MOOC - Predictive Maintenance Expert
Statistics and Mathematics
Fourth Unit is a part of learning material which introduce mathematic statistic into preventive maintenance process. In this unit, students will know some advanced statistical tools, which they will use to analyse historical machine data and predict their future behaviour.
Conditional expected value and Bayesian inference:
This learning element allows students to know how to calculate probability of some problem occurrence, based on statistical data expectation and inference using Bayesian theory.
PMEx.U4.E6.PC1
Expected value definition:
Student knows how to calculate expected value based on statistical data (historical) under defined condition.
PMEx.U4.E6.PC2
Conditional probability:
Student understand and is able to explain difference between normal and conditional probability
PMEx.U4.E6.PC3
Bayes probability calculation:
Student know how to calculate “a posteriori” probability according to Bayes equation.
PMEx.U4.E6.PC4
Probability forecasting:
Student can explain difference between prior and posterior probability.
PMEx.U4.E6.PC5
Bayesian prediction function calculation:
Student can calculate function of prior and posterior data distribution for Bayesian prediction.