Such record something does not make sense , look at the origin, application, and more with thinking have value
First, the law of large numbers
(1) law of small numbers:
- If statistics rarely, then the event on the performance of a variety of extreme conditions
- And these cases are accidental event
- He is saying nothing to do with expectations
(2) law of large numbers:
- If the data is large enough, then the probability of events occurring more close to its expected value
Second, the central limit theorem
Given a general any distribution, every I n th random samples from the population, a total of m times pumping. This sample group were then m average value, the average value is too distributed approximately obey
Third, the common distribution
1, evenly distributed
X sample probability interval falls within a ~ b are the same. The probability density for x
2, Bernoulli distribution
The results of the sample only two. For example coin toss, either 0 or 1.
3, binomial distribution
Do Bernoulli experiment n times, each time the results of only 0,1. If n = 1, then obviously Bernoulli distribution
4, Poisson distribution
Suppose we mean the number of known samples appear as λ, the number of occurrences of the sample within a certain period of time, the probability distribution of this sample is also called the Poisson distribution, which belongs to the discrete distribution.
5, exponential distribution
If desired sample occurring within a predetermined time known λ, then its probability distribution at time t of exponential
- Poisson statistics the number belongs to happen
- Statistics exponential distribution has occurred