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- Discrete
- The variable can take only specific countable levels of values (is a 'quantized' variable)
- Example: when throwing a dice the outcome is a discrete (quantized) variable: it can only take six values. The probability distribution (for a fair dice) is constant: 1/6
- Scipy.stats documentation on discrete statistical distributions
- Continuous
- The variable can take any value ('varies continuously') between a minimum and a maximum value. The probability distribution varies accordingly and is usually described by some mathematical expression
- Example: when measuring each individual's height in a group of people the variable 'height' varies between a minimum and a maximum value; there are no preset levels for this variable.
- Scipy.stats documentation on continuous statistical distributions
These are important methods to work with and you should gradually get familiar with them if you are serious with computational statistics. Below we concisely explain the meaning and operation of them. Coding examples are given in next sections discussing specific distributions.
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