Track 06

Motivation to do Track 06

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: 

1. Examples of random variables.

2. How to derive the probability distribution of random variables from the probability of events.

3. Types of continuous random variables probability distributions: Continous Uniform, Exponential distribution, Standard Normal or Gaussian

4. Inverse standard Normal distribution

5. Student's T distribution

These concepts will be applied in the following practices with real data:

1. The distribution of weight, dimension, and value per HS6 code from the OCDB dataset. 

2. How to fit a particular distribution?

3. Employing standard deviation to do an assessment of outliers as a certain percentage of the population.

4. Estimation of probability to find fraud as a sum of Bernoulli.

5. A primer approach to computing total time spent in a system: Exponential distribution application.

6. Gaussian mixture and its application.

The next links will help in this learning journey. Have a good learning journey.