Statistical learning for Reliability Analysis

Por: Swayam . en: , ,

Week 1: Introduction to reliability, reliability estimation, concept of statistical learning, advanced techniques to reliability analysis.Week 2:Probability distribution techniques: discrete and continuous probability distributions and their applications to reliability estimation modeling.Week 3:Sampling distribution techniques and their different applications for reliability prediction.Week 4:Statistical inference technique-I (Parametric-based approaches: Hypothesis testing, Confidence interval estimation).Week 5:Case studies for reliability analysis with parametric-based approaches.Week 6:Statistical inference techniques-II (Non-parametric-based approaches: Correlation analysis, Relation analysis, Regression analysis).Week 7:Case studies for reliability analysis with non-parametricbased approachesWeek 8:Statistical learning with single population, pair t-tests techniques. Illustration with applications to reliability analysis.Week 9:Statistical learning with more than one population, ANOVA techniques. Illustration with applications to reliability analysis.Week 10:Maximum likelihood estimation techniques. Illustration with applications to reliability analysis.Week 11:Statistical method of data classification. Illustration with applications to reliability analysis.Week 12:Entropy and its applications to statistical learning. Illustration with applications to reliability analysis.

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