Lecture
The continuous random variable X is evenly distributed in the interval [ a; c ] if its probability density in this interval is constant, i.e. if all values in this interval are equally likely:
 
  (8.1) 
The value of the constant с is determined from the normalization condition:
 
  .  (8.2) 
Distribution function:
 
  , (8.3) 
The numerical characteristics of a uniformly distributed random variable are defined as:
 
  (8.4) 
 
  (8.5) 
The standard deviation of the uniform distribution is
 
  (8.6) 
The uniform distribution of a random variable is completely determined by two parameters: a and b , the interval at which the random variable is defined.
If necessary, you can determine the parameters a and b of the uniform distribution of the known values of the expectation m X and variance D x random variable. For this, a system of equations is made up of the following form:
 
  , (8.7) 
from which the desired parameters are determined.
The probability of a uniformly distributed random variable falling into the interval [α, β) is determined as follows:
 
  where 
 
  Probability density ![]()  | |
  Distribution function ![]()  | |
| Designation |    , ![]()  | 
| Options |    ,    —Shift factor    - scale factor  | 
| Carrier | ![]()  | 
| Probability density |   b \ end {matrix}"> | 
| Distribution function | ![]()  | 
| Expected value | ![]()  | 
| Median | ![]()  | 
| Fashion |   any number of segment ![]()  | 
| Dispersion | ![]()  | 
| Asymmetry coefficient | ![]()  | 
| Coefficient of kurtosis | ![]()  | 
| Informational entropy | ![]()  | 
| Generating function of moments | ![]()  | 
| Characteristic function | ![]()  | 
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Probability theory. Mathematical Statistics and Stochastic Analysis
Terms: Probability theory. Mathematical Statistics and Stochastic Analysis