NOC:Statistical Learning for Reliability Analysis

Media Storage Type : 32 GB USB Stick

NPTEL Subject Matter Expert : Prof. Monalisa Sarma

NPTEL Co-ordinating Institute : IIT Kharagpur

NPTEL Lecture Count : 60

NPTEL Course Size : 6.7 GB

NPTEL PDF Text Transcription : Available and Included

NPTEL Subtitle Transcription : Available and Included (SRT)

Lecture Titles:

Lecture 1 - Introduction to Reliability Engineering
Lecture 2 - Introduction to Statistical Methods in Reliability
Lecture 3 - Concept of Probability and Probability Theory
Lecture 4 - Tutorial on Introduction to RE, SL and Probability Theory - Part I
Lecture 5 - Conditional, Total and Reverse Probability
Lecture 6 - Tutorial on Conditional Probability and Total Probability
Lecture 7 - Introduction to Probability Distributions
Lecture 8 - Introduction to Probability Distributions (Continued...)
Lecture 9 - Discrete Probability Distribution - Part 1
Lecture 10 - Discrete Probability Distribution - Part 2
Lecture 11 - Tutorial on Discrete Probability Distributions
Lecture 12 - Continuous Probability Distributions - Part 1
Lecture 13 - Continuous Probability Distributions - Part 2
Lecture 14 - Tutorial on Continuous Probability Distribution Functions - Part 1
Lecture 15 - Tutorial on Continuous Probability Distribution Functions - Part 2
Lecture 16 - Sampling Distributions - Part 1
Lecture 17 - Sampling Distributions - Part 2
Lecture 18 - Sampling Distributions - Part 3
Lecture 19 - Sampling Distributions - Part 4
Lecture 20 - Sampling Distributions - Part 5
Lecture 21 - Tutorial on Sampling Distributions
Lecture 22 - Statistical Inference - Part 1
Lecture 23 - Statistical Inference - Part 2
Lecture 24 - Statistical Inference - Part 3
Lecture 25 - Tutorial on Statistical Inference
Lecture 26 - Statistical Inference - Part 4
Lecture 27 - Statistical Inference - Part 5
Lecture 28 - Tutorial on Confidence Interval
Lecture 29 - Statistical Inference - Part 6
Lecture 30 - Statistical Inference - Part 7
Lecture 31 - Statistical Inference - Part 8
Lecture 32 - ANOVA - I
Lecture 33 - ANOVA - II
Lecture 34 - ANOVA - III
Lecture 35 - ANOVA - IV
Lecture 36 - ANOVA - V
Lecture 37 - ANOVA - VI
Lecture 38 - Correlation Analysis - Part I
Lecture 39 - Correlation Analysis - Part II
Lecture 40 - Regression Analysis - Part I
Lecture 41 - Regression Analysis - Part II
Lecture 42 - Regression Analysis - Part III
Lecture 43 - Tutorial on Relation Analysis
Lecture 44 - Auto-Regression Analysis
Lecture 45 - Logistic Regression - Part I
Lecture 46 - Logistic Regression - Part II
Lecture 47 - Logistic Regression - Part III
Lecture 48 - Tutorial on Logistic Regression
Lecture 49 - Introduction
Lecture 50 - Bayesian Classification - Part I
Lecture 51 - Bayesian Classification - Part II
Lecture 52 - k-Nearest Neighbor Classification
Lecture 53 - Tutorial on Classification Techniques
Lecture 54 - Support Vector Machine - Part I
Lecture 55 - Support Vector Machine - Part II
Lecture 56 - Support Vector Machine - Part III
Lecture 57 - Support Vector Machine - Part IV
Lecture 58 - Support Vector Machine - Part V
Lecture 59 - Support Vector Machine - Part VI
Lecture 60 - Tutorial on SVM