NOC:Introduction to Probability (with examples using R)

Media Storage Type : 32 GB USB Stick

NPTEL Subject Matter Expert : Prof. Siva Athreya

NPTEL Co-ordinating Institute : ISI Bangalore

NPTEL Lecture Count : 46

NPTEL Course Size : 3.8 GB

NPTEL PDF Text Transcription : Available and Included

NPTEL Subtitle Transcription : Available and Included (SRT)

Lecture Titles:

Lecture 1 - Sample Space, Events and Probability
Lecture 2 - Properties of Probability
Lecture 3 - Equally likely Outcomes
Lecture 4 - Conditional Probability
Lecture 5 - Bayes Theorem
Lecture 6 - Independence - Part 1
Lecture 7 - Independence - Part 2
Lecture 8 - Sampling and Repeated Trials
Lecture 9 - Sampling and Repeated Trials - Part 1
Lecture 10 - Sampling and Repeated Trials - Part 2
Lecture 11 - Sampling with and Without Replacement
Lecture 12 - Sampling without Replacement
Lecture 13 - Hypergeometric Distribution and Discrete Random Variables
Lecture 14 - Discrete Random Variables - Part 1
Lecture 15 - Discrete Random Variables - Part 2
Lecture 16 - Conditional, Joint and Marginal Distributions
Lecture 17 - Memoryless property of Geometric Distribution
Lecture 18 - Functions of Random Variables
Lecture 19 - Sums of Independent Random Variables
Lecture 20 - Functions and Independence
Lecture 21 - Expectation of Random Variables
Lecture 22 - Properties of Expectation
Lecture 23 - Expectation: Independence and Functions
Lecture 24 - Variance of Discrete Random Variables
Lecture 25 - Markov and Chebyshev Inequalities
Lecture 26 - Conditional Expectation and Covariance
Lecture 27 - Continuous Random Variables - Part 1
Lecture 28 - Continuous Random Variables - Part 2
Lecture 29 - Distribution Function
Lecture 30 - Exponential and Normal Random Variable
Lecture 31 - Normal Random Variable
Lecture 32 - Change of Variable
Lecture 33 - Joint Distribution of Continuous Random Variables
Lecture 34 - Marginal Density and Independence
Lecture 35 - Conditional Density
Lecture 36 - Sums of Independent Random Variables
Lecture 37 - Quotient of Independent Random Variables
Lecture 38 - Expectation and Variance of Continuous Random Variables
Lecture 39 - Sampling Distribution and Sample Mean
Lecture 40 - Weak Law of Large Numbers
Lecture 41 - Revisit of Variance and Expectation
Lecture 42 - Revisit of Properties of Variance
Lecture 43 - Revisit Weak Law of Large Numbers
Lecture 44 - Demoivre-Laplace Central Limit Theorem and Normal Random Variables
Lecture 45 - Revisit Normal Random Variables
Lecture 46 - Normal Tables, Mean and Variance