|
2 |
Brief Review of Probabilistic Modeling |
|
2.1 |
Experiment, Sample Space, and Events |
|
2.2 |
Event Probabilities |
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2.3 |
Random Variables |
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2.4 |
Probability Mass Function |
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2.5 |
Conditional PMF's and Independence |
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2.6 |
Functions of Random Variables |
|
2.7 |
Expectation |
|
2.8 |
The z-transform |
|
2.9 |
Often-Used PMF's |
| |
2.9.1 |
Bernoulli PMF |
| |
2.9.2 |
Geometric PMF |
| |
2.9.3 |
Binomial PMF |
| |
2.9.4 |
Poisson PMF |
|
2.10 |
Probability Density Functions |
| |
2.10.1 |
Conditional PDF's and independence |
| |
2.10.2 |
Expectation |
| |
2.10.3 |
Unit impulse function |
| |
2.10.4 |
The s-transform |
|
2.11 |
Often-Used PDF's |
| |
2.11.1 |
Uniform PDF |
| |
2.11.2 |
Exponential PDF |
| |
2.11.3 |
Erlang PDF |
| |
2.11.4 |
Gaussian PDF |
|
2.12 |
Poisson Process |
| |
2.12.1 |
Postulates of a Poisson process |
| |
2.12.2 |
Interarrival times |
| |
2.12.3 |
Unordered arrival times |
| |
2.12.4 |
Multiple independent Poisson processes |
|
2.13 |
Random Incidence |
|
2.14 |
Pedestrian Crossing Problem |
|
2.15 |
Conclusion |
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*** |
Problems |
