For continuous random variables, the limit of the probability of a single point is 0. This enlightens us that the probability equal to 0 is not necessarily an impossible event.
Probability density function is derived : used to describe the distribution of probability. The distribution function is equal to the definite integral of the probability density function from negative infinity to x.
Notice:
(1) For continuous random variables, the single-point probability density is 0
（2）f(x)>=0
(3) The probability density function integrates from negative infinity to positive infinity = 1
(4) If the probability density function f(x) is continuous at point x, then F'(x)=f(x)
Common Continuous Random Variables
1. Uniform distribution
wait for possible
2. Exponential distribution
Exponential distribution has the characteristics of no memory
3. Normal distribution
Normal distribution is also called normal distribution, Gaussian distribution
