TOPIC: Probability Theory
Continuous Distributions
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What is this module about?

Continuous cumulative distribution functions are being introduced under two aspects. On the one hand, they are appropriate/used for modelling in the case of random variables that have many different possible values that can be not integers or may be negative. On the other hand, they also serve for approximation for discrete distributions in order to calculate probabilities more easily. In this module we get to know the most important characteristics of continuous distributions as well as the density that belongs to a continuous cumulative distribution function. We transfer the concept of parameters from the discrete to the continuous distributions. Moreover, some of the most important distribution models are being introduced.



MEDIA
Applet exponential distribution
EXERCISES
Archer
Meantimes on the M345
Daily yields
Pareto distribution
EXAMPLES
Archer
Archer - continuation
Monthly yields
Archer - continuation
Monthly yields - continuation
Example of the inversion method (monthly yields)
Waiting distance to the first occurence of the letter "a"
Breakdowns
Liability damages
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