Understanding the common continuous probability distribution
In this section, you will see the three most important continuous distributions:
- Uniform distribution
- Exponential distribution
- Gaussian/normal distribution
Let's look at each of these in detail.
Uniform distribution
Uniform distribution is an important uniform distribution. It is useful computationally because many other distributions can be simulated with uniform distribution. In earlier code examples, I used random.random() in the simulation of the Bernoulli distribution, which itself generates a uniform random variable in the range [0,1].
For a uniformly distributed random variable on [0,1], the mean is 0.5 and the variance is 
. This is a good number to remember for a data scientist role interview.
For a general uniform distribution, If the range is [a,b], the PDF reads as 
if x is in the range [a,b]. The mean and variance become 
and 
, respectively. If you remember calculus, check...
