Discret Random Variable
Countable
Probability distribution function = probability mass funtion (PDF)
Continous Random Variable
Ex.: time to failure of a compressor
Probability distribution function: Denoted as density function (PDF)
Cumultative Distribution Function (CDF)
Dented as
Discrete case:
Continuous case:
Average behavior of X : expressed in terms of expacted value:
deusct (Mittelwert der Grundgesamtheit)
variance:
not working for distributions with two peaks
standard deviation and ratio between standard deviation and mean (variation)
standart deviation
Expectation E[.]
and
Variance expressed using expectation
R(t)
Reliability and Hazard Function
or lamda(t)
Bathtub curve
Bernoulli Distribution
Two possible outcomes:
Binomial Distribution
Geometric Distribution
n Bernoulli trails, Now focos on probabiltity, that first succes comes at the t-th trial
Geometric Distribution (Poisson)
3x requirements
Exponential Distribution
… just modeling useful life. // lamda^-1 is MMTF (meantime to failure), reaching MTTF is R(MTTF) = e^1 =0,37
Last changeda year ago
