It might help if you specified why WHAT was important in random variables.
the statistically independent random variables are uncorrelated but the converse is not true ,i want a counter example,
A random process is a sequence of random variables defined over a period of time.
Variables with values that are determined by chance are called random variables. They can take on different values based on the outcome of a random phenomenon or experiment. Random variables can be classified into two types: discrete, which can take on a finite number of values, and continuous, which can take on an infinite number of values within a given range.
first you make sure you have cake then you cook it in stew;0
Stochastic process is also known as a random process. It is a collection of random variables that represent the evolution of some system of random values over time.
In statistics, there are two main types of random variables: discrete random variables and continuous random variables. Discrete random variables take on a countable number of distinct values, such as the outcome of rolling a die. In contrast, continuous random variables can take on an infinite number of values within a given range, such as the height of individuals. Each type has its own probability distribution and methods of analysis.
Michael O'Flynn has written: 'Probabilities, random variables, and random processes' -- subject(s): Probabilities, Random variables, Signal processing, Stochastic processes
the statistically independent random variables are uncorrelated but the converse is not true ,i want a counter example,
A random process is a sequence of random variables defined over a period of time.
Variables with values that are determined by chance are called random variables. They can take on different values based on the outcome of a random phenomenon or experiment. Random variables can be classified into two types: discrete, which can take on a finite number of values, and continuous, which can take on an infinite number of values within a given range.
Random variables is a function that can produce outcomes with different probability and random variates is the particular outcome of a random variable.
first you make sure you have cake then you cook it in stew;0
Stochastic processes are families of random variables. Real-valued (i.e., continuous) random variables are often defined by their (cumulative) distribution function.
Wai Wan Tsang has written: 'Analysis of the square-the-histogram method for generating discrete random variables' -- subject(s): Random variables
YES.
The sum of two random variables that are normally distributed will be also be normally distributed. Use the link and check out the article. It'll save a cut and paste.
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