Motivation to do Track 05
Theme: The organization of values extracted from databases as a probability distribution function of a random variable is a powerful tool for detecting anomalous patterns. In particular, the procedure for obtaining probability distributions makes it easier to identify extremely high or low values, i.e., outliers. This can serve as a basis for carrying out more assertive inspections.
This learning path is designed to develop the following skills:
Examples of random variables.
How to derive the probability distribution of random variables from the probability of events.
Types of discrete random variables probability distributions: Discrete Uniform, Bernoulli, Binomial, Hypergeometric, Poisson.
These concepts will be applied in the following practices with real data:
The distribution of weight, dimension, and value per HS6 code from the INTTRA dataset.
How to fit a particular distribution?
Employing standard deviation to do an assessment of outliers as a certain percentage of the population.
Estimation of probability to find fraud as a sum of Bernoulli.
A primer approach to compute total time spent in a system: Exponential distribution application.
Gaussian mixture and its application (page 449).
The next links will help in this learning journey. Have a good learning journey.
The journey map of Track 05
Badges
Random Variable
GET PROB 2
Bernoulli Distrib,
BinomialDistrib,
Hyperg.Distrib,
PoissonDistrib,
Inspect LVL 2
MAPS LVL 2
1. Concepts & Definitions
1.1. Example of random variables
1.2. Probability of events to random variables
1.4. Discrete uniform distribution of probability
1.5. Bernoulli distribution of probability
1.6. Binomial distribution of probability
1.7. Hypergeometrical distribution of probability
2. Problem & Solution
1. Concepts & Definitions
2. Problem & Solution