The page discrete distributions module Data Analysis displays the theoretical representation of the 3 main discrete distributions:
Hypergeometric distributions:
💡Definition: Hypergeometric law
The parameters are
- N: Total number of samples
- D: Total number of faults
- n: Number of samples taken
- x: Number of defects sampled
- Cumulative probability: Probability of sampling x defects or less
- D min: Minimum number of defects in total sample (at 95%)
- D max: Maximum number of defects in the total sample (at 95%)
Binomial distributions:
💡Definition: Binomial distributions
The parameters are
- p: probability of default
- n: Number of samples taken
- x: Number of defects sampled
- Cumulative probability: Probability of sampling x defects or less
- p min: minimum probability of default (at 95%)
- p max: maximum probability of default (at 95%)
Poisson distribution:
💡Definition: Poisson's law
The parameters are
- lambda: lambda parameter of the poisson distribution
- x: Number of defects sampled
- Cumulative probability: Probability of sampling x defects or less
- lambda min: minimum lambda (at 95%)
- lambda max: maximum lambda (at 95%)