Show sidebar

Introduction to the Theory of Probability, by Mrityunjoy Chakraborty

,

Joint Characteristic Functions, by Mrityunjoy Chakraborty

,

Joint Conditional Densities (Contd.), by Mrityunjoy Chakraborty

,

Joint Conditional Densities, by Mrityunjoy Chakraborty

,

Joint Moments, by Mrityunjoy Chakraborty

,

Last Lecture on Portfolio Optimization, by Joydeep Dutta

,

Lec 20: Importance Sampling, by Saurabh Basu

,

Lec 21: Applications: Ising Model, by Saurabh Basu

,

Lectur 33 : Panel Data Model, by Rudra P. Pradhan

,

Lecture : 17 Profile analysis. :II, by Amit Mitra

,

Lecture 01-Basic Fundamental Concepts of Modelling., by Shalabh

,

Lecture 01-Why R and Installation Procedure, by Shalabh

,

Lecture 02 : Introduction _Help_ Demo Examples_ Packages_ Libraries, by Shalabh

,

Lecture 02-Regression Model-A Statistical Tool, by Shalabh

,

Lecture 03 : Introduction _Command Line_ Data Editor _ Rstudio, by Shalabh

,

Lecture 03-Simple Linear Regression Analysis, by Shalabh

,

Lecture 04 : Basics in Calculations, by Shalabh

,

Lecture 04-Estimation of Parameters in Simple Linear Regression Model, by Shalabh

,

Lecture 05 : Basics of Calculations _ Calculator _Built in Functions Assignments, by Shalabh

,

Lecture 05-Estimation of Parameters in Simple Linear Regression Model (Continued) : Some Nice Properties, by Shalabh

,

Lecture 06 : Basics of Calculations _Functions _Matrices, by Shalabh

,

Lecture 06-Estimation of Parameters in Simple Linear Regression Model (Continued), by Shalabh

,

Lecture 07-Maximum Likelihood Estimation of Parameters in Simple Linear Regression Model, by Shalabh

,

Lecture 08-Testing of Hypotheis and Confidence Interval Estimation in Simple Linear Regression Model, by Shalabh

,

Lecture 09-Testing of Hypotheis and Confidence Interval Estimation in Simple Linear Regression Model (Continued), by Shalabh

,

Lecture 1-Introduction to the Course on American Literature and Culture, by Aysha Iqbal Viswamohan

,

Lecture 1: Introduction to Commodity Derivatives & Risk Management, by Prabina Rajib

,

Lecture 1: Introduction to Multivariate Statistical Modeling-Part-I, by J Maiti

,

Lecture 10-Software Implementation in Simple Linear Regression Model Using MINITAB, by Shalabh

,

Lecture 10, by Raghu Nandan Sengupta

,

Lecture 10: The Analysis of Variance (ANOVA)-III, by Raghunandan Sengupta

,

Lecture 11 : Professional Ethics & Values in Teaching, by Atasi Mohanty

,

Lecture 11-Multiple Linear Regression Model, by Shalabh

,

Lecture 11, by Raghu Nandan Sengupta

,

Lecture 11: Commodity Basic Risk (Part-II), by Prabina Rajib

,

Lecture 11: The Analysis of Variance (ANOVA)-IV, by Raghunandan Sengupta

,

Lecture 12 : Professional Ethics & Values in Teaching (Contd.), by Atasi Mohanty

,

Lecture 12-Estimation of Model Parameters in Multiple Linear Regression Model, by Shalabh

,

Lecture 12, by Raghu Nandan Sengupta

,

Lecture 12: Minimum Variance Hedge Ratio (Part I), by Prabina Rajib

,

Lecture 12: The Analysis of Variance (ANOVA)-V, by Raghunandan Sengupta

,

Lecture 13-Estimation of Model Parameters in Multiple Linear Regression Model (Continued), by Shalabh

,

Lecture 13: Minimum Variance Hedge Ratio (Part II), by Prabina Rajib

,

Lecture 13: Professional Ethics & Values in Teaching (Contd.), by Atasi Mohanty

,

Lecture 13: The Analysis of Variance (ANOVA)-VI, by Raghunandan Sengupta

,

Lecture 14-Standardized Regression Coefficients and Testing of Hypothesis, by Shalabh

,

Lecture 14: Commodity Indexes (Part-I), by Prabina Rajib

,

Lecture 14: Emotional Intelligence and Educational Leadership, by Atasi Mohanty

,

Lecture 14: The Analysis of Variance (ANOVA)-VII and Introduction to Factorial Design, by Raghunandan Sengupta

,

Lecture 15-Testing of Hypothesis (Continued) and Goodness of Fit of the Model, by Shalabh

,