5 MBB4. Applying Linear Algebra with R (Brandon Strain, 2020)/3. Understanding Operations on Matrices/1. Understanding Operations on Matrices.mp4 11.4 MBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/3. Solving Problems Using Statistical Inference/5. Demo - Performing Chi2 Analysis.mp4 11.4 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/3. Applying Numerical Methods to Solve Problems/4. Demo - Iterative Techniques - Jacobi Method to Solve Linear Equations.mp4 11.3 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/2. Understanding Numerical Methods/9. Gaussian Elimination and Jacobi Method.mp4 11.2 MBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/2. Getting Started with Differential Equations/05. Verhulsts Equation of Population Growth.mp4 11.2 MBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/4. Implementing Bootstrap Methods for Regression Models/6. Demo - Case Resampling and Residual Resampling Using the Boot() Method.mp4 11.2 MBB4. Applying Linear Algebra with R (Brandon Strain, 2020)/8. Implementing Matrix Decomposition/1. Implementing Matrix Decomposition.mp4 10.9 MBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/4. Solving Differential Equations/2. Demo - Solving ODEs - Van Der Pols Equation.mp4 10.9 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/6. Implementing Integration and Differentiation/07. Demo - Performing Integration.mp4 10.8 MBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/3. Making Predictions with Monte Carlo/2. Random Walk.mp4 10.8 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/3. Applying Numerical Methods to Solve Problems/6. Demo - Discretizing Continuous Data.mp4 10.7 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/5. Implementing Local Search and Optimizations/06. Demo - 8 Queens - Solution Using Local Search Techniques.mp4 10.7 MBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/4. Applying Mathematical Models in R/4. Demo - Solving Verhulsts Equation for Population Growth.mp4 10.7 MBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/3. Understanding Types of Differential Equations/3. Partial Differential Equations.mp4 10.6 MBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/2. Performing Qualitative and Quantitative Analysis Using MASS Datasets/05. Hypothesis Testing Using t-tests.mp4 10.5 MBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/2. Getting Started with Bootstrapping in R/09. Demo - The Central Limit Theorem on Real Data.mp4 10.5 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/4. Working with Graphs Using Numerical Techniques/04. Graph Representations.mp4 10.4 MBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/5. Performing Dimensional Analysis for Non-linear Data/4. Demo - Kernel PCA for Non-linearly Separable Data.mp4 10.4 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/3. Applying Numerical Methods to Solve Problems/8. Demo - Approximating Derivate Calculations.mp4 10.4 MB
B3. Performing Dimension Analysis with R (Janani Ravi, 2020)/exercise.7z 10.4 MBB4. Applying Linear Algebra with R (Brandon Strain, 2020)/7. Calculating the kth Item in a Series/2. Difference Equations.mp4 10.3 MBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/3. Solving Problems Using Statistical Inference/1. Demo - Preprocessing Data.mp4 10.2 MBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/4. Implementing Statistical Models/7. Demo - Performing Logistic Regression.mp4 10.0 MBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/5. Applying Statistical Models in R/8. Demo - Paired Sample T-test and Z-test.mp4 10.0 MBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/4. Applying Mathematical Models in R/6. Local Search Optimization Techniques.mp4 9.8 MBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/2. Understanding Statistical and Mathematical Models/4. Mathematical Models and Statistical Models - Differences and Applicati.mp4 9.8 MBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/5. Utilizing MC for AB Testing/2. Two Sample t-test.mp4 9.8 MBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/3. Understanding Types of Differential Equations/1. Ordinary Differential Equations.mp4 9.8 MBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/2. Understanding Statistical Summaries/09. One-way ANOVA - Assumptions and Alternatives.mp4 9.8 MBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/4. Applying Mathematical Models in R/2. Demo - Calculating the Derivative of a Function.mp4 9.8 MBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/3. Understanding Types of Differential Equations/7. Infectious Disease Modeling.mp4 9.8 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/4. Working with Graphs Using Numerical Techniques/05. Shortest Path Algorithms.mp4 9.8 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/6. Implementing Integration and Differentiation/05. Demo - Calculating Derivatives.mp4 9.8 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/6. Implementing Integration and Differentiation/02. Interpreting Derivatives.mp4 9.7 MBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/4. Implementing Multi-state Models in R/02. Survival Models.mp4 9.6 MBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/2. Understanding Statistical and Mathematical Models/5. Data and Metadata.mp4 9.5 MBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/4. Implementing Statistical Models/3. Demo - Exploring Data for Regression Analysis.mp4 9.5 MBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/5. Applying Statistical Models in R/2. Understanding Hypothesis Testing.mp4 9.4 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/3. Applying Numerical Methods to Solve Problems/7. Demo - Rounding Errors and Approximation Errors.mp4 9.4 MBB4. Applying Linear Algebra with R (Brandon Strain, 2020)/exercise.7z 9.4 MBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/3. Implementing Bootstrap Methods for Summary Statistics/5. Introducing the Bayesian Bootstrap.mp4 9.4 MBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/2. Understanding Monte Carlo Basics/4. Estimating Pi.mp4 9.3 MBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/2. Getting Started with Bootstrapping in R/03. Sample Statistics and Confidence Intervals.mp4 9.3 MBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/5. Applying Statistical Models in R/3. The T-test and the Z-test.mp4 9.2 MBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/5. Understanding and Applying Linear Inverse Models/05. Underdetermined and Overdetermined Systems.mp4 9.1 MBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/3. Implementing Bootstrap Methods for Summary Statistics/3. Demo - Performing Bootstrapping Using the Boot Method.mp4 9.1 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/4. Working with Graphs Using Numerical Techniques/08. Demo - Exploring Different Kinds of Graphs.mp4 9.0 MBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/2. Understanding the Importance of Reducing Complexity in Data/09. Demo - Selecting Predictors to Build Regression Models.mp4 9.0 MBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/3. Understanding Types of Differential Equations/2. Differential Algebraic Equations.mp4 8.9 MBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/3. Case Studies on Statistical and Mathematical Models/4. Modeling Value at Risk - A Simplistic Model.mp4 8.9 MBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/5. Implementing Bayesian AB Testing/05. The Conjugate Prior.mp4 8.8 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/2. Understanding Numerical Methods/7. Constant, Linear, Polynomial, and Spline Interpolation.mp4 8.7 MBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/5. Implementing Bayesian AB Testing/06. Understanding the Bayesian AB Test.mp4 8.7 MBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/5. Implementing Bayesian AB Testing/01. Introducing AB Testing.mp4 8.7 MBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/2. Performing Qualitative and Quantitative Analysis Using MASS Datasets/11. Demo - Executing ANOVA Analysis on Cars Data.mp4 8.6 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/5. Implementing Local Search and Optimizations/11. Demo - Solving Optimization Problems Using Linear Programming.mp4 8.6 MBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/3. Performing Dimensional Analysis for Continuous Data/2. Partial Least Squares Regression.mp4 8.6 MBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/4. Implementing Bootstrap Methods for Regression Models/2. Regression Metrics and Bootstrapping.mp4 8.6 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/5. Implementing Local Search and Optimizations/02. Introducing Local Search Algorithms.mp4 8.6 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/2. Understanding Numerical Methods/4. Direct and Iterative Numerical Methods.mp4 8.6 MBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/3. Performing Predictive Analytics Using MASS Models/1. Principal Component Analysis - Intuition.mp4 8.6 MBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/4. Implementing Statistical Models/5. Logistic Regression.mp4 8.5 MBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/5. Implementing Bayesian AB Testing/08. Demo - Performing and Interpreting the Bayesian AB Test for Click-through Rates.mp4 8.5 MBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/5. Utilizing MC for AB Testing/3. Chi-squared Test.mp4 8.5 MBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/4. Implementing Statistical Models/2. Linear Regression.mp4 8.3 MBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/3. Performing Dimensional Analysis for Continuous Data/6. Demo - Partial Least Squares Regression.mp4 8.3 MBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/2. Performing Qualitative and Quantitative Analysis Using MASS Datasets/09. Demo - Running t-tests on Birthweight Data.mp4 8.3 MBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/5. Understanding and Applying Linear Inverse Models/09. Demo - Applying Linear Inverse Models.mp4 8.3 MBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/4. Solving Differential Equations/3. Demo - Solving ODEs - Chaotic Solutions to Lorenzs Equation.mp4 8.2 MBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/3. Case Studies on Statistical and Mathematical Models/6. Using Monte Carlo Simulations to Model Value at Risk.mp4 8.2 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/4. Working with Graphs Using Numerical Techniques/01. Graphs and Graph Applications.mp4 8.2 MBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/2. Getting Started with Differential Equations/04. Interpreting Derivatives.mp4 8.1 MBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/2. Understanding the Importance of Reducing Complexity in Data/07. Choosing the Right Technique.mp4 8.0 MBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/2. Understanding Statistical Summaries/07. The T-test for Different Use Cases.mp4 8.0 MBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/4. Implementing Multi-state Models in R/11. Demo - Log Rank Tests and the Proportional Hazards Model.mp4 8.0 MBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/2. Performing Qualitative and Quantitative Analysis Using MASS Datasets/10. Demo - Quantitative and Qualitative Analysis of Ca.mp4 8.0 MBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/3. Implementing Bootstrap Methods for Summary Statistics/9. Demo - Smoothed Bootstrap.mp4 7.9 MBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/3. Case Studies on Statistical and Mathematical Models/2. Interpreting Derivatives.mp4 7.9 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/4. Working with Graphs Using Numerical Techniques/07. Demo - Specifying Attributes for Edges and Vertices.mp4 7.9 MBB4. Applying Linear Algebra with R (Brandon Strain, 2020)/9. Using Least Squares Calculations/1. Using Least Squares Calculations.mp4 7.8 MBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/2. Performing Qualitative and Quantitative Analysis Using MASS Datasets/07. Demo - Integrating with the MASS Package.mp4 7.8 MBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/5. Understanding and Applying Linear Inverse Models/03. The Wyndor Glass Case Study.mp4 7.7 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/5. Implementing Local Search and Optimizations/08. Wyndor Glass - Framing the Optimization Problem.mp4 7.7 MBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/5. Utilizing MC for AB Testing/5. Inserting a Prior into the Simulations.mp4 7.7 MBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/2. Getting Started with Differential Equations/09. Analytical and Numerical Solvers.mp4 7.6 MBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/2. Understanding the Importance of Reducing Complexity in Data/06. Techniques to Reduce Complexity.mp4 7.6 MBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/5. Applying Statistical Models in R/6. Demo - One Sample Z-test.mp4 7.5 MBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/2. Getting Started with Differential Equations/10. Modeling Technology Adoption Using an S-curve.mp4 7.4 MBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/5. Understanding and Applying Linear Inverse Models/04. Primal and Dual Problems.mp4 7.3 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/2. Understanding Numerical Methods/5. Numerical Instability and Errors.mp4 7.3 MBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/5. Implementing Bayesian AB Testing/04. Frequentist Approach vs. Bayesian Approach.mp4 7.2 MBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/5. Understanding and Applying Linear Inverse Models/08. Demo - Solving Underdetermined Systems.mp4 7.1 MBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/2. Understanding Statistical and Mathematical Models/6. Demo - Creating an Environment to Run the R Kernel on Jupyter Notebook.mp4 7.1 MBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/3. Understanding Types of Differential Equations/5. The Diffusion Equation.mp4 7.1 MBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/5. Applying Statistical Models in R/1. Data Mining Statistics and Machine Learning.mp4 7.0 MBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/3. Performing Predictive Analytics Using MASS Models/5. Demo - LDA Using All Column Values.mp4 7.0 MBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/5. Understanding and Applying Linear Inverse Models/01. Framing the Optimization Problem.mp4 6.9 MBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/3. Performing Predictive Analytics Using MASS Models/3. Fitting Robust Linear Models.mp4 6.9 MBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/3. Case Studies on Statistical and Mathematical Models/3. Verhulsts Decreasing Growth Model.mp4 6.9 MBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/4. Implementing Bootstrap Methods for Regression Models/3. Case Resampling and Residual Resampling.mp4 6.9 MBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/5. Understanding and Applying Linear Inverse Models/07. Demo - Solving Overdetermined Systems.mp4 6.8 MBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/2. Performing Qualitative and Quantitative Analysis Using MASS Datasets/12. Demo - Paired Sample t-test on Anorexia Data.mp4 6.7 MBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/4. Performing Dimensional Analysis for Categorical Data/4. Demo - Performing Quadratic Discriminant Analysis on Glass Data.mp4 6.7 MBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/3. Solving Problems Using Statistical Inference/8. Demo - Assumptions of One-way ANOVA and Alternatives.mp4 6.7 MBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/3. Case Studies on Statistical and Mathematical Models/5. Understanding Monte Carlo Simulations.mp4 6.6 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/6. Implementing Integration and Differentiation/01. Modeling Population Growth.mp4 6.5 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/2. Understanding Numerical Methods/3. Introducing Numerical Methods.mp4 6.4 MBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/3. Understanding Types of Differential Equations/6. Delay Differential Equations.mp4 6.3 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/4. Working with Graphs Using Numerical Techniques/02. Directed and Undirected Graphs.mp4 6.3 MBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/5. Understanding and Applying Linear Inverse Models/06. Demo - Solving Even Determined Systems.mp4 6.3 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/4. Working with Graphs Using Numerical Techniques/10. Demo - Calculating Shortest Paths.mp4 6.2 MBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/2. Understanding Statistical Summaries/11. Pearsons Chi2 Test.mp4 6.2 MBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/3. Performing Predictive Analytics Using MASS Models/2. Linear Discriminant Analysis and Quadratic Discriminant Analysis.mp4 6.2 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/3. Applying Numerical Methods to Solve Problems/5. Demo - Direct Techniques - Gaussian Elimination to Solve Linear Equations.mp4 6.1 MBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/2. Getting Started with Bootstrapping in R/05. Normally Distributed Data - Calculating Confidence Intervals.mp4 6.1 MBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/2. Getting Started with Differential Equations/03. Introducing Differentiation.mp4 6.1 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/5. Implementing Local Search and Optimizations/03. Simulated Annealing and Threshold Accepting.mp4 6.1 MBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/2. Understanding Monte Carlo Basics/1. Introduction to Monte Carlo.mp4 6.0 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/6. Implementing Integration and Differentiation/04. Understanding Integration.mp4 6.0 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/5. Implementing Local Search and Optimizations/12. Demo - Linear Programming to Solve the Wyndor Glass Problem.mp4 5.9 MBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/4. Implementing Multi-state Models in R/03. Types of State Models.mp4 5.9 MBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/3. Case Studies on Statistical and Mathematical Models/1. Modeling Population Growth Using ODEs.mp4 5.8 MBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/2. Getting Started with Bootstrapping in R/10. Drawbacks of Conventional Approaches.mp4 5.7 MBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/5. Implementing Bayesian AB Testing/09. Demo - Performing and Interpreting the Bayesian AB Test for Page Interactions.mp4 5.7 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/2. Understanding Numerical Methods/8. System of Linear Equations.mp4 5.6 MBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/4. Using Monte Carlo for Value at Risk/1. Introduction to Value at Risk.mp4 5.5 MBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/5. Implementing Bayesian AB Testing/03. Bayes Theorem Intuition.mp4 5.5 MBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/2. Understanding Statistical Summaries/06. Introducing the T-test.mp4 5.5 MBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/3. Implementing Bootstrap Methods for Summary Statistics/6. Bayesian Bootstrap Algorithm.mp4 5.4 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/exercise.7z 5.4 MBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/exercise.7z 5.3 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/6. Implementing Integration and Differentiation/06. Demo - Calculating Velocity and Acceleration Using Derivatives.mp4 5.3 MBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/2. Getting Started with Differential Equations/06. Introducing Integration to Solve Differential Equations.mp4 5.3 MBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/3. Performing Predictive Analytics Using MASS Models/6. Demo - Quadratic Discriminant Analysis.mp4 5.2 MBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/2. Understanding Statistical Summaries/03. The Role of Statistics in Understanding Data.mp4 5.2 MBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/2. Getting Started with Bootstrapping in R/07. Implications of the Central Limit Theorem.mp4 5.0 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/3. Applying Numerical Methods to Solve Problems/3. Demo - Interpolation Using Spline and Smoothing Techniques.mp4 5.0 MBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/2. Getting Started with Differential Equations/08. Initial and Boundary Value Problems.mp4 5.0 MBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/2. Performing Qualitative and Quantitative Analysis Using MASS Datasets/04. Qualitative and Quantitative Data.mp4 4.8 MBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/3. Implementing Bootstrap Methods for Summary Statistics/8. Introducing the Smoothed Bootstrap.mp4 4.7 MBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/5. Understanding and Applying Linear Inverse Models/02. Forward Models and Inverse Models.mp4 4.7 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/2. Understanding Numerical Methods/2. Prerequisites and Course Outline.mp4 4.7 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/5. Implementing Local Search and Optimizations/10. Solving the Linear Programming Problem Graphically.mp4 4.7 MBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/4. Solving Differential Equations/5. Demo - Solving DAEs - The Pendulum Equation.mp4 4.7 MBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/2. Getting Started with Differential Equations/07. Types of Differential Equations.mp4 4.6 MBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/2. Performing Qualitative and Quantitative Analysis Using MASS Datasets/06. Hypothesis Testing Using ANOVA.mp4 4.6 MBB4. Applying Linear Algebra with R (Brandon Strain, 2020)/1. Course Overview/1. Course Overview.mp4 4.6 MBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/exercise.7z 4.4 MBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/4. Implementing Multi-state Models in R/05. Examples of Multi-state Models.mp4 4.4 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/5. Implementing Local Search and Optimizations/09. Setting up the Optimization as a Linear Programming Problem.mp4 4.3 MBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/exercise.7z 4.2 MBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/2. Understanding Statistical Summaries/08. The Z-test.mp4 4.2 MBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/4. Implementing Statistical Models/1. Continuous and Categorical Data.mp4 4.2 MBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/2. Getting Started with Bootstrapping in R/02. Prerequisites and Course Outline.mp4 4.2 MBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/2. Understanding the Importance of Reducing Complexity in Data/02. Prerequisites and Course Outline.mp4 4.2 MBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/4. Implementing Multi-state Models in R/04. Understanding Weibull Distributions to Model State Transitions.mp4 4.1 MBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/2. Getting Started with Differential Equations/02. Prerequisites and Course Outline.mp4 4.1 MBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/2. Understanding Statistical and Mathematical Models/7. Demo - Associating Metadata Using the Comment Function.mp4 4.0 MBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/3. Understanding Types of Differential Equations/4. Solving Partial Differential Equations.mp4 4.0 MBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/2. Performing Qualitative and Quantitative Analysis Using MASS Datasets/02. Prerequisites and Course Outline.mp4 4.0 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/2. Understanding Numerical Methods/6. Interpolation and Extrapolation.mp4 4.0 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/5. Implementing Local Search and Optimizations/05. Demo - 8 Queens - Generating Candidate Solutions.mp4 4.0 MBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/1. Course Overview/1. Course Overview.mp4 3.9 MBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/2. Understanding Statistical Summaries/05. P-values, Power, and Alpha of Statistical Tests.mp4 3.9 MBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/1. Course Overview/1. Course Overview.mp4 3.9 MBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/1. Course Overview/1. Course Overview.mp4 3.8 MBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/1. Course Overview/1. Course Overview.mp4 3.8 MBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/exercise.7z 3.8 MBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/1. Course Overview/1. Course Overview.mp4 3.8 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/4. Working with Graphs Using Numerical Techniques/03. Connected and Unconnected Graphs.mp4 3.7 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/1. Course Overview/1. Course Overview.mp4 3.7 MBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/4. Implementing Multi-state Models in R/06. The Kaplan-Meier Estimator and the Log Rank Test.mp4 3.7 MBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/5. Utilizing MC for AB Testing/1. Introduction to AB Testing.mp4 3.6 MBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/1. Course Overview/1. Course Overview.mp4 3.6 MBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/2. Understanding Statistical Summaries/10. Two-way ANOVA and Assumptions.mp4 3.5 MBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/1. Course Overview/1. Course Overview.mp4 3.4 MBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/4. Applying Mathematical Models in R/1. Recap - Ordinary Differential Equations.mp4 3.4 MBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/2. Understanding the Importance of Reducing Complexity in Data/04. Drawbacks of Dimensionality Reduction.mp4 3.2 MBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/4. Implementing Statistical Models/6. Odds Ratio and the Forest Plot.mp4 3.2 MBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/5. Performing Dimensional Analysis for Non-linear Data/5. Module Summary.mp4 3.0 MBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/4. Implementing Bootstrap Methods for Regression Models/1. Introducing Linear Regression.mp4 2.9 MBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/2. Understanding Statistical Summaries/02. Prerequisites and Course Outline.mp4 2.8 MBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/4. Implementing Bootstrap Methods for Regression Models/7. Summary and Further Study.mp4 2.7 MBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/2. Performing Qualitative and Quantitative Analysis Using MASS Datasets/03. Introducing the MASS Package.mp4 2.6 MBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/exercise.7z 2.6 MBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/5. Implementing Bayesian AB Testing/10. Summary and Further Study.mp4 2.4 MBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/exercise.7z 2.3 MBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/5. Applying Statistical Models in R/9. Summary and Further Study.mp4 2.2 MBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/4. Implementing Multi-state Models in R/12. Summary and Further Study.mp4 2.2 MBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/5. Understanding and Applying Linear Inverse Models/10. Summary and Further Study.mp4 2.2 MBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/6. Implementing Integration and Differentiation/10. Summary and Further Study.mp4 2.1 MBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/3. Making Predictions with Monte Carlo/1. Introduction.mp4 2.1 MBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/2. Understanding Statistical and Mathematical Models/2. Prerequisites and Course Outline.mp4 2.0 MBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/3. Making Predictions with Monte Carlo/6. Conclusion.mp4 1.3 MBB4. Applying Linear Algebra with R (Brandon Strain, 2020)/7. Calculating the kth Item in a Series/1. Calculating the kth Item in a Series.mp4 803.7 kBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/2. Understanding Statistical and Mathematical Models/1. Version Check.mp4 525.5 kBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/2. Getting Started with Differential Equations/01. Version Check.mp4 520.1 kBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/2. Performing Qualitative and Quantitative Analysis Using MASS Datasets/01. Version Check.mp4 514.6 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/2. Understanding Numerical Methods/1. Version Check.mp4 502.5 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/2. Understanding Statistical Summaries/01. Version Check.mp4 499.6 kBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/2. Understanding the Importance of Reducing Complexity in Data/01. Version Check.mp4 499.0 kBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/2. Getting Started with Bootstrapping in R/01. Version Check.mp4 498.6 kB
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B4. Applying Linear Algebra with R (Brandon Strain, 2020)/4. Getting Weird - Inverting, Transposing, and Row Equivalence/1. Getting Weird.vtt 15.8 kBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/3. Making Predictions with Monte Carlo/5. Predictions on Commodities Data.vtt 15.6 kBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/2. Understanding Monte Carlo Basics/2. MC Basics in R.vtt 13.9 kBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/4. Applying Mathematical Models in R/7. Demo - Setting up Helper Functions to Solve the 8 Queens Optimization Prob.vtt 13.6 kBB4. Applying Linear Algebra with R (Brandon Strain, 2020)/6. Understanding and Calculating Eigenvalues and Eigenvectors/1. Understanding and Calculating Eigenvalues and Eigenvectors.vtt 13.4 kBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/3. Implementing Bootstrap Methods for Summary Statistics/1. Demo - Bootstrap Statistics and Sample Statistics.vtt 13.3 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/5. Implementing Local Search and Optimizations/04. Demo - 8 Queens - Calculating Number of Attacks.vtt 13.2 kBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/3. Making Predictions with Monte Carlo/4. Point Estimates and Confidence Intervals.vtt 13.1 kBB4. Applying Linear Algebra with R (Brandon Strain, 2020)/5. Solving Linear Equations/1. Solving Linear Equations.vtt 13.0 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/3. Applying Numerical Methods to Solve Problems/9. Demo - Eulers Method and Numerical Instability.vtt 12.9 kBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/4. Implementing Multi-state Models in R/01. Multi-state Models.vtt 12.5 kBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/5. Performing Dimensional Analysis for Non-linear Data/1. Manifold Learning.vtt 12.2 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/3. Solving Problems Using Statistical Inference/9. Demo - Two-way ANOVA.vtt 12.2 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/5. Implementing Bayesian AB Testing/02. Distributions and Statistical Tests.vtt 12.1 kBB4. Applying Linear Algebra with R (Brandon Strain, 2020)/8. Implementing Matrix Decomposition/1. Implementing Matrix Decomposition.vtt 11.9 kBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/4. Applying Mathematical Models in R/5. The 8 Queens Problem.vtt 11.9 kBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/2. Performing Qualitative and Quantitative Analysis Using MASS Datasets/08. Demo - Quantitative and Qualitative Analysis of Bi.vtt 11.9 kBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/3. Performing Predictive Analytics Using MASS Models/8. Demo - Robust Regression Using the Boston Housing Dataset.vtt 11.8 kBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/2. Understanding Statistical and Mathematical Models/3. Understanding Mathematical Models and Statistical Models.vtt 11.8 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/4. Implementing Statistical Models/8. Demo - Accuracy, Sensitivity, and Specificity of the Logistic Regression Model.vtt 11.7 kBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/3. Implementing Bootstrap Methods for Summary Statistics/2. Demo - Performing Bootstrapping on Real Data.vtt 11.7 kBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/3. Performing Predictive Analytics Using MASS Models/4. Demo - Linear Discriminant Analysis (LDA) and Visualization.vtt 11.6 kBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/2. Getting Started with Bootstrapping in R/12. Bootstrapped Confidence Intervals.vtt 11.6 kBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/4. Performing Dimensional Analysis for Categorical Data/3. Demo - Performing Linear Discriminant Analysis on Glass Data.vtt 11.5 kBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/2. Understanding the Importance of Reducing Complexity in Data/03. The Curse of Dimensionality.vtt 11.4 kBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/3. Making Predictions with Monte Carlo/3. Simulating Random Walk with MC.vtt 11.3 kBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/5. Performing Dimensional Analysis for Non-linear Data/2. Demo - Manifold Learning Using Metric and Non-metric MDS.vtt 11.3 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/2. Understanding Statistical Summaries/04. Hypothesis Testing.vtt 11.2 kBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/5. Utilizing MC for AB Testing/4. AB Testing with Monte Carlo.vtt 11.2 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/3. Applying Numerical Methods to Solve Problems/1. Demo - Linear and Constant Interpolation.vtt 11.1 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/5. Implementing Bayesian AB Testing/07. Demo - Modelling Outcomes and Priors for the Bayes AB Test.vtt 11.0 kBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/2. Understanding the Importance of Reducing Complexity in Data/05. Overfitting and the Bias-variance Trade-off.vtt 11.0 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/5. Implementing Local Search and Optimizations/01. Solutions Approaches to N-Queens.vtt 10.9 kBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/3. Performing Predictive Analytics Using MASS Models/7. Demo - Fitting a Robust Linear Model.vtt 10.7 kBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/2. Getting Started with Bootstrapping in R/08. Demo - The Central Limit Theorem with Different Distributions.vtt 10.6 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/3. Solving Problems Using Statistical Inference/3. Demo - Two Sample T-test.vtt 10.6 kBB4. Applying Linear Algebra with R (Brandon Strain, 2020)/2. Working with Vectors and Matrices in R/1. Working with Vectors and Matrices in R.vtt 10.5 kBB4. Applying Linear Algebra with R (Brandon Strain, 2020)/8. Implementing Matrix Decomposition/2. Demo - Implementing Matrix Decomposition.vtt 10.4 kBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/3. Performing Dimensional Analysis for Continuous Data/1. Principal Components Analysis.vtt 10.4 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/4. Implementing Statistical Models/4. Demo - Performing Linear Regression and Interpretings Results.vtt 10.3 kBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/3. Implementing Bootstrap Methods for Summary Statistics/4. Demo - Bootstrapping Multiple Statistics.vtt 10.0 kBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/2. Understanding Statistical and Mathematical Models/8. Demo - Querying and Setting Metadata Using the Meta Function.vtt 9.9 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/3. Solving Problems Using Statistical Inference/7. Demo - One-way ANOVA.vtt 9.9 kBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/2. Understanding Monte Carlo Basics/3. Rolling the Dice.vtt 9.8 kBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/4. Implementing Multi-state Models in R/07. Demo - Understanding the Multi-state Model Data.vtt 9.8 kBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/4. Performing Dimensional Analysis for Categorical Data/1. Linear Discriminant Analysis and Quadratic Discriminant Analysis.vtt 9.7 kBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/2. Understanding Statistical and Mathematical Models/5. Data and Metadata.vtt 9.7 kBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/4. Implementing Multi-state Models in R/08. Demo - Modeling Transition Probabilities and Simulating Outcomes.vtt 9.7 kBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/4. Performing Dimensional Analysis for Categorical Data/2. Demo - Exploring and Preparing Data for Linear Discriminant Analysis.vtt 9.7 kBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/2. Understanding the Importance of Reducing Complexity in Data/10. Demo - Performing Stepwise and Kitchen Sink Regression.vtt 9.5 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/2. Understanding Numerical Methods/9. Gaussian Elimination and Jacobi Method.vtt 9.5 kBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/4. Applying Mathematical Models in R/8. Demo - Applying Local Search Optimization to Solve the Eight Queens Proble.vtt 9.5 kBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/2. Getting Started with Differential Equations/11. Modeling Financial Assets Using PDEs.vtt 9.4 kBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/4. Applying Mathematical Models in R/6. Local Search Optimization Techniques.vtt 9.4 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/3. Solving Problems Using Statistical Inference/4. Demo - Type I and Type II Errors.vtt 9.3 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/4. Working with Graphs Using Numerical Techniques/09. Demo - Calculating Shortest Distances.vtt 9.2 kBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/3. Performing Dimensional Analysis for Continuous Data/3. Demo - Performing Principal Component Analysis.vtt 9.2 kBB4. Applying Linear Algebra with R (Brandon Strain, 2020)/7. Calculating the kth Item in a Series/3. Demo - Calculating the kth Item in a Series.vtt 9.2 kBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/2. Understanding Statistical and Mathematical Models/4. Mathematical Models and Statistical Models - Differences and Applicati.vtt 9.1 kBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/3. Implementing Bootstrap Methods for Summary Statistics/7. Demo - Performing Bayesian Bootstrapping.vtt 9.0 kBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/4. Applying Mathematical Models in R/3. Demo - Solving Differential Equations.vtt 9.0 kBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/4. Using Monte Carlo for Value at Risk/3. Parametric and Historical VaR.vtt 9.0 kBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/2. Performing Qualitative and Quantitative Analysis Using MASS Datasets/05. Hypothesis Testing Using t-tests.vtt 9.0 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/3. Solving Problems Using Statistical Inference/2. Demo - One Sample T-test and Z-test.vtt 9.0 kBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/2. Understanding the Importance of Reducing Complexity in Data/08. Demo - Exploring the Boston Housing Dataset.vtt 8.9 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/2. Understanding Statistical Summaries/09. One-way ANOVA - Assumptions and Alternatives.vtt 8.8 kBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/4. Implementing Multi-state Models in R/09. Demo - Visualizing and Interpreting State Occupancy Probabilities.vtt 8.8 kBB4. Applying Linear Algebra with R (Brandon Strain, 2020)/7. Calculating the kth Item in a Series/2. Difference Equations.vtt 8.8 kBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/4. Using Monte Carlo for Value at Risk/4. Monte Carlo VaR.vtt 8.8 kBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/4. Solving Differential Equations/1. Demo - Solving ODEs - The Population Growth Model.vtt 8.7 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/3. Solving Problems Using Statistical Inference/5. Demo - Performing Chi2 Analysis.vtt 8.7 kBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/2. Getting Started with Bootstrapping in R/11. Introducing Bootstrapping.vtt 8.7 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/3. Solving Problems Using Statistical Inference/6. Demo - Interpreting the Results of Chi2 Analysis.vtt 8.6 kBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/5. Applying Statistical Models in R/5. Demo - One Sample T-test.vtt 8.6 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/5. Implementing Local Search and Optimizations/07. Objective Constraints and Decision Variables.vtt 8.5 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/3. Applying Numerical Methods to Solve Problems/2. Demo - Linear and Polynomial Extrapolation.vtt 8.5 kBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/4. Solving Differential Equations/4. Demo - Solving DAEs - An Auto-catalytic Chemical Reaction.vtt 8.5 kBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/5. Performing Dimensional Analysis for Non-linear Data/3. Demo - Manifold Learning Using t-SNE, Isomap, and LLE.vtt 8.4 kBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/3. Making Predictions with Monte Carlo/2. Random Walk.vtt 8.4 kBB4. Applying Linear Algebra with R (Brandon Strain, 2020)/9. Using Least Squares Calculations/2. Demo - Using Least Squares Calculations.vtt 8.4 kBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/4. Implementing Bootstrap Methods for Regression Models/5. Demo - Estimating Coefficients Using Bootstrapping.vtt 8.4 kBB4. Applying Linear Algebra with R (Brandon Strain, 2020)/9. Using Least Squares Calculations/1. Using Least Squares Calculations.vtt 8.4 kBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/4. Implementing Bootstrap Methods for Regression Models/4. Demo - Estimating R2 of Regression Models Using Bootstrapping.vtt 8.4 kBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/5. Applying Statistical Models in R/2. Understanding Hypothesis Testing.vtt 8.3 kBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/4. Applying Mathematical Models in R/4. Demo - Solving Verhulsts Equation for Population Growth.vtt 8.2 kBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/2. Getting Started with Bootstrapping in R/04. Normally Distributed Data - Estimating Mean.vtt 8.1 kBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/5. Applying Statistical Models in R/3. The T-test and the Z-test.vtt 8.1 kBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/4. Implementing Multi-state Models in R/02. Survival Models.vtt 8.1 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/4. Implementing Statistical Models/2. Linear Regression.vtt 8.0 kBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/4. Solving Differential Equations/7. Demo - Solving DDEs - Infectious Disease Modeling.vtt 8.0 kBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/3. Understanding Types of Differential Equations/1. Ordinary Differential Equations.vtt 8.0 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/6. Implementing Integration and Differentiation/08. Demo - Using the ODE Solver to Solve Differential Equations.vtt 8.0 kBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/3. Understanding Types of Differential Equations/3. Partial Differential Equations.vtt 7.9 kBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/3. Case Studies on Statistical and Mathematical Models/4. Modeling Value at Risk - A Simplistic Model.vtt 7.9 kBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/3. Case Studies on Statistical and Mathematical Models/6. Using Monte Carlo Simulations to Model Value at Risk.vtt 7.8 kBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/5. Applying Statistical Models in R/7. Demo - Two Sample T-test.vtt 7.8 kBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/5. Applying Statistical Models in R/4. Demo - Exploring the Automobile Dataset.vtt 7.8 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/5. Implementing Bayesian AB Testing/06. Understanding the Bayesian AB Test.vtt 7.8 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/4. Implementing Statistical Models/5. Logistic Regression.vtt 7.8 kBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/4. Using Monte Carlo for Value at Risk/2. Data Preparation.vtt 7.8 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/5. Implementing Bayesian AB Testing/05. The Conjugate Prior.vtt 7.8 kBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/4. Applying Mathematical Models in R/2. Demo - Calculating the Derivative of a Function.vtt 7.8 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/5. Implementing Bayesian AB Testing/01. Introducing AB Testing.vtt 7.7 kBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/5. Utilizing MC for AB Testing/5. Inserting a Prior into the Simulations.vtt 7.7 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/4. Working with Graphs Using Numerical Techniques/06. Demo - Defining and Configuring Graphs.vtt 7.7 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/4. Working with Graphs Using Numerical Techniques/05. Shortest Path Algorithms.vtt 7.7 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/3. Solving Problems Using Statistical Inference/1. Demo - Preprocessing Data.vtt 7.7 kBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/2. Getting Started with Bootstrapping in R/06. Data with Any Distribution - Estimating Mean and Confidence Intervals.vtt 7.6 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/6. Implementing Integration and Differentiation/02. Interpreting Derivatives.vtt 7.6 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/2. Understanding Statistical Summaries/07. The T-test for Different Use Cases.vtt 7.6 kBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/2. Getting Started with Bootstrapping in R/03. Sample Statistics and Confidence Intervals.vtt 7.6 kBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/3. Performing Dimensional Analysis for Continuous Data/5. Demo - Principal Components Regression.vtt 7.5 kBB4. Applying Linear Algebra with R (Brandon Strain, 2020)/3. Understanding Operations on Matrices/1. Understanding Operations on Matrices.vtt 7.5 kBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/3. Case Studies on Statistical and Mathematical Models/2. Interpreting Derivatives.vtt 7.4 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/3. Applying Numerical Methods to Solve Problems/4. Demo - Iterative Techniques - Jacobi Method to Solve Linear Equations.vtt 7.4 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/5. Implementing Local Search and Optimizations/02. Introducing Local Search Algorithms.vtt 7.4 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/6. Implementing Integration and Differentiation/03. Verhulsts Equation for Population Growth.vtt 7.3 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/4. Working with Graphs Using Numerical Techniques/01. Graphs and Graph Applications.vtt 7.3 kBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/4. Solving Differential Equations/6. Demo - Solving PDEs - The Diffusion Equation for Heat Transfer.vtt 7.3 kBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/3. Understanding Types of Differential Equations/7. Infectious Disease Modeling.vtt 7.3 kBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/4. Implementing Multi-state Models in R/10. Demo - Modeling Survival Analysis.vtt 7.2 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/4. Working with Graphs Using Numerical Techniques/04. Graph Representations.vtt 7.2 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/2. Understanding Numerical Methods/4. Direct and Iterative Numerical Methods.vtt 7.2 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/6. Implementing Integration and Differentiation/09. Demo - Solving Verhulsts Equation.vtt 7.1 kBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/2. Getting Started with Differential Equations/10. Modeling Technology Adoption Using an S-curve.vtt 7.1 kBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/5. Understanding and Applying Linear Inverse Models/05. Underdetermined and Overdetermined Systems.vtt 7.1 kBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/2. Getting Started with Differential Equations/05. Verhulsts Equation of Population Growth.vtt 7.1 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/4. Implementing Statistical Models/7. Demo - Performing Logistic Regression.vtt 7.1 kBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/5. Applying Statistical Models in R/1. Data Mining Statistics and Machine Learning.vtt 7.1 kBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/5. Applying Statistical Models in R/8. Demo - Paired Sample T-test and Z-test.vtt 7.0 kBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/3. Performing Predictive Analytics Using MASS Models/1. Principal Component Analysis - Intuition.vtt 7.0 kBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/5. Utilizing MC for AB Testing/3. Chi-squared Test.vtt 7.0 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/2. Understanding Numerical Methods/7. Constant, Linear, Polynomial, and Spline Interpolation.vtt 7.0 kBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/2. Understanding Monte Carlo Basics/1. Introduction to Monte Carlo.vtt 6.9 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/3. Applying Numerical Methods to Solve Problems/6. Demo - Discretizing Continuous Data.vtt 6.8 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/5. Implementing Bayesian AB Testing/04. Frequentist Approach vs. Bayesian Approach.vtt 6.8 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/3. Applying Numerical Methods to Solve Problems/8. Demo - Approximating Derivate Calculations.vtt 6.8 kBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/3. Understanding Types of Differential Equations/2. Differential Algebraic Equations.vtt 6.7 kBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/3. Performing Dimensional Analysis for Continuous Data/4. Demo - Regression Using Principal Components.vtt 6.7 kBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/5. Performing Dimensional Analysis for Non-linear Data/4. Demo - Kernel PCA for Non-linearly Separable Data.vtt 6.7 kBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/3. Performing Dimensional Analysis for Continuous Data/2. Partial Least Squares Regression.vtt 6.7 kBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/3. Implementing Bootstrap Methods for Summary Statistics/5. Introducing the Bayesian Bootstrap.vtt 6.6 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/4. Implementing Statistical Models/3. Demo - Exploring Data for Regression Analysis.vtt 6.5 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/5. Implementing Local Search and Optimizations/06. Demo - 8 Queens - Solution Using Local Search Techniques.vtt 6.5 kBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/3. Performing Dimensional Analysis for Continuous Data/6. Demo - Partial Least Squares Regression.vtt 6.5 kBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/2. Understanding the Importance of Reducing Complexity in Data/06. Techniques to Reduce Complexity.vtt 6.5 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/6. Implementing Integration and Differentiation/07. Demo - Performing Integration.vtt 6.4 kBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/2. Understanding the Importance of Reducing Complexity in Data/07. Choosing the Right Technique.vtt 6.4 kBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/5. Utilizing MC for AB Testing/2. Two Sample t-test.vtt 6.4 kBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/4. Implementing Bootstrap Methods for Regression Models/2. Regression Metrics and Bootstrapping.vtt 6.4 kBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/2. Getting Started with Differential Equations/04. Interpreting Derivatives.vtt 6.2 kBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/3. Case Studies on Statistical and Mathematical Models/5. Understanding Monte Carlo Simulations.vtt 6.2 kBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/2. Getting Started with Bootstrapping in R/09. Demo - The Central Limit Theorem on Real Data.vtt 6.2 kBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/2. Getting Started with Differential Equations/09. Analytical and Numerical Solvers.vtt 6.1 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/2. Understanding Numerical Methods/3. Introducing Numerical Methods.vtt 6.1 kBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/3. Implementing Bootstrap Methods for Summary Statistics/3. Demo - Performing Bootstrapping Using the Boot Method.vtt 6.0 kBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/2. Understanding Monte Carlo Basics/4. Estimating Pi.vtt 5.9 kBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/3. Implementing Bootstrap Methods for Summary Statistics/9. Demo - Smoothed Bootstrap.vtt 5.9 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/4. Working with Graphs Using Numerical Techniques/08. Demo - Exploring Different Kinds of Graphs.vtt 5.9 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/5. Implementing Local Search and Optimizations/11. Demo - Solving Optimization Problems Using Linear Programming.vtt 5.9 kBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/3. Performing Predictive Analytics Using MASS Models/3. Fitting Robust Linear Models.vtt 5.8 kBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/4. Implementing Bootstrap Methods for Regression Models/6. Demo - Case Resampling and Residual Resampling Using the Boot() Method.vtt 5.8 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/3. Applying Numerical Methods to Solve Problems/7. Demo - Rounding Errors and Approximation Errors.vtt 5.8 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/4. Working with Graphs Using Numerical Techniques/02. Directed and Undirected Graphs.vtt 5.8 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/6. Implementing Integration and Differentiation/05. Demo - Calculating Derivatives.vtt 5.8 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/5. Implementing Bayesian AB Testing/03. Bayes Theorem Intuition.vtt 5.7 kBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/5. Applying Statistical Models in R/6. Demo - One Sample Z-test.vtt 5.7 kBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/2. Performing Qualitative and Quantitative Analysis Using MASS Datasets/07. Demo - Integrating with the MASS Package.vtt 5.7 kBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/5. Understanding and Applying Linear Inverse Models/09. Demo - Applying Linear Inverse Models.vtt 5.7 kBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/2. Performing Qualitative and Quantitative Analysis Using MASS Datasets/09. Demo - Running t-tests on Birthweight Data.vtt 5.7 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/5. Implementing Bayesian AB Testing/08. Demo - Performing and Interpreting the Bayesian AB Test for Click-through Rates.vtt 5.7 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/2. Understanding Numerical Methods/5. Numerical Instability and Errors.vtt 5.7 kBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/3. Case Studies on Statistical and Mathematical Models/3. Verhulsts Decreasing Growth Model.vtt 5.7 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/2. Understanding Statistical Summaries/11. Pearsons Chi2 Test.vtt 5.6 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/5. Implementing Local Search and Optimizations/08. Wyndor Glass - Framing the Optimization Problem.vtt 5.6 kBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/2. Performing Qualitative and Quantitative Analysis Using MASS Datasets/11. Demo - Executing ANOVA Analysis on Cars Data.vtt 5.5 kBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/3. Understanding Types of Differential Equations/5. The Diffusion Equation.vtt 5.5 kBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/4. Solving Differential Equations/2. Demo - Solving ODEs - Van Der Pols Equation.vtt 5.5 kBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/5. Understanding and Applying Linear Inverse Models/04. Primal and Dual Problems.vtt 5.4 kBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/2. Performing Qualitative and Quantitative Analysis Using MASS Datasets/12. Demo - Paired Sample t-test on Anorexia Data.vtt 5.4 kBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/5. Understanding and Applying Linear Inverse Models/03. The Wyndor Glass Case Study.vtt 5.4 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/2. Understanding Statistical Summaries/03. The Role of Statistics in Understanding Data.vtt 5.2 kBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/3. Case Studies on Statistical and Mathematical Models/1. Modeling Population Growth Using ODEs.vtt 5.2 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/6. Implementing Integration and Differentiation/04. Understanding Integration.vtt 5.2 kBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/4. Performing Dimensional Analysis for Categorical Data/4. Demo - Performing Quadratic Discriminant Analysis on Glass Data.vtt 5.0 kBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/2. Performing Qualitative and Quantitative Analysis Using MASS Datasets/10. Demo - Quantitative and Qualitative Analysis of Ca.vtt 5.0 kBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/4. Implementing Multi-state Models in R/03. Types of State Models.vtt 5.0 kBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/2. Understanding the Importance of Reducing Complexity in Data/09. Demo - Selecting Predictors to Build Regression Models.vtt 5.0 kBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/3. Understanding Types of Differential Equations/6. Delay Differential Equations.vtt 5.0 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/2. Understanding Statistical Summaries/06. Introducing the T-test.vtt 4.9 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/6. Implementing Integration and Differentiation/01. Modeling Population Growth.vtt 4.9 kBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/5. Understanding and Applying Linear Inverse Models/01. Framing the Optimization Problem.vtt 4.8 kBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/4. Implementing Bootstrap Methods for Regression Models/3. Case Resampling and Residual Resampling.vtt 4.8 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/playlist.m3u 4.8 kBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/2. Getting Started with Differential Equations/06. Introducing Integration to Solve Differential Equations.vtt 4.7 kBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/3. Performing Predictive Analytics Using MASS Models/2. Linear Discriminant Analysis and Quadratic Discriminant Analysis.vtt 4.6 kBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/5. Understanding and Applying Linear Inverse Models/08. Demo - Solving Underdetermined Systems.vtt 4.6 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/2. Understanding Numerical Methods/8. System of Linear Equations.vtt 4.6 kBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/2. Getting Started with Bootstrapping in R/05. Normally Distributed Data - Calculating Confidence Intervals.vtt 4.5 kBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/4. Implementing Multi-state Models in R/11. Demo - Log Rank Tests and the Proportional Hazards Model.vtt 4.5 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/3. Solving Problems Using Statistical Inference/8. Demo - Assumptions of One-way ANOVA and Alternatives.vtt 4.5 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/4. Working with Graphs Using Numerical Techniques/07. Demo - Specifying Attributes for Edges and Vertices.vtt 4.5 kBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/5. Understanding and Applying Linear Inverse Models/07. Demo - Solving Overdetermined Systems.vtt 4.5 kBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/4. Using Monte Carlo for Value at Risk/1. Introduction to Value at Risk.vtt 4.5 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/5. Implementing Local Search and Optimizations/03. Simulated Annealing and Threshold Accepting.vtt 4.4 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/5. Implementing Local Search and Optimizations/12. Demo - Linear Programming to Solve the Wyndor Glass Problem.vtt 4.4 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/5. Implementing Local Search and Optimizations/10. Solving the Linear Programming Problem Graphically.vtt 4.2 kBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/2. Getting Started with Bootstrapping in R/10. Drawbacks of Conventional Approaches.vtt 4.2 kBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/2. Getting Started with Differential Equations/08. Initial and Boundary Value Problems.vtt 4.2 kBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/2. Getting Started with Differential Equations/03. Introducing Differentiation.vtt 4.1 kBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/5. Understanding and Applying Linear Inverse Models/06. Demo - Solving Even Determined Systems.vtt 4.1 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/3. Applying Numerical Methods to Solve Problems/5. Demo - Direct Techniques - Gaussian Elimination to Solve Linear Equations.vtt 4.0 kBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/3. Performing Predictive Analytics Using MASS Models/5. Demo - LDA Using All Column Values.vtt 4.0 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/2. Understanding Numerical Methods/6. Interpolation and Extrapolation.vtt 3.9 kBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/2. Understanding the Importance of Reducing Complexity in Data/02. Prerequisites and Course Outline.vtt 3.9 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/2. Understanding Numerical Methods/2. Prerequisites and Course Outline.vtt 3.9 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/2. Understanding Statistical Summaries/08. The Z-test.vtt 3.9 kBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/2. Getting Started with Bootstrapping in R/02. Prerequisites and Course Outline.vtt 3.9 kBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/2. Performing Qualitative and Quantitative Analysis Using MASS Datasets/06. Hypothesis Testing Using ANOVA.vtt 3.9 kBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/2. Understanding Statistical and Mathematical Models/7. Demo - Associating Metadata Using the Comment Function.vtt 3.8 kBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/4. Solving Differential Equations/3. Demo - Solving ODEs - Chaotic Solutions to Lorenzs Equation.vtt 3.8 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/4. Working with Graphs Using Numerical Techniques/10. Demo - Calculating Shortest Paths.vtt 3.8 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/5. Implementing Bayesian AB Testing/09. Demo - Performing and Interpreting the Bayesian AB Test for Page Interactions.vtt 3.8 kBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/2. Understanding Statistical and Mathematical Models/6. Demo - Creating an Environment to Run the R Kernel on Jupyter Notebook.vtt 3.8 kBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/5. Utilizing MC for AB Testing/1. Introduction to AB Testing.vtt 3.7 kBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/5. Understanding and Applying Linear Inverse Models/02. Forward Models and Inverse Models.vtt 3.7 kBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/2. Getting Started with Differential Equations/07. Types of Differential Equations.vtt 3.7 kBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/2. Performing Qualitative and Quantitative Analysis Using MASS Datasets/04. Qualitative and Quantitative Data.vtt 3.7 kBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/3. Implementing Bootstrap Methods for Summary Statistics/8. Introducing the Smoothed Bootstrap.vtt 3.7 kBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/2. Getting Started with Differential Equations/02. Prerequisites and Course Outline.vtt 3.7 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/2. Understanding Statistical Summaries/05. P-values, Power, and Alpha of Statistical Tests.vtt 3.6 kBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/3. Implementing Bootstrap Methods for Summary Statistics/6. Bayesian Bootstrap Algorithm.vtt 3.6 kBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/2. Getting Started with Bootstrapping in R/07. Implications of the Central Limit Theorem.vtt 3.6 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/6. Implementing Integration and Differentiation/06. Demo - Calculating Velocity and Acceleration Using Derivatives.vtt 3.5 kBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/2. Performing Qualitative and Quantitative Analysis Using MASS Datasets/02. Prerequisites and Course Outline.vtt 3.5 kBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/4. Implementing Multi-state Models in R/04. Understanding Weibull Distributions to Model State Transitions.vtt 3.5 kBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/4. Implementing Multi-state Models in R/05. Examples of Multi-state Models.vtt 3.5 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/4. Implementing Statistical Models/1. Continuous and Categorical Data.vtt 3.5 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/5. Implementing Local Search and Optimizations/09. Setting up the Optimization as a Linear Programming Problem.vtt 3.4 kBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/1. Course Overview/1. Course Overview.vtt 3.4 kB
C2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/~i.txt 3.4 kBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/~i.txt 3.4 kBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/playlist.m3u 3.4 kBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/2. Understanding the Importance of Reducing Complexity in Data/04. Drawbacks of Dimensionality Reduction.vtt 3.4 kBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/3. Understanding Types of Differential Equations/4. Solving Partial Differential Equations.vtt 3.3 kBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/4. Implementing Multi-state Models in R/06. The Kaplan-Meier Estimator and the Log Rank Test.vtt 3.2 kBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/playlist.m3u 3.2 kBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/4. Applying Mathematical Models in R/1. Recap - Ordinary Differential Equations.vtt 3.2 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/playlist.m3u 3.2 kBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/1. Course Overview/1. Course Overview.vtt 3.1 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/2. Understanding Statistical Summaries/10. Two-way ANOVA and Assumptions.vtt 3.1 kBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/1. Course Overview/1. Course Overview.vtt 3.1 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/1. Course Overview/1. Course Overview.vtt 3.1 kBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/5. Performing Dimensional Analysis for Non-linear Data/5. Module Summary.vtt 3.1 kBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/~i.txt 3.1 kBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/3. Performing Predictive Analytics Using MASS Models/6. Demo - Quadratic Discriminant Analysis.vtt 3.1 kBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/1. Course Overview/1. Course Overview.vtt 3.1 kBB4. Applying Linear Algebra with R (Brandon Strain, 2020)/1. Course Overview/1. Course Overview.vtt 3.0 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/4. Implementing Statistical Models/6. Odds Ratio and the Forest Plot.vtt 3.0 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/1. Course Overview/1. Course Overview.vtt 3.0 kBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/1. Course Overview/1. Course Overview.vtt 3.0 kBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/playlist.m3u 2.9 kBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/playlist.m3u 2.9 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/~i.txt 2.8 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/2. Understanding Statistical Summaries/02. Prerequisites and Course Outline.vtt 2.8 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/4. Working with Graphs Using Numerical Techniques/03. Connected and Unconnected Graphs.vtt 2.8 kBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/4. Implementing Bootstrap Methods for Regression Models/7. Summary and Further Study.vtt 2.8 kBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/~i.txt 2.8 kBB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/playlist.m3u 2.7 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/3. Applying Numerical Methods to Solve Problems/3. Demo - Interpolation Using Spline and Smoothing Techniques.vtt 2.7 kBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/4. Solving Differential Equations/5. Demo - Solving DAEs - The Pendulum Equation.vtt 2.7 kBC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/4. Implementing Bootstrap Methods for Regression Models/1. Introducing Linear Regression.vtt 2.6 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/5. Implementing Local Search and Optimizations/05. Demo - 8 Queens - Generating Candidate Solutions.vtt 2.6 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/5. Implementing Bayesian AB Testing/10. Summary and Further Study.vtt 2.6 kBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/3. Making Predictions with Monte Carlo/1. Introduction.vtt 2.5 kBC1. Building Statistical Summaries with R (Janani Ravi, 2019)/~i.txt 2.5 kBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/2. Performing Qualitative and Quantitative Analysis Using MASS Datasets/03. Introducing the MASS Package.vtt 2.4 kBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/5. Applying Statistical Models in R/9. Summary and Further Study.vtt 2.2 kBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/~i.txt 2.1 kBB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/4. Implementing Multi-state Models in R/12. Summary and Further Study.vtt 2.1 kBA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/2. Understanding Statistical and Mathematical Models/2. Prerequisites and Course Outline.vtt 2.1 kBA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/6. Implementing Integration and Differentiation/10. Summary and Further Study.vtt 2.1 kBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/1. Course Overview/1. Course Overview.vtt 2.1 kBB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/5. Understanding and Applying Linear Inverse Models/10. Summary and Further Study.vtt 2.0 kBB4. Applying Linear Algebra with R (Brandon Strain, 2020)/~i.txt 1.6 kB~i.txt 1.6 kBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/~i.txt 1.5 kBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/playlist.m3u 1.3 kBC3. Implementing Monte Carlo Method in R (Chase DeHan, 2020)/3. Making Predictions with Monte Carlo/6. Conclusion.vtt 1.3 kBB4. Applying Linear Algebra with R (Brandon Strain, 2020)/playlist.m3u 1.1 kBB4. Applying Linear Algebra with R (Brandon Strain, 2020)/7. Calculating the kth Item in a Series/1. Calculating the kth Item in a Series.vtt 914 BytesA1. Understanding Statistical Models and Mathematical Models (Janani Ravi, 2019)/2. Understanding Statistical and Mathematical Models/1. Version Check.vtt 7 BytesA2. Solving Problems with Numerical Methods (Janani Ravi, 2020)/2. Understanding Numerical Methods/1. Version Check.vtt 7 BytesB1. Applying the Mathematical MASS Model with R (Janani Ravi, 2020)/2. Performing Qualitative and Quantitative Analysis Using MASS Datasets/01. Version Check.vtt 7 BytesB2. Applying Differential Equations and Inverse Models with R (Janani Ravi, 2020)/2. Getting Started with Differential Equations/01. Version Check.vtt 7 BytesB3. Performing Dimension Analysis with R (Janani Ravi, 2020)/2. Understanding the Importance of Reducing Complexity in Data/01. Version Check.vtt 7 BytesC1. Building Statistical Summaries with R (Janani Ravi, 2019)/2. Understanding Statistical Summaries/01. Version Check.vtt 7 BytesC2. Implementing Bootstrap Methods in R (Janani Ravi, 2020)/2. Getting Started with Bootstrapping in R/01. Version Check.vtt 7 Bytes Building A Container Home_ Building Container Homes_... 2.8 MB
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