Introduction and overview – Random Variables – Discrete Probability Distributions – Example Problems – Continuous Probability Distributions – Normal and Log Normal Probability Distributions – t-distribution – Chi-Square Distribution – F-distribution – Example Problems – Example Problems – Distribution of the random sample mean – Central Limit Theorem and its applications – Confidence Intervals – Maximum Likelihood Parameter Estimation – Example Problems – Formulation and Testing of Hypotheses – Errors in Hypothesis Testing – Hypothesis tests on population means, variances and ratio of variances

Design and Analysis of Single Factor Experiments – Randomized Block Design – Example Problems – Factorial Design with Two Factors – Factorial Design with Multiple Factors – Fractional Factorial Design – Example Problems – Matrix Approach to Linear Regression Analysis – Variance-Covariance Matrix – ANOVA in regression Analysis and Confidence Intervals – Extra Sum of Squares – Lack of Fit Analysis – Example Problems – Properties of Orthogonal Designs – Importance of Center Runs – Central Composite Design – Box Behnken Design and Face Centered Designs – Response Surface Methodology : Method of Steepest Ascent – Identification of optimal process conditions

Other Resources

Course Curriculum

Introduction Details 38:15
Random Variables Details 43:16
Discrete Probability Distributions Details 49:26
Example Set – I Details 47:41
Continuous probability distributions Details 32:52
Normal probability distribution Details 43:49
Exploratory Data Analysis – Part A Details 44:51
Exploratory Data Analysis – Part B Details 46:19
Example Set II Details 50:56
Example Set III Details 36:51
Random samples: Sampling distribution of the mean (Part A) Details 46:27
Random samples: Sampling distribution of the mean (Part B) Details 46:26
Point Estimation Details 46:47
Sampling distributions and the Central Limit Theorem Details 47:1
Example Set – IV Part A Details 47:17
Estimation of Population Parameters Using Moments Details 42:30
Confidence Intervals (Part A) Details 45:20
Confidence Intervals (Part B) Details 45:42
The T-distribution Details 49:34
Chi-square distribution Details 15:43
F-Distribution Details 40:1
Example Set 5 Details 52:39
Hypothesis Testing – Part A Details 45:4
Hypothesis Testing – Part B Details 37:45
Hypothesis Testing – Part C Details 28:56
Analysis of Experiments involving Single Factor – Part A Details 51:44
Analysis of Experiments involving Single Factor – Part B Details 52:1
Blocking and Randomization Details 39:30
Example Set -6 – Part A Details 47:4
Example Set -6 – Part B Details 51:55
Factorial Design of Experiments – Part A Details 50:28
Factorial Design of Experiments – Part B: 22 Factorial Design Details 58:45
Fractional Factorial Design – Part A Details 46:34
Fractional Factorial Design – Part B Details 44:53
Factorial Design of Experiments: Example Set (Part 7A) Details 47:30
Factorial Design of Experiments: Example Set (Part 7B) Details 54:27
Factorial Design of Experiments: Example Set (Part C) Details 42:22
Regression Analysis: Part A Details 52:32
Regression Analysis: Part B Details 43:25
Hypothesis Testing in Linear Regression Details 53:28
Discussion on Regression Output Details 59:22
Regression Analysis : Example Set 8 Details 52:3
Regression Analysis: Example Set 8 Continued Details 38:34
Regression Analysis: Example Set 8 Continued. Details 39:9
Orthogonal Model Fitting Concepts – Part A Details 40:2
Orthogonal Model Fitting Concepts – Part B Details 28:15
Experimental Design Strategies – A Details 45:36
Experimental Design Strategies – B Details 35:35
Experimental Design Strategies – C Details 53:13
Response Surface Methodology – A Details 32:21

This course is delivered by NPTEL, is part of IIT Madras online courses.

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