NOC:Probability and Statistics

Lecture 1 - Sets, Classes, Collection

Lecture 2 - Sequence of Sets

Lecture 3 - Ring, Field (Algebra)

Lecture 4 - Sigma-Ring, Sigma-Field, Monotone Class

Lecture 5 - Random Experiment, Events

Lecture 6 - Definitions of Probability

Lecture 7 - Properties of Probability Function - I

Lecture 8 - Properties of Probability Function - II

Lecture 9 - Conditional Probability

Lecture 10 - Independence of Events

Lecture 11 - Problems in Probability - I

Lecture 12 - Problems in Probability - II

Lecture 13 - Random Variables

Lecture 14 - Probability Distribution of a Random Variable - I

Lecture 15 - Probability Distribution of a Random Variable - II

Lecture 16 - Moments

Lecture 17 - Characteristics of Distributions - I

Lecture 18 - Characteristics of Distributions - II

Lecture 19 - Special Discrete Distributions - I

Lecture 20 - Special Discrete Distributions - II

Lecture 21 - Special Discrete Distributions - III

Lecture 22 - Poisson Process - I

Lecture 23 - Poisson Process - II

Lecture 24 - Special Continuous Distributions - I

Lecture 25 - Special Continuous Distributions - II

Lecture 26 - Special Continuous Distributions - III

Lecture 27 - Special Continuous Distributions - IV

Lecture 28 - Special Continuous Distributions - V

Lecture 29 - Normal Distribution

Lecture 30 - Problems on Normal Distribution

Lecture 31 - Problems on Special Distributions - I

Lecture 32 - Problems on Special Distributions - II

Lecture 33 - Function of a random variable - I

Lecture 34 - Function of a random variable - II

Lecture 35 - Joint Distributions - I

Lecture 36 - Joint Distributions - II

Lecture 37 - Independence, Product Moments

Lecture 38 - Linearity Property of Correlation and Examples

Lecture 39 - Bivariate Normal Distribution - I

Lecture 40 - Bivariate Normal Distribution - II

Lecture 41 - Additive Properties of Distributions - I

Lecture 42 - Additive Properties of Distributions - II

Lecture 43 - Transformation of Random Variables

Lecture 44 - Distribution of Order Statistics

Lecture 45 - Basic Concepts

Lecture 46 - Chi-Square Distribution

Lecture 47 - Chi-Square Distribution (Continued...), t-Distribution

Lecture 48 - F-Distribution

Lecture 49 - Descriptive Statistics - I

Lecture 50 - Descriptive Statistics - II

Lecture 51 - Descriptive Statistics - III

Lecture 52 - Descriptive Statistics - IV

Lecture 53 - Introduction to Estimation

Lecture 54 - Unbiased and Consistent Estimators

Lecture 55 - LSE, MME

Lecture 56 - Examples on MME, MLE

Lecture 57 - Examples on MLE - I

Lecture 58 - Examples on MLE - II, MSE

Lecture 59 - UMVUE, Sufficiency, Completeness

Lecture 60 - Rao - Blackwell Theorem and Its Applications

Lecture 61 - Confidence Intervals - I

Lecture 62 - Confidence Intervals - II

Lecture 63 - Confidence Intervals - III

Lecture 64 - Confidence Intervals - IV

Lecture 65 - Basic Definitions

Lecture 66 - Two Types of Errors

Lecture 67 - Neyman-Pearson Fundamental Lemma

Lecture 68 - Applications of N-P Lemma - I

Lecture 69 - Applications of N-P Lemma - II

Lecture 70 - Testing for Normal Mean

Lecture 71 - Testing for Normal Variance

Lecture 72 - Large Sample Test for Variance and Two Sample Problem

Lecture 73 - Paired t-Test

Lecture 74 - Examples

Lecture 75 - Testing Equality of Proportions

Lecture 76 - Chi-Square Test for Goodness Fit - I

Lecture 77 - Chi-Square Test for Goodness Fit - II

Lecture 78 - Testing for Independence in rxc Contingency Table - I

Lecture 79 - Testing for Independence in rxc Contingency Table - II